An Appeal to the Global Health Community for a Tripartite Innovation: An "Essential Diagnostics List," "Health in All Policies," and "See-Through 21(st) Century Science and Ethics".

PubMed

Dove, Edward S; Barlas, I Ömer; Birch, Kean; Boehme, Catharina; Borda-Rodriguez, Alexander; Byne, William M; Chaverneff, Florence; Coşkun, Yavuz; Dahl, Marja-Liisa; Dereli, Türkay; Diwakar, Shyam; Elbeyli, Levent; Endrenyi, Laszlo; Eroğlu-Kesim, Belgin; Ferguson, Lynnette R; Güngör, Kıvanç; Gürsoy, Ulvi; Hekim, Nezih; Huzair, Farah; Kaushik, Kabeer; Kickbusch, Ilona; Kıroğlu, Olcay; Kolker, Eugene; Könönen, Eija; Lin, Biaoyang; Llerena, Adrian; Malhan, Faruk; Nair, Bipin; Patrinos, George P; Şardaş, Semra; Sert, Özlem; Srivastava, Sanjeeva; Steuten, Lotte M G; Toraman, Cengiz; Vayena, Effy; Wang, Wei; Warnich, Louise; Özdemir, Vural

2015-08-01

Diagnostics spanning a wide range of new biotechnologies, including proteomics, metabolomics, and nanotechnology, are emerging as companion tests to innovative medicines. In this Opinion, we present the rationale for promulgating an "Essential Diagnostics List." Additionally, we explain the ways in which adopting a vision for "Health in All Policies" could link essential diagnostics with robust and timely societal outcomes such as sustainable development, human rights, gender parity, and alleviation of poverty. We do so in three ways. First, we propose the need for a new, "see through" taxonomy for knowledge-based innovation as we transition from the material industries (e.g., textiles, plastic, cement, glass) dominant in the 20(th) century to the anticipated knowledge industry of the 21st century. If knowledge is the currency of the present century, then it is sensible to adopt an approach that thoroughly examines scientific knowledge, starting with the production aims, methods, quality, distribution, access, and the ends it purports to serve. Second, we explain that this knowledge trajectory focus on innovation is crucial and applicable across all sectors, including public, private, or public-private partnerships, as it underscores the fact that scientific knowledge is a co-product of technology, human values, and social systems. By making the value systems embedded in scientific design and knowledge co-production transparent, we all stand to benefit from sustainable and transparent science. Third, we appeal to the global health community to consider the necessary qualities of good governance for 21st century organizations that will embark on developing essential diagnostics. These have importance not only for science and knowledge-based innovation, but also for the ways in which we can build open, healthy, and peaceful civil societies today and for future generations.

Gut feelings as a third track in general practitioners' diagnostic reasoning.

PubMed

Stolper, Erik; Van de Wiel, Margje; Van Royen, Paul; Van Bokhoven, Marloes; Van der Weijden, Trudy; Dinant, Geert Jan

2011-02-01

General practitioners (GPs) are often faced with complicated, vague problems in situations of uncertainty that they have to solve at short notice. In such situations, gut feelings seem to play a substantial role in their diagnostic process. Qualitative research distinguished a sense of alarm and a sense of reassurance. However, not every GP trusted their gut feelings, since a scientific explanation is lacking. This paper explains how gut feelings arise and function in GPs' diagnostic reasoning. The paper reviews literature from medical, psychological and neuroscientific perspectives. Gut feelings in general practice are based on the interaction between patient information and a GP's knowledge and experience. This is visualized in a knowledge-based model of GPs' diagnostic reasoning emphasizing that this complex task combines analytical and non-analytical cognitive processes. The model integrates the two well-known diagnostic reasoning tracks of medical decision-making and medical problem-solving, and adds gut feelings as a third track. Analytical and non-analytical diagnostic reasoning interacts continuously, and GPs use elements of all three tracks, depending on the task and the situation. In this dual process theory, gut feelings emerge as a consequence of non-analytical processing of the available information and knowledge, either reassuring GPs or alerting them that something is wrong and action is required. The role of affect as a heuristic within the physician's knowledge network explains how gut feelings may help GPs to navigate in a mostly efficient way in the often complex and uncertain diagnostic situations of general practice. Emotion research and neuroscientific data support the unmistakable role of affect in the process of making decisions and explain the bodily sensation of gut feelings.The implications for health care practice and medical education are discussed.

Gut Feelings as a Third Track in General Practitioners’ Diagnostic Reasoning

PubMed Central

Van de Wiel, Margje; Van Royen, Paul; Van Bokhoven, Marloes; Van der Weijden, Trudy; Dinant, Geert Jan

2010-01-01

Background General practitioners (GPs) are often faced with complicated, vague problems in situations of uncertainty that they have to solve at short notice. In such situations, gut feelings seem to play a substantial role in their diagnostic process. Qualitative research distinguished a sense of alarm and a sense of reassurance. However, not every GP trusted their gut feelings, since a scientific explanation is lacking. Objective This paper explains how gut feelings arise and function in GPs’ diagnostic reasoning. Approach The paper reviews literature from medical, psychological and neuroscientific perspectives. Conclusions Gut feelings in general practice are based on the interaction between patient information and a GP’s knowledge and experience. This is visualized in a knowledge-based model of GPs’ diagnostic reasoning emphasizing that this complex task combines analytical and non-analytical cognitive processes. The model integrates the two well-known diagnostic reasoning tracks of medical decision-making and medical problem-solving, and adds gut feelings as a third track. Analytical and non-analytical diagnostic reasoning interacts continuously, and GPs use elements of all three tracks, depending on the task and the situation. In this dual process theory, gut feelings emerge as a consequence of non-analytical processing of the available information and knowledge, either reassuring GPs or alerting them that something is wrong and action is required. The role of affect as a heuristic within the physician’s knowledge network explains how gut feelings may help GPs to navigate in a mostly efficient way in the often complex and uncertain diagnostic situations of general practice. Emotion research and neuroscientific data support the unmistakable role of affect in the process of making decisions and explain the bodily sensation of gut feelings.The implications for health care practice and medical education are discussed. PMID:20967509

Diagnostics aid for mass spectrometer trouble-shooting

NASA Astrophysics Data System (ADS)

Filby, E. E.; Rankin, R. A.; Webb, G. W.

The MS Expert system provides problem diagnostics for instruments used in the Mass Spectrometry Laboratory (MSL). The most critical results generated on these mass spectrometers are the uranium concentration and isotopic content data used for process control and materials accountability at the Idaho Chemical Processing Plant. The two purposes of the system are: (1) to minimize instrument downtime and thereby provide the best possible support to the Plant, and (2) to improve long-term data quality. This system combines the knowledge of several experts on mass spectrometry to provide a diagnostic tool, and can make these skills available on a more timely basis. It integrates code written in the Pascal language with a knowledge base entered into a commercial expert system shell. The user performs some preliminary status checks, and then selects from among several broad diagnostic categories. These initial steps provide input to the rule base. The overall analysis provides the user with a set of possible solutions to the observed problems, graded as to their probabilities. Besides the trouble-shooting benefits expected from this system, it will also provide structures diagnostic training for lab personnel. In addition, development of the system knowledge base has already produced a better understanding of instrument behavior. Two key findings are that a good user interface is necessary for full acceptance of the tool, and a development system should include standard programming capabilities as well as the expert system shell.

Case-based tutoring from a medical knowledge base.

PubMed

Chin, H L; Cooper, G F

1989-01-01

The past decade has seen the emergence of programs that make use of large knowledge bases to assist physicians in diagnosis within the general field of internal medicine. One such program, Internist-I, contains knowledge about over 600 diseases, covering a significant proportion of internal medicine. This paper describes the process of converting a subset of this knowledge base--in the area of cardiovascular diseases--into a probabilistic format, and the use of this resulting knowledge base to teach medical diagnostic knowledge. The system (called KBSimulator--for Knowledge-Based patient Simulator) generates simulated patient cases and uses these cases as a focal point from which to teach medical knowledge. This project demonstrates the feasibility of building an intelligent, flexible instructional system that uses a knowledge base constructed primarily for medical diagnosis.

Dutch Research on Knowledge-Based Instructional Systems: Introduction to the Special Issue.

ERIC Educational Resources Information Center

van Merrienboer, Jeroen J. G.

1994-01-01

Provides an overview of this issue that reviews Dutch research concerning knowledge-based instructional systems. Topics discussed include experimental research, conceptual models, design considerations, and guidelines; the design of student diagnostic modules, instructional modules, and interface modules; second-language teaching; intelligent…

Development and Evaluation of a Diagnostic Documentation Support System using Knowledge Processing

NASA Astrophysics Data System (ADS)

Makino, Kyoko; Hayakawa, Rumi; Terai, Koichi; Fukatsu, Hiroshi

In this paper, we will introduce a system which supports creating diagnostic reports. Diagnostic reports are documents by doctors of radiology describing the existence and nonexistence of abnormalities from the inspection images, such as CT and MRI, and summarize a patient's state and disease. Our system indicates insufficiencies in these reports created by younger doctors, by using knowledge processing based on a medical knowledge dictionary. These indications are not only clerical errors, but the system also analyzes the purpose of the inspection and determines whether a comparison with a former inspection is required, or whether there is any shortage in description. We verified our system by using actual data of 2,233 report pairs, a pair comprised of a report written by a younger doctor and a check result of the report by an experienced doctor. The results of the verification showed that the rules of string analysis for detecting clerical errors and sentence wordiness obtained a recall of over 90% and a precision of over 75%. Moreover, the rules based on a medical knowledge dictionary for detecting the lack of required comparison with a former inspection and the shortage in description for the inspection purpose obtained a recall of over 70%. From these results, we confirmed that our system contributes to the quality improvement of diagnostic reports. We expect that our system can comprehensively support diagnostic documentations by cooperating with the interface which refers to inspection images or past reports.

Model of critical diagnostic reasoning: achieving expert clinician performance.

PubMed

Harjai, Prashant Kumar; Tiwari, Ruby

2009-01-01

Diagnostic reasoning refers to the analytical processes used to determine patient health problems. While the education curriculum and health care system focus on training nurse clinicians to accurately recognize and rescue clinical situations, assessments of non-expert nurses have yielded less than satisfactory data on diagnostic competency. The contrast between the expert and non-expert nurse clinician raises the important question of how differences in thinking may contribute to a large divergence in accurate diagnostic reasoning. This article recognizes superior organization of one's knowledge base, using prototypes, and quick retrieval of pertinent information, using similarity recognition as two reasons for the expert's superior diagnostic performance. A model of critical diagnostic reasoning, using prototypes and similarity recognition, is proposed and elucidated using case studies. This model serves as a starting point toward bridging the gap between clinical data and accurate problem identification, verification, and management while providing a structure for a knowledge exchange between expert and non-expert clinicians.

Bayes' theorem application in the measure information diagnostic value assessment

NASA Astrophysics Data System (ADS)

Orzechowski, Piotr D.; Makal, Jaroslaw; Nazarkiewicz, Andrzej

2006-03-01

The paper presents Bayesian method application in the measure information diagnostic value assessment that is used in the computer-aided diagnosis system. The computer system described here has been created basing on the Bayesian Network and is used in Benign Prostatic Hyperplasia (BPH) diagnosis. The graphic diagnostic model enables to juxtapose experts' knowledge with data.

Diagnostic reasoning and underlying knowledge of students with preclinical patient contacts in PBL.

PubMed

Diemers, Agnes D; van de Wiel, Margje W J; Scherpbier, Albert J J A; Baarveld, Frank; Dolmans, Diana H J M

2015-12-01

Medical experts have access to elaborate and integrated knowledge networks consisting of biomedical and clinical knowledge. These coherent knowledge networks enable them to generate more accurate diagnoses in a shorter time. However, students' knowledge networks are less organised and students have difficulties linking theory and practice and transferring acquired knowledge. Therefore we wanted to explore the development and transfer of knowledge of third-year preclinical students on a problem-based learning (PBL) course with real patient contacts. Before and after a 10-week PBL course with real patients, third-year medical students were asked to think out loud while diagnosing four types of paper patient problems (two course cases and two transfer cases), and explain the underlying pathophysiological mechanisms of the patient features. Diagnostic accuracy and time needed to think through the cases were measured. The think-aloud protocols were transcribed verbatim and different types of knowledge were coded and quantitatively analysed. The written pathophysiological explanations were translated into networks of concepts. Both the concepts and the links between concepts in students' networks were compared to model networks. Over the course diagnostic accuracy increased, case-processing time decreased, and students used less biomedical and clinical knowledge during diagnostic reasoning. The quality of the pathophysiological explanations increased: the students used more concepts, especially more model concepts, and they used fewer wrong concepts and links. The findings differed across course and transfer cases. The effects were generally less strong for transfer cases. Students' improved diagnostic accuracy and the improved quality of their knowledge networks suggest that integration of biomedical and clinical knowledge took place during a 10-week course. The differences between course and transfer cases demonstrate that transfer is complex and time-consuming. We therefore suggest offering students many varied patient contacts with the same underlying pathophysiological mechanism and encouraging students to link biomedical and clinical knowledge. © 2015 John Wiley & Sons Ltd.

Intelligent Diagnostic Assistant for Complicated Skin Diseases through C5's Algorithm.

PubMed

Jeddi, Fatemeh Rangraz; Arabfard, Masoud; Kermany, Zahra Arab

2017-09-01

Intelligent Diagnostic Assistant can be used for complicated diagnosis of skin diseases, which are among the most common causes of disability. The aim of this study was to design and implement a computerized intelligent diagnostic assistant for complicated skin diseases through C5's Algorithm. An applied-developmental study was done in 2015. Knowledge base was developed based on interviews with dermatologists through questionnaires and checklists. Knowledge representation was obtained from the train data in the database using Excel Microsoft Office. Clementine Software and C5's Algorithms were applied to draw the decision tree. Analysis of test accuracy was performed based on rules extracted using inference chains. The rules extracted from the decision tree were entered into the CLIPS programming environment and the intelligent diagnostic assistant was designed then. The rules were defined using forward chaining inference technique and were entered into Clips programming environment as RULE. The accuracy and error rates obtained in the training phase from the decision tree were 99.56% and 0.44%, respectively. The accuracy of the decision tree was 98% and the error was 2% in the test phase. Intelligent diagnostic assistant can be used as a reliable system with high accuracy, sensitivity, specificity, and agreement.

Longitudinal Retention of Anatomical Knowledge in Second-year Medical Students

ERIC Educational Resources Information Center

Doomernik, Denise E.; van Goor, Harry; Kooloos, Jan G. M.; ten Broek, Richard P.

2017-01-01

The Radboud University Medical Center has a problem-based, learner-oriented, horizontally, and vertically integrated medical curriculum. Anatomists and clinicians have noticed students' decreasing anatomical knowledge and the disability to apply knowledge in diagnostic reasoning and problem solving. In a longitudinal cohort, the retention of…

Impact of Diagnosticity on the Adequacy of Models for Cognitive Diagnosis under a Linear Attribute Structure: A Simulation Study

ERIC Educational Resources Information Center

de La Torre, Jimmy; Karelitz, Tzur M.

2009-01-01

Compared to unidimensional item response models (IRMs), cognitive diagnostic models (CDMs) based on latent classes represent examinees' knowledge and item requirements using discrete structures. This study systematically examines the viability of retrofitting CDMs to IRM-based data with a linear attribute structure. The study utilizes a procedure…

A diagnostic prototype of the potable water subsystem of the Space Station Freedom ECLSS

NASA Technical Reports Server (NTRS)

Lukefahr, Brenda D.; Rochowiak, Daniel M.; Benson, Brian L.; Rogers, John S.; Mckee, James W.

1989-01-01

In analyzing the baseline Environmental Control and Life Support System (ECLSS) command and control architecture, various processes are found which would be enhanced by the use of knowledge based system methods of implementation. The most suitable process for prototyping using rule based methods are documented, while domain knowledge resources and other practical considerations are examined. Requirements for a prototype rule based software system are documented. These requirements reflect Space Station Freedom ECLSS software and hardware development efforts, and knowledge based system requirements. A quick prototype knowledge based system environment is researched and developed.

Approach to building knowledge bases in information-measuring systems diagnostics of acute leukemias

NASA Astrophysics Data System (ADS)

Nikitaev, V. G.; Pronichev, A. N.; Polyakov, E. V.; Dmitrieva, V. V.

2018-01-01

The paper describes an approach for the formation of the reference base of peripheral blood cells and bone marrow in information-measuring systems of acute leukemia diagnostics. The proposed approach has allowed to create a system, that is enable peer evaluation of blood cells needed for the training of recognition systems when carrying out microscopic studies.

Domain knowledge patterns in pedagogical diagnostics

NASA Astrophysics Data System (ADS)

Miarka, Rostislav

2017-07-01

This paper shows a proposal of representation of knowledge patterns in RDF(S) language. Knowledge patterns are used for reuse of knowledge. They can be divided into two groups - Top-level knowledge patterns and Domain knowledge patterns. Pedagogical diagnostics is aimed at testing of knowledge of students at primary and secondary school. An example of domain knowledge pattern from pedagogical diagnostics is part of this paper.

Evidence-based development of a diagnosis-dependent therapy planning system and its implementation in modern diagnostic software.

PubMed

Ahlers, M O; Jakstat, H A

2005-07-01

The prerequisite for structured individual therapy of craniomandibular dysfunctions is differential diagnostics. Suggestions for the structured recording of findings and their structured evaluation beyond the global diagnosis of "craniomandibular disorders" have been published. Only this structured approach enables computerization of the diagnostic process. The respective software is available for use in practice (CMDcheck for CMD screening, CMDfact for the differential diagnostics). Based on this structured diagnostics, knowledge-based therapy planning is also conceivable. The prerequisite for this would be a model of achieving consensus on the indicated forms of therapy related to the diagnosis. Therefore, a procedure for evidence-based achievement of consensus on suitable forms of therapy in CMD was developed first in multicentric cooperation, and then implemented in corresponding software. The clinical knowledge of experienced specialists was included consciously for the consensus achievement process. At the same time, anonymized mathematical statistical evaluations were used for control and objectification. Different examiners form different departments of several universities working independently of one another assigned the theoretically conceiveable therapeutic alternatives to the already published diagnostic scheme. After anonymization, the correlation of these assignments was then calculated mathematically. For achieving consensus in those cases for which no agreement initally existed, agreement was subsequently arrived at in the course of a consensus conference on the basis of literature evaluations and the discussion of clinical case examples. This consensus in turn finally served as the basis of a therapy planner implemented in the above-mentioned diagnostic software CMDfact. Contributing to quality assurance, the principles of programming this assistant as well as the interface for linking into the diagnostic software are documented and also published here.

Spacelab Life Sciences-1 electrical diagnostic expert system

NASA Technical Reports Server (NTRS)

Kao, C. Y.; Morris, W. S.

1989-01-01

The Spacelab Life Sciences-1 (SLS-1) Electrical Diagnostic (SLED) expert system is a continuous, real time knowledge-based system to monitor and diagnose electrical system problems in the Spacelab. After fault isolation, the SLED system provides corrective procedures and advice to the ground-based console operator. The SLED system updates its knowledge about the status of Spacelab every 3 seconds. The system supports multiprocessing of malfunctions and allows multiple failures to be handled simultaneously. Information which is readily available via a mouse click includes: general information about the system and each component, the electrical schematics, the recovery procedures of each malfunction, and an explanation of the diagnosis.

Effects of a Web-Based Decision Aid Regarding Diagnostic Self-Testing. A Single-Blind Randomized Controlled Trial

ERIC Educational Resources Information Center

Ickenroth, Martine H. P.; Grispen, J. E. J.; de Vries, N. K.; Dinant, G. J.; Ronda, G.; van der Weijden, T.

2016-01-01

Currently, there are many diagnostic self-tests on body materials available to consumers. The aim of this study was to assess the effect of an online decision aid on diagnostic self-testing for cholesterol and diabetes on knowledge among consumers with an intention to take these tests. A randomized controlled trial was designed. A total of 1259…

Autonomous power expert system

NASA Technical Reports Server (NTRS)

Ringer, Mark J.; Quinn, Todd M.

1990-01-01

The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control technologies to the Space Station Freedom Electrical Power Systems (SSF/EPS). The objectives of the program are to establish artificial intelligence/expert system technology paths, to create knowledge based tools with advanced human-operator interfaces, and to integrate and interface knowledge-based and conventional control schemes. This program is being developed at the NASA-Lewis. The APS Brassboard represents a subset of a 20 KHz Space Station Power Management And Distribution (PMAD) testbed. A distributed control scheme is used to manage multiple levels of computers and switchgear. The brassboard is comprised of a set of intelligent switchgear used to effectively switch power from the sources to the loads. The Autonomous Power Expert System (APEX) portion of the APS program integrates a knowledge based fault diagnostic system, a power resource scheduler, and an interface to the APS Brassboard. The system includes knowledge bases for system diagnostics, fault detection and isolation, and recommended actions. The scheduler autonomously assigns start times to the attached loads based on temporal and power constraints. The scheduler is able to work in a near real time environment for both scheduling and dynamic replanning.

Autonomous power expert system

NASA Technical Reports Server (NTRS)

Ringer, Mark J.; Quinn, Todd M.

1990-01-01

The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control technologies to the Space Station Freedom Electrical Power Systems (SSF/EPS). The objectives of the program are to establish artificial intelligence/expert system technology paths, to create knowledge based tools with advanced human-operator interfaces, and to integrate and interface knowledge-based and conventional control schemes. This program is being developed at the NASA-Lewis. The APS Brassboard represents a subset of a 20 KHz Space Station Power Management And Distribution (PMAD) testbed. A distributed control scheme is used to manage multiple levels of computers and switchgear. The brassboard is comprised of a set of intelligent switchgear used to effectively switch power from the sources to the loads. The Autonomous Power Expert System (APEX) portion of the APS program integrates a knowledge based fault diagnostic system, a power resource scheduler, and an interface to the APS Brassboard. The system includes knowledge bases for system diagnostics, fault detection and isolation, and recommended actions. The scheduler autonomously assigns start times to the attached loads based on temporal and power constraints. The scheduler is able to work in a near real time environment for both scheduling an dynamic replanning.

Assessing the effectiveness of problem-based learning in physical diagnostics education in China: a meta-analysis

PubMed Central

Wang, Jianmiao; Xu, Yongjian; Liu, Xiansheng; Xiong, Weining; Xie, Jungang; Zhao, Jianping

2016-01-01

Problem-based learning (PBL) has been extensively applied as an experimental educational method in Chinese medical schools over the past decade. A meta-analysis was performed to assess the effectiveness of PBL on students’ learning outcomes in physical diagnostics education. Related databases were searched for eligible studies evaluating the effects of PBL compared to traditional teaching on students’ knowledge and/or skill scores of physical diagnostics. Standardized mean difference (SMD) with 95% confidence interval (CI) was estimated. Thirteen studies with a total of 2086 medical students were included in this meta-analysis. All of these studies provided usable data on knowledge scores, and the pooled analysis showed a significant difference in favor of PBL compared to the traditional teaching (SMD = 0.76, 95%CI = 0.33–1.19). Ten studies provided usable data on skill scores, and a significant difference in favor of PBL was also observed (SMD = 1.46, 95%CI = 0.89–2.02). Statistically similar results were obtained in the sensitivity analysis, and there was no significant evidence of publication bias. These results suggested that PBL in physical diagnostics education in China appeared to be more effective than traditional teaching method in improving knowledge and skills. PMID:27808158

Assessing the effectiveness of problem-based learning in physical diagnostics education in China: a meta-analysis.

PubMed

Wang, Jianmiao; Xu, Yongjian; Liu, Xiansheng; Xiong, Weining; Xie, Jungang; Zhao, Jianping

2016-11-03

Problem-based learning (PBL) has been extensively applied as an experimental educational method in Chinese medical schools over the past decade. A meta-analysis was performed to assess the effectiveness of PBL on students' learning outcomes in physical diagnostics education. Related databases were searched for eligible studies evaluating the effects of PBL compared to traditional teaching on students' knowledge and/or skill scores of physical diagnostics. Standardized mean difference (SMD) with 95% confidence interval (CI) was estimated. Thirteen studies with a total of 2086 medical students were included in this meta-analysis. All of these studies provided usable data on knowledge scores, and the pooled analysis showed a significant difference in favor of PBL compared to the traditional teaching (SMD = 0.76, 95%CI = 0.33-1.19). Ten studies provided usable data on skill scores, and a significant difference in favor of PBL was also observed (SMD = 1.46, 95%CI = 0.89-2.02). Statistically similar results were obtained in the sensitivity analysis, and there was no significant evidence of publication bias. These results suggested that PBL in physical diagnostics education in China appeared to be more effective than traditional teaching method in improving knowledge and skills.

Automated extraction of knowledge for model-based diagnostics

NASA Technical Reports Server (NTRS)

Gonzalez, Avelino J.; Myler, Harley R.; Towhidnejad, Massood; Mckenzie, Frederic D.; Kladke, Robin R.

1990-01-01

The concept of accessing computer aided design (CAD) design databases and extracting a process model automatically is investigated as a possible source for the generation of knowledge bases for model-based reasoning systems. The resulting system, referred to as automated knowledge generation (AKG), uses an object-oriented programming structure and constraint techniques as well as internal database of component descriptions to generate a frame-based structure that describes the model. The procedure has been designed to be general enough to be easily coupled to CAD systems that feature a database capable of providing label and connectivity data from the drawn system. The AKG system is capable of defining knowledge bases in formats required by various model-based reasoning tools.

Creating of structure of facts for the knowledge base of an expert system for wind power plant's equipment diagnosis

NASA Astrophysics Data System (ADS)

Duer, Stanisław; Wrzesień, Paweł; Duer, Radosław

2017-10-01

This article describes rules and conditions for making a structure (a set) of facts for an expert knowledge base of the intelligent system to diagnose Wind Power Plants' equipment. Considering particular operational conditions of a technical object, that is a set of Wind Power Plant's equipment, this is a significant issue. A structural model of Wind Power Plant's equipment is developed. Based on that, a functional - diagnostic model of Wind Power Plant's equipment is elaborated. That model is a basis for determining primary elements of the object structure, as well as for interpreting a set of diagnostic signals and their reference signals. The key content of this paper is a description of rules for building of facts on the basis of developed analytical dependence. According to facts, their dependence is described by rules for transferring of a set of pieces of diagnostic information into a specific set of facts. The article consists of four chapters that concern particular issues on the subject.

Photolithography diagnostic expert systems: a systematic approach to problem solving in a wafer fabrication facility

NASA Astrophysics Data System (ADS)

Weatherwax Scott, Caroline; Tsareff, Christopher R.

1990-06-01

One of the main goals of process engineering in the semiconductor industry is to improve wafer fabrication productivity and throughput. Engineers must work continuously toward this goal in addition to performing sustaining and development tasks. To accomplish these objectives, managers must make efficient use of engineering resources. One of the tools being used to improve efficiency is the diagnostic expert system. Expert systems are knowledge based computer programs designed to lead the user through the analysis and solution of a problem. Several photolithography diagnostic expert systems have been implemented at the Hughes Technology Center to provide a systematic approach to process problem solving. This systematic approach was achieved by documenting cause and effect analyses for a wide variety of processing problems. This knowledge was organized in the form of IF-THEN rules, a common structure for knowledge representation in expert system technology. These rules form the knowledge base of the expert system which is stored in the computer. The systems also include the problem solving methodology used by the expert when addressing a problem in his area of expertise. Operators now use the expert systems to solve many process problems without engineering assistance. The systems also facilitate the collection of appropriate data to assist engineering in solving unanticipated problems. Currently, several expert systems have been implemented to cover all aspects of the photolithography process. The systems, which have been in use for over a year, include wafer surface preparation (HMDS), photoresist coat and softbake, align and expose on a wafer stepper, and develop inspection. These systems are part of a plan to implement an expert system diagnostic environment throughout the wafer fabrication facility. In this paper, the systems' construction is described, including knowledge acquisition, rule construction, knowledge refinement, testing, and evaluation. The roles played by the process engineering expert and the knowledge engineer are discussed. The features of the systems are shown, particularly the interactive quality of the consultations and the ease of system use.

Effects of pressure ulcer classification system education programme on knowledge and visual differential diagnostic ability of pressure ulcer classification and incontinence-associated dermatitis for clinical nurses in Korea.

PubMed

Lee, Yun Jin; Kim, Jung Yoon

2016-03-01

The objective of this study was to evaluate the effect of pressure ulcer classification system education on clinical nurses' knowledge and visual differential diagnostic ability of pressure ulcer (PU) classification and incontinence-associated dermatitis (IAD). One group pre and post-test was used. A convenience sample of 407 nurses, participating in PU classification education programme of continuing education, were enrolled. The education programme was composed of a 50-minute lecture on PU classification and case-studies. The PU Classification system and IAD knowledge test (PUCS-KT) and visual differential diagnostic ability tool (VDDAT), consisting of 21 photographs including clinical information were used. Paired t-test was performed using SPSS/WIN 20.0. The overall mean difference of PUCS-KT (t = -11·437, P<0·001) and VDDAT (t = -21·113, P<0·001) was significantly increased after PU classification education. Overall understanding of six PU classification and IAD after education programme was increased, but lacked visual differential diagnostic ability regarding Stage III PU, suspected deep tissue injury (SDTI), and Unstageable. Continuous differentiated education based on clinical practice is needed to improve knowledge and visual differential diagnostic ability for PU classification, and comparison experiment study is required to examine effects of education programmes. © 2016 Medicalhelplines.com Inc and John Wiley & Sons Ltd.

A Fuzzy-Based Prior Knowledge Diagnostic Model with Multiple Attribute Evaluation

ERIC Educational Resources Information Center

Lin, Yi-Chun; Huang, Yueh-Min

2013-01-01

Prior knowledge is a very important part of teaching and learning, as it affects how instructors and students interact with the learning materials. In general, tests are used to assess students' prior knowledge. Nevertheless, conventional testing approaches usually assign only an overall score to each student, and this may mean that students are…

DEB: A Diagnostic Experience Browser using similarity networks

NASA Technical Reports Server (NTRS)

Casadaban, Cyprian E.

1990-01-01

Diagnostic Experience Browser (DEB): a fusion of knowledge base and data base that allows users to examine only the data which is most useful to them is described. The system combines a data base of historical cases of diagnostic trouble-shooting experience with similarity networks. A menu-driven natural language interface receives input about the user's current problem. Similarity networks provide the user with references to past cases that are most similar or most related to those they now face. The user can then choose the case that is most pertinent and browse its full textual description which, in turn, may include references to other related cases.

Design of a diagnostic encyclopaedia using AIDA.

PubMed

van Ginneken, A M; Smeulders, A W; Jansen, W

1987-01-01

Diagnostic Encyclopaedia Workstation (DEW) is the name of a digital encyclopaedia constructed to contain reference knowledge with respect to the pathology of the ovary. Comparing DEW with the common sources of reference knowledge (i.e. books) leads to the following advantages of DEW: it contains more verbal knowledge, pictures and case histories, and it offers information adjusted to the needs of the user. Based on an analysis of the structure of this reference knowledge we have chosen AIDA to develop a relational database and we use a video-disc player to contain the pictorial part of the database. The system consists of a database input version and a read-only run version. The design of the database input version is discussed. Reference knowledge for ovary pathology requires 1-3 Mbytes of memory. At present 15% of this amount is available. The design of the run version is based on an analysis of which information must necessarily be specified to the system by the user to access a desired item of information. Finally, the use of AIDA in constructing DEW is evaluated.

Built-In Diagnostics (BID) Of Equipment/Systems

NASA Technical Reports Server (NTRS)

Granieri, Michael N.; Giordano, John P.; Nolan, Mary E.

1995-01-01

Diagnostician(TM)-on-Chip (DOC) technology identifies faults and commands systems reconfiguration. Smart microcontrollers operating in conjunction with other system-control circuits, command self-correcting system/equipment actions in real time. DOC microcontroller generates commands for associated built-in test equipment to stimulate unit of equipment diagnosed, collects and processes response data obtained by built-in test equipment, and performs diagnostic reasoning on response data, using diagnostic knowledge base derived from design data.

International Expert Consensus Document on Takotsubo Syndrome (Part I): Clinical Characteristics, Diagnostic Criteria, and Pathophysiology.

PubMed

Ghadri, Jelena-Rima; Wittstein, Ilan Shor; Prasad, Abhiram; Sharkey, Scott; Dote, Keigo; Akashi, Yoshihiro John; Cammann, Victoria Lucia; Crea, Filippo; Galiuto, Leonarda; Desmet, Walter; Yoshida, Tetsuro; Manfredini, Roberto; Eitel, Ingo; Kosuge, Masami; Nef, Holger M; Deshmukh, Abhishek; Lerman, Amir; Bossone, Eduardo; Citro, Rodolfo; Ueyama, Takashi; Corrado, Domenico; Kurisu, Satoshi; Ruschitzka, Frank; Winchester, David; Lyon, Alexander R; Omerovic, Elmir; Bax, Jeroen J; Meimoun, Patrick; Tarantini, Guiseppe; Rihal, Charanjit; Y-Hassan, Shams; Migliore, Federico; Horowitz, John D; Shimokawa, Hiroaki; Lüscher, Thomas Felix; Templin, Christian

2018-06-07

Takotsubo syndrome (TTS) is a poorly recognized heart disease that was initially regarded as a benign condition. Recently, it has been shown that TTS may be associated with severe clinical complications including death and that its prevalence is probably underestimated. Since current guidelines on TTS are lacking, it appears timely and important to provide an expert consensus statement on TTS. The clinical expert consensus document part I summarizes the current state of knowledge on clinical presentation and characteristics of TTS and agrees on controversies surrounding TTS such as nomenclature, different TTS types, role of coronary artery disease, and etiology. This consensus also proposes new diagnostic criteria based on current knowledge to improve diagnostic accuracy.

International Expert Consensus Document on Takotsubo Syndrome (Part I): Clinical Characteristics, Diagnostic Criteria, and Pathophysiology

PubMed Central

Ghadri, Jelena-Rima; Wittstein, Ilan Shor; Prasad, Abhiram; Sharkey, Scott; Dote, Keigo; Akashi, Yoshihiro John; Cammann, Victoria Lucia; Crea, Filippo; Galiuto, Leonarda; Desmet, Walter; Yoshida, Tetsuro; Manfredini, Roberto; Eitel, Ingo; Kosuge, Masami; Nef, Holger M; Deshmukh, Abhishek; Lerman, Amir; Bossone, Eduardo; Citro, Rodolfo; Ueyama, Takashi; Corrado, Domenico; Kurisu, Satoshi; Ruschitzka, Frank; Winchester, David; Lyon, Alexander R; Omerovic, Elmir; Bax, Jeroen J; Meimoun, Patrick; Tarantini, Guiseppe; Rihal, Charanjit; Y.-Hassan, Shams; Migliore, Federico; Horowitz, John D; Shimokawa, Hiroaki; Lüscher, Thomas Felix; Templin, Christian

2018-01-01

Abstract Takotsubo syndrome (TTS) is a poorly recognized heart disease that was initially regarded as a benign condition. Recently, it has been shown that TTS may be associated with severe clinical complications including death and that its prevalence is probably underestimated. Since current guidelines on TTS are lacking, it appears timely and important to provide an expert consensus statement on TTS. The clinical expert consensus document part I summarizes the current state of knowledge on clinical presentation and characteristics of TTS and agrees on controversies surrounding TTS such as nomenclature, different TTS types, role of coronary artery disease, and etiology. This consensus also proposes new diagnostic criteria based on current knowledge to improve diagnostic accuracy. PMID:29850871

Optimizing Diagnostic Imaging in the Emergency Department

PubMed Central

Mills, Angela M.; Raja, Ali S.; Marin, Jennifer R.

2015-01-01

While emergency diagnostic imaging use has increased significantly, there is a lack of evidence for corresponding improvements in patient outcomes. Optimizing emergency department (ED) diagnostic imaging has the potential to improve the quality, safety, and outcomes of ED patients, but to date, there have not been any coordinated efforts to further our evidence-based knowledge in this area. The objective of this article is to discuss six aspects of diagnostic imaging in order to provide background information on the underlying framework for the 2015 Academic Emergency Medicine consensus conference, “Diagnostic Imaging in the Emergency Department: A Research Agenda to Optimize Utilization.” The consensus conference aims to generate a high priority research agenda for emergency diagnostic imaging that will inform the design of future investigations. The six components herein will serve as the group topics for the conference: 1) patient-centered outcomes research; 2) clinical decision rules; 3) training, education, and competency; 4) knowledge translation and barriers to image optimization; 5) use of administrative data; and 6) comparative effectiveness research: alternatives to traditional CT use. PMID:25731864

Optimizing diagnostic imaging in the emergency department.

PubMed

Mills, Angela M; Raja, Ali S; Marin, Jennifer R

2015-05-01

While emergency diagnostic imaging use has increased significantly, there is a lack of evidence for corresponding improvements in patient outcomes. Optimizing emergency department (ED) diagnostic imaging has the potential to improve the quality, safety, and outcomes of ED patients, but to date, there have not been any coordinated efforts to further our evidence-based knowledge in this area. The objective of this article is to discuss six aspects of diagnostic imaging to provide background information on the underlying framework for the 2015 Academic Emergency Medicine consensus conference, "Diagnostic Imaging in the Emergency Department: A Research Agenda to Optimize Utilization." The consensus conference aims to generate a high priority research agenda for emergency diagnostic imaging that will inform the design of future investigations. The six components herein will serve as the group topics for the conference: 1) patient-centered outcomes research; 2) clinical decision rules; 3) training, education, and competency; 4) knowledge translation and barriers to image optimization; 5) use of administrative data; and 6) comparative effectiveness research: alternatives to traditional CT use. © 2015 by the Society for Academic Emergency Medicine.

A Pilot Study on Modeling of Diagnostic Criteria Using OWL and SWRL.

PubMed

Hong, Na; Jiang, Guoqian; Pathak, Jyotishiman; Chute, Christopher G

2015-01-01

The objective of this study is to describe our efforts in a pilot study on modeling diagnostic criteria using a Semantic Web-based approach. We reused the basic framework of the ICD-11 content model and refined it into an operational model in the Web Ontology Language (OWL). The refinement is based on a bottom-up analysis method, in which we analyzed data elements (including value sets) in a collection (n=20) of randomly selected diagnostic criteria. We also performed a case study to formalize rule logic in the diagnostic criteria of metabolic syndrome using the Semantic Web Rule Language (SWRL). The results demonstrated that it is feasible to use OWL and SWRL to formalize the diagnostic criteria knowledge, and to execute the rules through reasoning.

Array-based disease diagnostics using lipid/polydiacetylene vesicles encapsulated in a sol-gel matrix.

PubMed

Kolusheva, S; Yossef, R; Kugel, A; Katz, M; Volinsky, R; Welt, M; Hadad, U; Drory, V; Kliger, M; Rubin, E; Porgador, A; Jelinek, R

2012-07-17

We demonstrate a novel array-based diagnostic platform comprising lipid/polydiacetylene (PDA) vesicles embedded within a transparent silica-gel matrix. The diagnostic scheme is based upon the unique chromatic properties of PDA, which undergoes blue-red transformations induced by interactions with amphiphilic or membrane-active analytes. We show that constructing a gel matrix array hosting PDA vesicles with different lipid compositions and applying to blood plasma obtained from healthy individuals and from patients suffering from disease, respectively, allow distinguishing among the disease conditions through application of a simple machine-learning algorithm, using the colorimetric response of the lipid/PDA/gel matrix as the input. Importantly, the new colorimetric diagnostic approach does not require a priori knowledge on the exact metabolite compositions of the blood plasma, since the concept relies only on identifying statistically significant changes in overall disease-induced chromatic response. The chromatic lipid/PDA/gel array-based "fingerprinting" concept is generic, easy to apply, and could be implemented for varied diagnostic and screening applications.

Diagnostic games: from adequate formalization of clinical experience to structure discovery.

PubMed

Shifrin, Michael A; Kasparova, Eva I

2008-01-01

A method of obtaining well-founded and reproducible results in clinical decision making is presented. It is based on "diagnostic games", a procedure of elicitation and formalization of experts' knowledge and experience. The use of this procedure allows formulating decision rules in the terms of an adequate language, that are both unambiguous and clinically clear.

An architecture for the development of real-time fault diagnosis systems using model-based reasoning

NASA Technical Reports Server (NTRS)

Hall, Gardiner A.; Schuetzle, James; Lavallee, David; Gupta, Uday

1992-01-01

Presented here is an architecture for implementing real-time telemetry based diagnostic systems using model-based reasoning. First, we describe Paragon, a knowledge acquisition tool for offline entry and validation of physical system models. Paragon provides domain experts with a structured editing capability to capture the physical component's structure, behavior, and causal relationships. We next describe the architecture of the run time diagnostic system. The diagnostic system, written entirely in Ada, uses the behavioral model developed offline by Paragon to simulate expected component states as reflected in the telemetry stream. The diagnostic algorithm traces causal relationships contained within the model to isolate system faults. Since the diagnostic process relies exclusively on the behavioral model and is implemented without the use of heuristic rules, it can be used to isolate unpredicted faults in a wide variety of systems. Finally, we discuss the implementation of a prototype system constructed using this technique for diagnosing faults in a science instrument. The prototype demonstrates the use of model-based reasoning to develop maintainable systems with greater diagnostic capabilities at a lower cost.

Magnetic resonance imaging in multiple sclerosis--patients' experiences, information interests and responses to an education programme.

PubMed

Brand, Judith; Köpke, Sascha; Kasper, Jürgen; Rahn, Anne; Backhus, Imke; Poettgen, Jana; Stellmann, Jan-Patrick; Siemonsen, Susanne; Heesen, Christoph

2014-01-01

Magnetic resonance imaging (MRI) is a key diagnostic and monitoring tool in multiple sclerosis (MS) management. However, many scientific uncertainties, especially concerning correlates to impairment and prognosis remain. Little is known about MS patients' experiences, knowledge, attitudes, and unmet information needs concerning MRI. We performed qualitative interviews (n = 5) and a survey (n = 104) with MS patients regarding MRI patient information, and basic MRI knowledge. Based on these findings an interactive training program of 2 hours was developed and piloted in n = 26 patients. Interview analyses showed that patients often feel lost in the MRI scanner and left alone with MRI results and images while 90% of patients in the survey expressed a high interest in MRI education. Knowledge on MRI issues was fair with some important knowledge gaps. Major information interests were relevance of lesions as well as the prognostic and diagnostic value of MRI results. The education program was highly appreciated and resulted in a substantial knowledge increase. Patients reported that, based on the program, they felt more competent to engage in encounters with their physicians. This work strongly supports the further development of an evidence-based MRI education program for MS patients to enhance participation in health-care.

A Knowledge-Based System for the Computer Assisted Diagnosis of Endoscopic Images

NASA Astrophysics Data System (ADS)

Kage, Andreas; Münzenmayer, Christian; Wittenberg, Thomas

Due to the actual demographic development the use of Computer-Assisted Diagnosis (CAD) systems becomes a more important part of clinical workflows and clinical decision making. Because changes on the mucosa of the esophagus can indicate the first stage of cancerous developments, there is a large interest to detect and correctly diagnose any such lesion. We present a knowledge-based system which is able to support a physician with the interpretation and diagnosis of endoscopic images of the esophagus. Our system is designed to support the physician directly during the examination of the patient, thus prodving diagnostic assistence at the point of care (POC). Based on an interactively marked region in an endoscopic image of interest, the system provides a diagnostic suggestion, based on an annotated reference image database. Furthermore, using relevant feedback mechanisms, the results can be enhanced interactively.

The INTELSAT VI SSTDMA network diagnostic system

NASA Astrophysics Data System (ADS)

Tamboli, Satish P.; Zhu, Xiaobo; Wilkins, Kim N.; Gupta, Ramesh K.

The system-level design of an expert-system-based, near-real-time diagnostic system for INTELSAT VI satellite-switched time-division multiple access (SSTDMA) network is described. The challenges of INTELSAT VI diagnostics are discussed, along with alternative approaches for network diagnostics and the rationale for choosing a method based on burst unique-word detection. The focal point of the diagnostic system is the diagnostic processor, which resides in the central control and monitoring facility known as the INTELSAT Operations Center TDMA Facility (IOCTF). As real-time information such as burst unique-word detection data, reference terminal status data, and satellite telemetry alarm data are received at the IOCTF, the diagnostic processor continuously monitors the data streams. When a burst status change is detected, a 'snapshot' of the real-time data is forwarded to the expert system. Receipt of the change causes a set of rules to be invoked which associate the traffic pattern with a set of probable causes. A user-friendly interface allows a graphical view of the burst time plan and provides the ability to browse through the knowledge bases.

A prototype knowledge-based simulation support system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hill, T.R.; Roberts, S.D.

1987-04-01

As a preliminary step toward the goal of an intelligent automated system for simulation modeling support, we explore the feasibility of the overall concept by generating and testing a prototypical framework. A prototype knowledge-based computer system was developed to support a senior level course in industrial engineering so that the overall feasibility of an expert simulation support system could be studied in a controlled and observable setting. The system behavior mimics the diagnostic (intelligent) process performed by the course instructor and teaching assistants, finding logical errors in INSIGHT simulation models and recommending appropriate corrective measures. The system was programmed inmore » a non-procedural language (PROLOG) and designed to run interactively with students working on course homework and projects. The knowledge-based structure supports intelligent behavior, providing its users with access to an evolving accumulation of expert diagnostic knowledge. The non-procedural approach facilitates the maintenance of the system and helps merge the roles of expert and knowledge engineer by allowing new knowledge to be easily incorporated without regard to the existing flow of control. The background, features and design of the system are describe and preliminary results are reported. Initial success is judged to demonstrate the utility of the reported approach and support the ultimate goal of an intelligent modeling system which can support simulation modelers outside the classroom environment. Finally, future extensions are suggested.« less

Diagnostic reasoning by hospital pharmacists: assessment of attitudes, knowledge, and skills.

PubMed

Chernushkin, Kseniya; Loewen, Peter; de Lemos, Jane; Aulakh, Amneet; Jung, Joanne; Dahri, Karen

2012-07-01

Hospital pharmacists participate in activities that may be considered diagnostic. Two reasoning approaches to diagnosis have been described: non-analytic and analytic. Of the 6 analytic traditions, the probabilistic tradition has been shown to improve diagnostic accuracy and reduce unnecessary testing. To the authors' knowledge, pharmacists' attitudes toward having a diagnostic role and their diagnostic knowledge and skills have never been studied. To describe pharmacists' attitudes toward the role of diagnosis in pharmacotherapeutic problem-solving and to characterize the extent of pharmacists' knowledge and skills related to diagnostic literacy. Pharmacists working within Lower Mainland Pharmacy Services (British Columbia) who spent at least 33% of their time in direct patient care were invited to participate in a prospective observational survey. The survey sought information about demographic characteristics and attitudes toward diagnosis. Diagnostic knowledge and skills were tested by means of 3 case scenarios. The analysis included simple descriptive statistics and inferential statistics to evaluate relationships between responses and experience and training. Of 266 pharmacists invited to participate, 94 responded. The attitudes section of the survey was completed by 90 pharmacists; of these, 80 (89%) agreed with the definition of "diagnosis" proposed in the survey, and 83 (92%) agreed that it is important for pharmacists to have diagnosis-related skills. Respondents preferred an analytic to a non-analytic approach to diagnostic decision-making. The probabilistic tradition was not the preferred method in any of the 3 cases. In evaluating 5 clinical scenarios that might require diagnostic skills, on average 84% of respondents agreed that they should be involved in assessing such problems. Respondents' knowledge of and ability to apply probabilistic diagnostic tools were highest for test sensitivity (average of 61% of respondents with the correct answers) and lower for test specificity (average of 48% with correct answers) and likelihood ratios (average of 39% with correct answers). Respondents to this survey strongly believed that diagnostic skills were important for solving drug-related problems, but they demonstrated low levels of knowledge and ability to apply concepts of probabilistic diagnostic reasoning. Opportunities to expand pharmacists' knowledge of diagnostic reasoning exist, and the findings reported here indicate that pharmacists would consider such professional development valuable.

Assessing an AI knowledge-base for asymptomatic liver diseases.

PubMed

Babic, A; Mathiesen, U; Hedin, K; Bodemar, G; Wigertz, O

1998-01-01

Discovering not yet seen knowledge from clinical data is of importance in the field of asymptomatic liver diseases. Avoidance of liver biopsy which is used as the ultimate confirmation of diagnosis by making the decision based on relevant laboratory findings only, would be considered an essential support. The system based on Quinlan's ID3 algorithm was simple and efficient in extracting the sought knowledge. Basic principles of applying the AI systems are therefore described and complemented with medical evaluation. Some of the diagnostic rules were found to be useful as decision algorithms i.e. they could be directly applied in clinical work and made a part of the knowledge-base of the Liver Guide, an automated decision support system.

A Degree Is Not Enough: A Quantitative Study of Aspects of Pre-Service Science Teachers' Chemistry Content Knowledge

ERIC Educational Resources Information Center

Kind, Vanessa

2014-01-01

Aspects of chemistry content knowledge held by 265 UK-based pre-service teachers (PSTs) were probed using 28 diagnostic questions in five chemistry concept areas, "Particle theory and changes of state", "Mass conservation" (taught to 11-14-year-olds), and "Chemical bonding", "Mole calculations" and…

GENOSENSE Diagnostics GmbH.

PubMed

Schneeberger, Christian

2004-07-01

GENOSENSE Diagnostics GmbH, a company specialized in preventive genetic diagnostics, has committed itself to applying molecular medical knowledge to realizing the vision of individual, preventive and patient-tailored medicine. GENOSENSE offers a unique line of preventive genomic diagnostic profiles. Each profile focuses on a carefully selected set of polymorphisms associated with particular diseases or physiologic imbalances. GENOSENSE does not only provide the genetic test results, but highly capable medical experts 'translate' the results into a clinical language and assist the customer with established support regarding their medical interpretation. In addition, the company provides academic institutions and pharmaceutical companies with turnkey solutions for research-based projects.

Software For Fault-Tree Diagnosis Of A System

NASA Technical Reports Server (NTRS)

Iverson, Dave; Patterson-Hine, Ann; Liao, Jack

1993-01-01

Fault Tree Diagnosis System (FTDS) computer program is automated-diagnostic-system program identifying likely causes of specified failure on basis of information represented in system-reliability mathematical models known as fault trees. Is modified implementation of failure-cause-identification phase of Narayanan's and Viswanadham's methodology for acquisition of knowledge and reasoning in analyzing failures of systems. Knowledge base of if/then rules replaced with object-oriented fault-tree representation. Enhancement yields more-efficient identification of causes of failures and enables dynamic updating of knowledge base. Written in C language, C++, and Common LISP.

Knowledge regarding Ebola Hemorrhagic Fever among private dental practitioners in Tricity, India: A cross-sectional questionnaire study.

PubMed

Gupta, Nidhi; Mehta, Nishant; Gupta, Preety; Arora, Vikram; Setia, Priyanka

2015-01-01

Ebola viral fever, a highly contagious haemorrhagic disease has today become a major public health concern in the developing countries worldwide. The purpose of this study was to assess knowledge among dental practitioners regarding Ebola Haemorrhagic Fever (Ebola HF) in Tricity, (Chandigarh, Panchkula and Mohali). A total of 500 private dental practitioners were randomly approached to participate in this cross-sectional survey. A self-structured, closed ended questionnaire was administered to each participant to record demographic and professional characteristics followed by their knowledge regarding Ebola HF. Knowledge section included questions related to communicability; symptomatology and diagnostics; at-risk individuals; prevention and treatment; and, virus characteristics of Ebola HF. The results were expressed in percentages. Multivariable linear regression analysis was carried out to assess the association of participants's demographic and professional characteristics with the knowledge scores. Statistically significant difference was seen when mean knowledge scores were compared based on the locality and qualification of the participants (P < 0.05). Dental practitioners from urban areas with higher qualification had better knowledge yet there were notable deficiencies regarding the virus characteristics, diagnostics, elimination and treatment.

Chronobiology of epilepsy: diagnostic and therapeutic implications of chrono-epileptology.

PubMed

Loddenkemper, Tobias; Lockley, Steven W; Kaleyias, Joseph; Kothare, Sanjeev V

2011-04-01

The combination of chronobiology and epilepsy offers novel diagnostic and therapeutic management options. Knowledge of the interactions between circadian periodicity, entrainment, sleep patterns, and epilepsy may provide additional diagnostic options beyond sleep deprivation and extended release medication formulations. It may also provide novel insights into the physiologic, biochemical, and genetic regulation processes of epilepsy and the circadian clock, rendering new treatment options. Temporal fluctuations of seizure susceptibility based on sleep homeostasis and circadian phase in selected epilepsies may provide predictability based on mathematical models. Chrono-epileptology offers opportunities for individualized patient-oriented treatment paradigms based on chrono-pharmacology, differential medication dosing, chrono-drug delivery systems, and utilization of "zeitgebers" such as chronobiotics or light-therapy and desynchronization strategies among others.

American Pancreatic Association Practice Guidelines in Chronic Pancreatitis: evidence-based report on diagnostic guidelines.

PubMed

Conwell, Darwin L; Lee, Linda S; Yadav, Dhiraj; Longnecker, Daniel S; Miller, Frank H; Mortele, Koenraad J; Levy, Michael J; Kwon, Richard; Lieb, John G; Stevens, Tyler; Toskes, Phillip P; Gardner, Timothy B; Gelrud, Andres; Wu, Bechien U; Forsmark, Christopher E; Vege, Santhi S

2014-11-01

The diagnosis of chronic pancreatitis remains challenging in early stages of the disease. This report defines the diagnostic criteria useful in the assessment of patients with suspected and established chronic pancreatitis. All current diagnostic procedures are reviewed, and evidence-based statements are provided about their utility and limitations. Diagnostic criteria for chronic pancreatitis are classified as definitive, probable, or insufficient evidence. A diagnostic (STEP-wise; survey, tomography, endoscopy, and pancreas function testing) algorithm is proposed that proceeds from a noninvasive to a more invasive approach. This algorithm maximizes specificity (low false-positive rate) in subjects with chronic abdominal pain and equivocal imaging changes. Furthermore, a nomenclature is suggested to further characterize patients with established chronic pancreatitis based on TIGAR-O (toxic, idiopathic, genetic, autoimmune, recurrent, and obstructive) etiology, gland morphology (Cambridge criteria), and physiologic state (exocrine, endocrine function) for uniformity across future multicenter research collaborations. This guideline will serve as a baseline manuscript that will be modified as new evidence becomes available and our knowledge of chronic pancreatitis improves.

Distributed Knowledge Base Systems for Diagnosis and Information Retrieval.

DTIC Science & Technology

1985-09-01

thinks of the idiagnostic task, while it may be generic in the sense that the task may be quite similar across domains, it is not a unitary task...solving in our approach,’, outgrowth of ou group’s experience with MDX, a meaning that a special kind of organization and Q medical diagnostic program...5.4. Determining the Findings of a Knowledge U). It is important that the meaning of the Group knowledge group’s result be clear. In this knowledge

A report on the Academic Emergency Medicine 2015 consensus conference "Diagnostic imaging in the emergency department: a research agenda to optimize utilization".

PubMed

Gunn, Martin L; Marin, Jennifer R; Mills, Angela M; Chong, Suzanne T; Froemming, Adam T; Johnson, Jamlik O; Kumaravel, Manickam; Sodickson, Aaron D

2016-08-01

In May 2015, the Academic Emergency Medicine consensus conference "Diagnostic imaging in the emergency department: a research agenda to optimize utilization" was held. The goal of the conference was to develop a high-priority research agenda regarding emergency diagnostic imaging on which to base future research. In addition to representatives from the Society of Academic Emergency Medicine, the multidisciplinary conference included members of several radiology organizations: American Society for Emergency Radiology, Radiological Society of North America, the American College of Radiology, and the American Association of Physicists in Medicine. The specific aims of the conference were to (1) understand the current state of evidence regarding emergency department (ED) diagnostic imaging utilization and identify key opportunities, limitations, and gaps in knowledge; (2) develop a consensus-driven research agenda emphasizing priorities and opportunities for research in ED diagnostic imaging; and (3) explore specific funding mechanisms available to facilitate research in ED diagnostic imaging. Through a multistep consensus process, participants developed targeted research questions for future research in six content areas within emergency diagnostic imaging: clinical decision rules; use of administrative data; patient-centered outcomes research; training, education, and competency; knowledge translation and barriers to imaging optimization; and comparative effectiveness research in alternatives to traditional computed tomography use.

Graph-based real-time fault diagnostics

NASA Technical Reports Server (NTRS)

Padalkar, S.; Karsai, G.; Sztipanovits, J.

1988-01-01

A real-time fault detection and diagnosis capability is absolutely crucial in the design of large-scale space systems. Some of the existing AI-based fault diagnostic techniques like expert systems and qualitative modelling are frequently ill-suited for this purpose. Expert systems are often inadequately structured, difficult to validate and suffer from knowledge acquisition bottlenecks. Qualitative modelling techniques sometimes generate a large number of failure source alternatives, thus hampering speedy diagnosis. In this paper we present a graph-based technique which is well suited for real-time fault diagnosis, structured knowledge representation and acquisition and testing and validation. A Hierarchical Fault Model of the system to be diagnosed is developed. At each level of hierarchy, there exist fault propagation digraphs denoting causal relations between failure modes of subsystems. The edges of such a digraph are weighted with fault propagation time intervals. Efficient and restartable graph algorithms are used for on-line speedy identification of failure source components.

Methodology for automating software systems

NASA Technical Reports Server (NTRS)

Moseley, Warren

1990-01-01

Applying ITS technology to the shuttle diagnostics would not require the rigor of the Petri Net representation, however it is important in providing the animated simulated portion of the interface and the demands placed on the system to support the training aspects to have a homogeneous and consistent underlying knowledge representation. By keeping the diagnostic rule base, the hardware description, the software description, user profiles, desired behavioral knowledge, and the user interface in the same notation, it is possible to reason about the all of the properties of petri nets, on any selected portion of the simulation. This reasoning provides foundation for utilization of intelligent tutoring systems technology.

A Testbed for Data Fusion for Engine Diagnostics and Prognostics1

DTIC Science & Technology

2002-03-01

detected ; too late to be useful for prognostics development. Table 1. Table of acronyms ACRONYM MEANING AD Anomaly detector...strictly defined points. Determining where we are on the engine health curve is the first step in prognostics . Fault detection / diagnostic reasoning... Detection As described above the ability of the monitoring system to detect an anomaly is especially important for knowledge-based systems, i.e.,

The diversity effect in diagnostic reasoning.

PubMed

Rebitschek, Felix G; Krems, Josef F; Jahn, Georg

2016-07-01

Diagnostic reasoning draws on knowledge about effects and their potential causes. The causal-diversity effect in diagnostic reasoning normatively depends on the distribution of effects in causal structures, and thus, a psychological diversity effect could indicate whether causally structured knowledge is used in evaluating the probability of a diagnosis, if the effect were to covary with manipulations of causal structures. In four experiments, participants dealt with a quasi-medical scenario presenting symptom sets (effects) that consistently suggested a specified diagnosis (cause). The probability that the diagnosis was correct had to be rated for two opposed symptom sets that differed with regard to the symptoms' positions (proximal or diverse) in the causal structure that was initially acquired. The causal structure linking the diagnosis to the symptoms and the base rate of the diagnosis were manipulated to explore whether the diagnosis was rated as more probable for diverse than for proximal symptoms when alternative causations were more plausible (e.g., because of a lower base rate of the diagnosis in question). The results replicated the causal diversity effect in diagnostic reasoning across these conditions, but no consistent effects of structure and base rate variations were observed. Diversity effects computed in causal Bayesian networks are presented, illustrating the consequences of the structure manipulations and corroborating that a diversity effect across the different experimental manipulations is normatively justified. The observed diversity effects presumably resulted from shortcut reasoning about the possibilities of alternative causation.

The biomedical disciplines and the structure of biomedical and clinical knowledge.

PubMed

Nederbragt, H

2000-11-01

The relation between biomedical knowledge and clinical knowledge is discussed by comparing their respective structures. The knowledge of a disease as a biological phenomenon is constructed by the interaction of facts and theories from the main biomedical disciplines: epidemiology, diagnostics, clinical trial, therapy development and pathogenesis. Although these facts and theories are based on probabilities and extrapolations, the interaction provides a reliable and coherent structure, comparable to a Kuhnian paradigma. In the structure of clinical knowledge, i.e. knowledge of the patient with the disease, not only biomedical knowledge contributes to the structure but also economic and social relations, ethics and personal experience. However, the interaction between each of the participating "knowledges" in clinical knowledge is not based on mutual dependency and accumulation of different arguments from each, as in biomedical knowledge, but on competition and partial exclusion. Therefore, the structure of biomedical knowledge is different from that of clinical knowledge. This difference is used as the basis for a discussion in which the place of technology, evidence-based medicine and the gap between scientific and clinical knowledge are evaluated.

Tacit knowledge and visual expertise in medical diagnostic reasoning: implications for medical education.

PubMed

Heiberg Engel, Peter Johan

2008-01-01

Much education--especially at the university level--has been criticized for having primarily dealt with explicit knowledge, i.e. those aspects of mental activities, which are verbal and conscious. Furthermore, research in medical diagnostic reasoning has been criticized for having focused on the specialty of intern medicine, while specialties with other skills, i.e. perceptive skills within pathology and radiology, have been ignored. To show that the concept of tacit knowledge is important in medical education-at all levels and in medical diagnostic reasoning. Describing how tacit knowledge according to Michael Polany, is experienced and expressed in day-to-day life, it is shown that there is a tacit dimension to all knowledge. Reviewing recent literature on medical diagnostic reasoning, it is shown that tacit knowledge is recognized in connection with concepts such as "non-analytical reasoning" and "dual process of reasoning." It is important that educators are trained in how explicit and implicit knowledge is attained and that tacit knowledge is included in educational programmes of all medical specialties.

Development of an intelligent diagnostic system for reusable rocket engine control

NASA Technical Reports Server (NTRS)

Anex, R. P.; Russell, J. R.; Guo, T.-H.

1991-01-01

A description of an intelligent diagnostic system for the Space Shuttle Main Engines (SSME) is presented. This system is suitable for incorporation in an intelligent controller which implements accommodating closed-loop control to extend engine life and maximize available performance. The diagnostic system architecture is a modular, hierarchical, blackboard system which is particularly well suited for real-time implementation of a system which must be repeatedly updated and extended. The diagnostic problem is formulated as a hierarchical classification problem in which the failure hypotheses are represented in terms of predefined data patterns. The diagnostic expert system incorporates techniques for priority-based diagnostics, the combination of analytical and heuristic knowledge for diagnosis, integration of different AI systems, and the implementation of hierarchical distributed systems. A prototype reusable rocket engine diagnostic system (ReREDS) has been implemented. The prototype user interface and diagnostic performance using SSME test data are described.

Application of content-based image compression to telepathology

NASA Astrophysics Data System (ADS)

Varga, Margaret J.; Ducksbury, Paul G.; Callagy, Grace

2002-05-01

Telepathology is a means of practicing pathology at a distance, viewing images on a computer display rather than directly through a microscope. Without compression, images take too long to transmit to a remote location and are very expensive to store for future examination. However, to date the use of compressed images in pathology remains controversial. This is because commercial image compression algorithms such as JPEG achieve data compression without knowledge of the diagnostic content. Often images are lossily compressed at the expense of corrupting informative content. None of the currently available lossy compression techniques are concerned with what information has been preserved and what data has been discarded. Their sole objective is to compress and transmit the images as fast as possible. By contrast, this paper presents a novel image compression technique, which exploits knowledge of the slide diagnostic content. This 'content based' approach combines visually lossless and lossy compression techniques, judiciously applying each in the appropriate context across an image so as to maintain 'diagnostic' information while still maximising the possible compression. Standard compression algorithms, e.g. wavelets, can still be used, but their use in a context sensitive manner can offer high compression ratios and preservation of diagnostically important information. When compared with lossless compression the novel content-based approach can potentially provide the same degree of information with a smaller amount of data. When compared with lossy compression it can provide more information for a given amount of compression. The precise gain in the compression performance depends on the application (e.g. database archive or second opinion consultation) and the diagnostic content of the images.

Diagnostic and Therapeutic Knowledge and Practices in the Management of Congenital Syphilis by Pediatricians in Public Maternity Hospitals in Brazil.

PubMed

Dos Santos, Raquel Rodrigues; Niquini, Roberta Pereira; Bastos, Francisco Inácio; Domingues, Rosa Maria Soares Madeira

2017-01-01

The study aimed to assess conformity with Brazil's standard protocol for diagnostic and therapeutic practices in the management of congenital syphilis by pediatricians in public maternity hospitals. A cross-sectional study was conducted in 2015 with 41 pediatricians working in all the public maternity hospitals in Teresina, the capital of Piauí State, Northeast Brazil, through self-completed questionnaires. The study assessed the conformity of knowledge and practices according to the Brazilian Ministry of Health protocols. The study has made evident low access to training courses (54%) and insufficient knowledge of the case definition of congenital syphilis (42%) and rapid tests for syphilis (39%). Flaws were observed in the diagnostic workup and treatment of newborns. Requesting VDRL (88%) and correct treatment of neurosyphilis (88%) were the practices that showed the highest conformity with standard protocols. Low conformity with protocols leads to missed opportunities for identifying and adequately treating congenital syphilis. Based on the barriers identified in the study, better access to diagnostic and treatment protocols, improved recording on prenatal cards and hospital patient charts, availability of tests and medicines, and educational work with pregnant women should be urgently implemented, aiming to reverse the currently inadequate management of congenital syphilis and to curb its spread.

The role of strategy and redundancy in diagnostic reasoning.

PubMed

Bloch, Ralph F; Hofer, Daniel; Feller, Sabine; Hodel, Maria

2003-01-24

Diagnostic reasoning is a key competence of physicians. We explored the effects of knowledge, practice and additional clinical information on strategy, redundancy and accuracy of diagnosing a peripheral neurological defect in the hand based on sensory examination. Using an interactive computer simulation that includes 21 unique cases with seven sensory loss patterns and either concordant, neutral or discordant textual information, 21 3rd year medical students, 21 6th year and 21 senior neurology residents each examined 15 cases over the course of one session. An additional 23 psychology students examined 24 cases over two sessions, 12 cases per session. Subjects also took a seven-item MCQ exam of seven classical patterns presented visually. Knowledge of sensory patterns and diagnostic accuracy are highly correlated within groups (R2 = 0.64). The total amount of information gathered for incorrect diagnoses is no lower than that for correct diagnoses. Residents require significantly fewer tests than either psychology or 6th year students, who in turn require fewer than the 3rd year students (p < 0.001). The diagnostic accuracy of subjects is affected both by level of training (p < 0.001) and concordance of clinical information (p < 0.001). For discordant cases, refutation testing occurs significantly in 6th year students (p < 0.001) and residents (p < 0.01), but not in psychology or 3rd year students. Conversely, there is a stable 55% excess of confirmatory testing, independent of training or concordance. Knowledge and practice are both important for diagnostic success. For complex diagnostic situations reasoning components employing redundancy seem more essential than those using strategy.

Linking medical records to an expert system

NASA Technical Reports Server (NTRS)

Naeymi-Rad, Frank; Trace, David; Desouzaalmeida, Fabio

1991-01-01

This presentation will be done using the IMR-Entry (Intelligent Medical Record Entry) system. IMR-Entry is a software program developed as a front-end to our diagnostic consultant software MEDAS (Medical Emergency Decision Assistance System). MEDAS (the Medical Emergency Diagnostic Assistance System) is a diagnostic consultant system using a multimembership Bayesian design for its inference engine and relational database technology for its knowledge base maintenance. Research on MEDAS began at the University of Southern California and the Institute of Critical Care in the mid 1970's with support from NASA and NSF. The MEDAS project moved to Chicago in 1982; its current progress is due to collaboration between Illinois Institute of Technology, The Chicago Medical School, Lake Forest College and NASA at KSC. Since the purpose of an expert system is to derive a hypothesis, its communication vocabulary is limited to features used by its knowledge base. The development of a comprehensive problem based medical record entry system which could handshake with an expert system while creating an electronic medical record at the same time was studied. IMR-E is a computer based patient record that serves as a front end to the expert system MEDAS. IMR-E is a graphically oriented comprehensive medical record. The programs major components are demonstrated.

Proposal of diagnostic process model for computer based diagnosis.

PubMed

Matsumura, Yasushi; Takeda, Toshihiro; Manabe, Shiro; Saito, Hirokazu; Teramoto, Kei; Kuwata, Shigeki; Mihara, Naoki

2012-01-01

We aim at making a diagnosis support system that can be put to practical use. We proposed a diagnostic process model based on simple knowledge which can be gleaned from textbooks. We defined clinical finding (CF) as a general concept for patient's symptom or findings etc., whose value is expressed by Boolean. We call the combination of several CFs a "CF pattern", and a set of CF patterns with concomitant diseases "case base". We consider diagnosis as a process of searching an instance from the case base whose CF pattern is concomitant with that of a patient. The diseases which have the same CF pattern are candidates for diagnosis. Then we select a CF which is present in part of the candidates and check whether it is present or absent in the patient in order to narrow down the candidates. Because the case base does not exist in reality, the probability of CF pattern is calculated by the product of CF occurrence rate assuming that occurrence of CF is independent. Therefore the knowledge required for diagnosis is frequency of disease under sex and age group and CF-disease relation (CF and its occurrence rate in the disease). By processing these two types of knowledge, diagnosis can be made.

From spoken narratives to domain knowledge: mining linguistic data for medical image understanding.

PubMed

Guo, Xuan; Yu, Qi; Alm, Cecilia Ovesdotter; Calvelli, Cara; Pelz, Jeff B; Shi, Pengcheng; Haake, Anne R

2014-10-01

Extracting useful visual clues from medical images allowing accurate diagnoses requires physicians' domain knowledge acquired through years of systematic study and clinical training. This is especially true in the dermatology domain, a medical specialty that requires physicians to have image inspection experience. Automating or at least aiding such efforts requires understanding physicians' reasoning processes and their use of domain knowledge. Mining physicians' references to medical concepts in narratives during image-based diagnosis of a disease is an interesting research topic that can help reveal experts' reasoning processes. It can also be a useful resource to assist with design of information technologies for image use and for image case-based medical education systems. We collected data for analyzing physicians' diagnostic reasoning processes by conducting an experiment that recorded their spoken descriptions during inspection of dermatology images. In this paper we focus on the benefit of physicians' spoken descriptions and provide a general workflow for mining medical domain knowledge based on linguistic data from these narratives. The challenge of a medical image case can influence the accuracy of the diagnosis as well as how physicians pursue the diagnostic process. Accordingly, we define two lexical metrics for physicians' narratives--lexical consensus score and top N relatedness score--and evaluate their usefulness by assessing the diagnostic challenge levels of corresponding medical images. We also report on clustering medical images based on anchor concepts obtained from physicians' medical term usage. These analyses are based on physicians' spoken narratives that have been preprocessed by incorporating the Unified Medical Language System for detecting medical concepts. The image rankings based on lexical consensus score and on top 1 relatedness score are well correlated with those based on challenge levels (Spearman correlation>0.5 and Kendall correlation>0.4). Clustering results are largely improved based on our anchor concept method (accuracy>70% and mutual information>80%). Physicians' spoken narratives are valuable for the purpose of mining the domain knowledge that physicians use in medical image inspections. We also show that the semantic metrics introduced in the paper can be successfully applied to medical image understanding and allow discussion of additional uses of these metrics. Copyright © 2014 Elsevier B.V. All rights reserved.

Evaluation of an Intelligent Tutoring System in Pathology: Effects of External Representation on Performance Gains, Metacognition, and Acceptance

PubMed Central

Crowley, Rebecca S.; Legowski, Elizabeth; Medvedeva, Olga; Tseytlin, Eugene; Roh, Ellen; Jukic, Drazen

2007-01-01

Objective Determine effects of computer-based tutoring on diagnostic performance gains, meta-cognition, and acceptance using two different problem representations. Describe impact of tutoring on spectrum of diagnostic skills required for task performance. Identify key features of student-tutor interaction contributing to learning gains. Design Prospective, between-subjects study, controlled for participant level of training. Resident physicians in two academic pathology programs spent four hours using one of two interfaces which differed mainly in external problem representation. The case-focused representation provided an open-learning environment in which students were free to explore evidence-hypothesis relationships within a case, but could not visualize the entire diagnostic space. The knowledge-focused representation provided an interactive representation of the entire diagnostic space, which more tightly constrained student actions. Measurements Metrics included results of pretest, post-test and retention-test for multiple choice and case diagnosis tests, ratios of performance to student reported certainty, results of participant survey, learning curves, and interaction behaviors during tutoring. Results Students had highly significant learning gains after one tutoring session. Learning was retained at one week. There were no differences between the two interfaces in learning gains on post-test or retention test. Only students in the knowledge-focused interface exhibited significant metacognitive gains from pretest to post-test and pretest to retention test. Students rated the knowledge-focused interface significantly higher than the case-focused interface. Conclusions Cognitive tutoring is associated with improved diagnostic performance in a complex medical domain. The effect is retained at one-week post-training. Knowledge-focused external problem representation shows an advantage over case-focused representation for metacognitive effects and user acceptance. PMID:17213494

Evaluation of an intelligent tutoring system in pathology: effects of external representation on performance gains, metacognition, and acceptance.

PubMed

Crowley, Rebecca S; Legowski, Elizabeth; Medvedeva, Olga; Tseytlin, Eugene; Roh, Ellen; Jukic, Drazen

2007-01-01

Determine effects of computer-based tutoring on diagnostic performance gains, meta-cognition, and acceptance using two different problem representations. Describe impact of tutoring on spectrum of diagnostic skills required for task performance. Identify key features of student-tutor interaction contributing to learning gains. Prospective, between-subjects study, controlled for participant level of training. Resident physicians in two academic pathology programs spent four hours using one of two interfaces which differed mainly in external problem representation. The case-focused representation provided an open-learning environment in which students were free to explore evidence-hypothesis relationships within a case, but could not visualize the entire diagnostic space. The knowledge-focused representation provided an interactive representation of the entire diagnostic space, which more tightly constrained student actions. Metrics included results of pretest, post-test and retention-test for multiple choice and case diagnosis tests, ratios of performance to student reported certainty, results of participant survey, learning curves, and interaction behaviors during tutoring. Students had highly significant learning gains after one tutoring session. Learning was retained at one week. There were no differences between the two interfaces in learning gains on post-test or retention test. Only students in the knowledge-focused interface exhibited significant metacognitive gains from pretest to post-test and pretest to retention test. Students rated the knowledge-focused interface significantly higher than the case-focused interface. Cognitive tutoring is associated with improved diagnostic performance in a complex medical domain. The effect is retained at one-week post-training. Knowledge-focused external problem representation shows an advantage over case-focused representation for metacognitive effects and user acceptance.

Oral Cancer Knowledge and Diagnostic Ability Among Dental Students.

PubMed

Hassona, Y; Scully, C; Abu Tarboush, N; Baqain, Z; Ismail, F; Hawamdeh, S; Sawair, F

2017-09-01

The purpose of this study is to examine factors that influence the diagnostic ability of dental students with regards to oral cancer and oral potentially malignant disorders. Dental students at different levels of study were directly interviewed to examine their oral cancer knowledge and diagnostic ability using a validated and pre-tested survey instrument containing validated clinical images of oral cancer and oral potentially malignant disorders. An oral cancer knowledge scale (0 to 31) was generated from correct responses on oral cancer general knowledge, and a diagnostic ability scale (0 to 100) was generated from correct selections of suspicious oral lesions. Knowledge scores ranged from 0 to 27 (mean 10.1 ± 6.0); mean knowledge scores increased with year of study; 5th year students had the highest mean knowledge score (19.1 ± 4.0), while 1st year students had the lowest (5.6 ± 3.5). Diagnostic ability scores increased with year of study and ranged from 0 to 88.5 % (mean 41.8 % ± 15.6). The ability to recognize suspicious oral lesions was significantly correlated with knowledge about oral cancer and oral potentially malignant disorders (r = 0.28; P < 0.001). There is a need to improve oral cancer education curricula; increasing students' contact with patients who have oral lesions including oral cancer will help to improve their future diagnostic ability and early detection practices.

An expert system for diagnostics and estimation of steam turbine components condition

NASA Astrophysics Data System (ADS)

Murmansky, B. E.; Aronson, K. E.; Brodov, Yu. M.

2017-11-01

The report describes an expert system of probability type for diagnostics and state estimation of steam turbine technological subsystems components. The expert system is based on Bayes’ theorem and permits to troubleshoot the equipment components, using expert experience, when there is a lack of baseline information on the indicators of turbine operation. Within a unified approach the expert system solves the problems of diagnosing the flow steam path of the turbine, bearings, thermal expansion system, regulatory system, condensing unit, the systems of regenerative feed-water and hot water heating. The knowledge base of the expert system for turbine unit rotors and bearings contains a description of 34 defects and of 104 related diagnostic features that cause a change in its vibration state. The knowledge base for the condensing unit contains 12 hypotheses and 15 evidence (indications); the procedures are also designated for 20 state parameters estimation. Similar knowledge base containing the diagnostic features and faults hypotheses are formulated for other technological subsystems of turbine unit. With the necessary initial information available a number of problems can be solved within the expert system for various technological subsystems of steam turbine unit: for steam flow path it is the correlation and regression analysis of multifactor relationship between the vibration parameters variations and the regime parameters; for system of thermal expansions it is the evaluation of force acting on the longitudinal keys depending on the temperature state of the turbine cylinder; for condensing unit it is the evaluation of separate effect of the heat exchange surface contamination and of the presence of air in condenser steam space on condenser thermal efficiency performance, as well as the evaluation of term for condenser cleaning and for tube system replacement and so forth. With a lack of initial information the expert system enables to formulate a diagnosis, calculating the probability of faults hypotheses, given the degree of the expert confidence in estimation of turbine components operation parameters.

A systems engineering approach to automated failure cause diagnosis in space power systems

NASA Technical Reports Server (NTRS)

Dolce, James L.; Faymon, Karl A.

1987-01-01

Automatic failure-cause diagnosis is a key element in autonomous operation of space power systems such as Space Station's. A rule-based diagnostic system has been developed for determining the cause of degraded performance. The knowledge required for such diagnosis is elicited from the system engineering process by using traditional failure analysis techniques. Symptoms, failures, causes, and detector information are represented with structured data; and diagnostic procedural knowledge is represented with rules. Detected symptoms instantiate failure modes and possible causes consistent with currently held beliefs about the likelihood of the cause. A diagnosis concludes with an explanation of the observed symptoms in terms of a chain of possible causes and subcauses.

Knowledge-based and integrated monitoring and diagnosis in autonomous power systems

NASA Technical Reports Server (NTRS)

Momoh, J. A.; Zhang, Z. Z.

1990-01-01

A new technique of knowledge-based and integrated monitoring and diagnosis (KBIMD) to deal with abnormalities and incipient or potential failures in autonomous power systems is presented. The KBIMD conception is discussed as a new function of autonomous power system automation. Available diagnostic modelling, system structure, principles and strategies are suggested. In order to verify the feasibility of the KBIMD, a preliminary prototype expert system is designed to simulate the KBIMD function in a main electric network of the autonomous power system.

Expert systems and simulation models; Proceedings of the Seminar, Tucson, AZ, November 18, 19, 1985

NASA Technical Reports Server (NTRS)

1986-01-01

The seminar presents papers on modeling and simulation methodology, artificial intelligence and expert systems, environments for simulation/expert system development, and methodology for simulation/expert system development. Particular attention is given to simulation modeling concepts and their representation, modular hierarchical model specification, knowledge representation, and rule-based diagnostic expert system development. Other topics include the combination of symbolic and discrete event simulation, real time inferencing, and the management of large knowledge-based simulation projects.

American Pancreatic Association Practice Guidelines in Chronic Pancreatitis: Evidence-Based Report on Diagnostic Guidelines

PubMed Central

Conwell, Darwin L.; Lee, Linda S.; Yadav, Dhiraj; Longnecker, Daniel S.; Miller, Frank H.; Mortele, Koenraad J.; Levy, Michael J.; Kwon, Richard; Lieb, John G.; Stevens, Tyler; Toskes, Philip P.; Gardner, Timothy B.; Gelrud, Andres; Wu, Bechien U.; Forsmark, Christopher E.; Vege, Santhi S.

2016-01-01

The diagnosis of chronic pancreatitis remains challenging in early stages of the disease. This report defines the diagnostic criteria useful in the assessment of patients with suspected and established chronic pancreatitis. All current diagnostic procedures are reviewed and evidence based statements are provided about their utility and limitations. Diagnostic criteria for chronic pancreatitis are classified as definitive, probable or insufficient evidence. A diagnostic (STEP-wise; S-survey, T-tomography, E-endoscopy and P-pancreas function testing) algorithm is proposed that proceeds from a non-invasive to a more invasive approach. This algorithm maximizes specificity (low false positive rate) in subjects with chronic abdominal pain and equivocal imaging changes. Futhermore, a nomenclature is suggested to further characterize patients with established chronic pancreatitis based on TIGAR-O (T-toxic, I-idiopathic, G-genetic, A- autoimmune, R-recurrent and O-obstructive) etiology, gland morphology (Cambridge criteria) and physiologic state (exocrine, endocrine function) for uniformity across future multi-center research collaborations. This guideline will serve as a baseline manuscript that will be modified as new evidence becomes available and our knowledge of chronic pancreatitis improves. PMID:25333398

System diagnostics using qualitative analysis and component functional classification

DOEpatents

Reifman, J.; Wei, T.Y.C.

1993-11-23

A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system. 5 figures.

System diagnostics using qualitative analysis and component functional classification

DOEpatents

Reifman, Jaques; Wei, Thomas Y. C.

1993-01-01

A method for detecting and identifying faulty component candidates during off-normal operations of nuclear power plants involves the qualitative analysis of macroscopic imbalances in the conservation equations of mass, energy and momentum in thermal-hydraulic control volumes associated with one or more plant components and the functional classification of components. The qualitative analysis of mass and energy is performed through the associated equations of state, while imbalances in momentum are obtained by tracking mass flow rates which are incorporated into a first knowledge base. The plant components are functionally classified, according to their type, as sources or sinks of mass, energy and momentum, depending upon which of the three balance equations is most strongly affected by a faulty component which is incorporated into a second knowledge base. Information describing the connections among the components of the system forms a third knowledge base. The method is particularly adapted for use in a diagnostic expert system to detect and identify faulty component candidates in the presence of component failures and is not limited to use in a nuclear power plant, but may be used with virtually any type of thermal-hydraulic operating system.

The Quantitative Science of Evaluating Imaging Evidence.

PubMed

Genders, Tessa S S; Ferket, Bart S; Hunink, M G Myriam

2017-03-01

Cardiovascular diagnostic imaging tests are increasingly used in everyday clinical practice, but are often imperfect, just like any other diagnostic test. The performance of a cardiovascular diagnostic imaging test is usually expressed in terms of sensitivity and specificity compared with the reference standard (gold standard) for diagnosing the disease. However, evidence-based application of a diagnostic test also requires knowledge about the pre-test probability of disease, the benefit of making a correct diagnosis, the harm caused by false-positive imaging test results, and potential adverse effects of performing the test itself. To assist in clinical decision making regarding appropriate use of cardiovascular diagnostic imaging tests, we reviewed quantitative concepts related to diagnostic performance (e.g., sensitivity, specificity, predictive values, likelihood ratios), as well as possible biases and solutions in diagnostic performance studies, Bayesian principles, and the threshold approach to decision making. Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Computer-Based and Paper-Based Measurement of Semantic Knowledge

DTIC Science & Technology

1989-01-01

of Personality Assessment , 34, 353-361. McArthur, D. L., & Choppin, B. H. (1984). Computerized diagnostic testing. Journal 15 of Educational...Computers in Human Behavior, 1, 49-58. Lushene, R. E., O’Neii, H. F., & Dunn, T. (1974). Equivalent validity of a completely computerized MMPI. Journal

The engine of thought is a hybrid: roles of associative and structured knowledge in reasoning.

PubMed

Bright, Aimée K; Feeney, Aidan

2014-12-01

Across a range of domains in psychology different theories assume different mental representations of knowledge. For example, in the literature on category-based inductive reasoning, certain theories (e.g., Rogers & McClelland, 2004; Sloutsky & Fisher, 2008) assume that the knowledge upon which inductive inferences are based is associative, whereas others (e.g., Heit & Rubinstein, 1994; Kemp & Tenenbaum, 2009; Osherson, Smith, Wilkie, López, & Shafir, 1990) assume that knowledge is structured. In this article we investigate whether associative and structured knowledge underlie inductive reasoning to different degrees under different processing conditions. We develop a measure of knowledge about the degree of association between categories and show that it dissociates from measures of structured knowledge. In Experiment 1 participants rated the strength of inductive arguments whose categories were either taxonomically or causally related. A measure of associative strength predicted reasoning when people had to respond fast, whereas causal and taxonomic knowledge explained inference strength when people responded slowly. In Experiment 2, we also manipulated whether the causal link between the categories was predictive or diagnostic. Participants preferred predictive to diagnostic arguments except when they responded under cognitive load. In Experiment 3, using an open-ended induction paradigm, people generated and evaluated their own conclusion categories. Inductive strength was predicted by associative strength under heavy cognitive load, whereas an index of structured knowledge was more predictive of inductive strength under minimal cognitive load. Together these results suggest that associative and structured models of reasoning apply best under different processing conditions and that the application of structured knowledge in reasoning is often effortful. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Deficits in knowledge, attitude, and practice towards blood culture sampling: results of a nationwide mixed-methods study among inpatient care physicians in Germany.

PubMed

Raupach-Rosin, Heike; Duddeck, Arne; Gehrlich, Maike; Helmke, Charlotte; Huebner, Johannes; Pletz, Mathias W; Mikolajczyk, Rafael; Karch, André

2017-08-01

Blood culture (BC) sampling rates in Germany are considerably lower than recommended. Aim of our study was to assess knowledge, attitudes, and practice of physicians in Germany regarding BC diagnostics. We conducted a cross-sectional mixed-methods study among physicians working in inpatient care in Germany. Based on the results of qualitative focus groups, a questionnaire-based quantitative study was conducted in 2015-2016. In total, 706 medical doctors and final-year medical students from 11 out of 16 federal states in Germany participated. BC sampling was considered an important diagnostic tool by 95% of the participants. However, only 23% of them would collect BCs in three scenarios for which BC ordering is recommended by present guidelines in Germany; almost one out of ten physicians would not have taken blood cultures in any of the three scenarios. The majority of participants (74%) reported not to adhere to the guideline recommendation that blood culture sampling should include at least two blood culture sets from two different injection sites. High routine in blood culture sampling, perceived importance of blood culture diagnostics, the availability of an in-house microbiological lab, and the department the physician worked in were identified as predictors for good blood culture practice. Our study suggests that there are substantial deficits in BC ordering and the application of guidelines for good BC practice in Germany. Based on these findings, multimodal interventions appear necessary for improving BC diagnostics.

Intelligent model-based diagnostics for vehicle health management

NASA Astrophysics Data System (ADS)

Luo, Jianhui; Tu, Fang; Azam, Mohammad S.; Pattipati, Krishna R.; Willett, Peter K.; Qiao, Liu; Kawamoto, Masayuki

2003-08-01

The recent advances in sensor technology, remote communication and computational capabilities, and standardized hardware/software interfaces are creating a dramatic shift in the way the health of vehicles is monitored and managed. These advances facilitate remote monitoring, diagnosis and condition-based maintenance of automotive systems. With the increased sophistication of electronic control systems in vehicles, there is a concomitant increased difficulty in the identification of the malfunction phenomena. Consequently, the current rule-based diagnostic systems are difficult to develop, validate and maintain. New intelligent model-based diagnostic methodologies that exploit the advances in sensor, telecommunications, computing and software technologies are needed. In this paper, we will investigate hybrid model-based techniques that seamlessly employ quantitative (analytical) models and graph-based dependency models for intelligent diagnosis. Automotive engineers have found quantitative simulation (e.g. MATLAB/SIMULINK) to be a vital tool in the development of advanced control systems. The hybrid method exploits this capability to improve the diagnostic system's accuracy and consistency, utilizes existing validated knowledge on rule-based methods, enables remote diagnosis, and responds to the challenges of increased system complexity. The solution is generic and has the potential for application in a wide range of systems.

Designing a training tool for imaging mental models

NASA Technical Reports Server (NTRS)

Dede, Christopher J.; Jayaram, Geetha

1990-01-01

The training process can be conceptualized as the student acquiring an evolutionary sequence of classification-problem solving mental models. For example a physician learns (1) classification systems for patient symptoms, diagnostic procedures, diseases, and therapeutic interventions and (2) interrelationships among these classifications (e.g., how to use diagnostic procedures to collect data about a patient's symptoms in order to identify the disease so that therapeutic measures can be taken. This project developed functional specifications for a computer-based tool, Mental Link, that allows the evaluative imaging of such mental models. The fundamental design approach underlying this representational medium is traversal of virtual cognition space. Typically intangible cognitive entities and links among them are visible as a three-dimensional web that represents a knowledge structure. The tool has a high degree of flexibility and customizability to allow extension to other types of uses, such a front-end to an intelligent tutoring system, knowledge base, hypermedia system, or semantic network.

Using experts feedback in clinical case resolution and arbitration as accuracy diagnosis methodology.

PubMed

Rodríguez-González, Alejandro; Torres-Niño, Javier; Valencia-Garcia, Rafael; Mayer, Miguel A; Alor-Hernandez, Giner

2013-09-01

This paper proposes a new methodology for assessing the efficiency of medical diagnostic systems and clinical decision support systems by using the feedback/opinions of medical experts. The methodology behind this work is based on a comparison between the expert feedback that has helped solve different clinical cases and the expert system that has evaluated these same cases. Once the results are returned, an arbitration process is carried out in order to ensure the correctness of the results provided by both methods. Once this process has been completed, the results are analyzed using Precision, Recall, Accuracy, Specificity and Matthews Correlation Coefficient (MCC) (PRAS-M) metrics. When the methodology is applied, the results obtained from a real diagnostic system allow researchers to establish the accuracy of the system based on objective facts. The methodology returns enough information to analyze the system's behavior for each disease in the knowledge base or across the entire knowledge base. It also returns data on the efficiency of the different assessors involved in the evaluation process, analyzing their behavior in the diagnostic process. The proposed work facilitates the evaluation of medical diagnostic systems, having a reliable process based on objective facts. The methodology presented in this research makes it possible to identify the main characteristics that define a medical diagnostic system and their values, allowing for system improvement. A good example of the results provided by the application of the methodology is shown in this paper. A diagnosis system was evaluated by means of this methodology, yielding positive results (statistically significant) when comparing the system with the assessors that participated in the evaluation process of the system through metrics such as recall (+27.54%) and MCC (+32.19%). These results demonstrate the real applicability of the methodology used. Copyright © 2013 Elsevier Ltd. All rights reserved.

Developing genomic knowledge bases and databases to support clinical management: current perspectives.

PubMed

Huser, Vojtech; Sincan, Murat; Cimino, James J

2014-01-01

Personalized medicine, the ability to tailor diagnostic and treatment decisions for individual patients, is seen as the evolution of modern medicine. We characterize here the informatics resources available today or envisioned in the near future that can support clinical interpretation of genomic test results. We assume a clinical sequencing scenario (germline whole-exome sequencing) in which a clinical specialist, such as an endocrinologist, needs to tailor patient management decisions within his or her specialty (targeted findings) but relies on a genetic counselor to interpret off-target incidental findings. We characterize the genomic input data and list various types of knowledge bases that provide genomic knowledge for generating clinical decision support. We highlight the need for patient-level databases with detailed lifelong phenotype content in addition to genotype data and provide a list of recommendations for personalized medicine knowledge bases and databases. We conclude that no single knowledge base can currently support all aspects of personalized recommendations and that consolidation of several current resources into larger, more dynamic and collaborative knowledge bases may offer a future path forward.

Developing genomic knowledge bases and databases to support clinical management: current perspectives

PubMed Central

Huser, Vojtech; Sincan, Murat; Cimino, James J

2014-01-01

Personalized medicine, the ability to tailor diagnostic and treatment decisions for individual patients, is seen as the evolution of modern medicine. We characterize here the informatics resources available today or envisioned in the near future that can support clinical interpretation of genomic test results. We assume a clinical sequencing scenario (germline whole-exome sequencing) in which a clinical specialist, such as an endocrinologist, needs to tailor patient management decisions within his or her specialty (targeted findings) but relies on a genetic counselor to interpret off-target incidental findings. We characterize the genomic input data and list various types of knowledge bases that provide genomic knowledge for generating clinical decision support. We highlight the need for patient-level databases with detailed lifelong phenotype content in addition to genotype data and provide a list of recommendations for personalized medicine knowledge bases and databases. We conclude that no single knowledge base can currently support all aspects of personalized recommendations and that consolidation of several current resources into larger, more dynamic and collaborative knowledge bases may offer a future path forward. PMID:25276091

Problem-based learning in internal medicine: virtual patients or paper-based problems?

PubMed

Sobocan, Monika; Turk, Neja; Dinevski, Dejan; Hojs, Radovan; Pecovnik Balon, Breda

2017-01-01

Teaching using paper problem-based learning (p-PBL) sessions has left some students fatigued with the learning process. Therefore, attempts have been made to replace p-PBL with digitally enhanced, decision-making PBL in the form of virtual patients (VP). Student enthusiasm for substituting p-PBL with VP has not been quantitatively evaluated on the intended educational effects. To determine the educational effects of substituting p-PBL sessions with VP on undergraduate medical students in their internal medicine course. We conducted a randomised controlled study on 34 third-year undergraduate medical students in the academic year 2015-2016. Student performance after an intervention substituting p-PBL sessions with VP was analysed. The educational outcomes were measured with knowledge exams and the Diagnostic Thinking Inventory. There was no difference in exam performance between groups (P > 0.833) immediately after the intervention, or in long term. Nor was there a significant difference in improvement of diagnostic thinking between groups (P > 0.935 and P > 0.320). Our study showed no significant improvement in diagnostic thinking abilities or knowledge exam results with the use of VP. Educators can add VP to sessions to motivate students, but a significant improvement to educational outcome should not be expected. © 2016 Royal Australasian College of Physicians.

Will the future of knowledge work automation transform personalized medicine?

PubMed

Naik, Gauri; Bhide, Sanika S

2014-09-01

Today, we live in a world of 'information overload' which demands high level of knowledge-based work. However, advances in computer hardware and software have opened possibilities to automate 'routine cognitive tasks' for knowledge processing. Engineering intelligent software systems that can process large data sets using unstructured commands and subtle judgments and have the ability to learn 'on the fly' are a significant step towards automation of knowledge work. The applications of this technology for high throughput genomic analysis, database updating, reporting clinically significant variants, and diagnostic imaging purposes are explored using case studies.

Automation based on knowledge modeling theory and its applications in engine diagnostic systems using Space Shuttle Main Engine vibrational data. M.S. Thesis

NASA Technical Reports Server (NTRS)

Kim, Jonnathan H.

1995-01-01

Humans can perform many complicated tasks without explicit rules. This inherent and advantageous capability becomes a hurdle when a task is to be automated. Modern computers and numerical calculations require explicit rules and discrete numerical values. In order to bridge the gap between human knowledge and automating tools, a knowledge model is proposed. Knowledge modeling techniques are discussed and utilized to automate a labor and time intensive task of detecting anomalous bearing wear patterns in the Space Shuttle Main Engine (SSME) High Pressure Oxygen Turbopump (HPOTP).

Studies in knowledge-based diagnosis of failures in robotic assembly

NASA Technical Reports Server (NTRS)

Lam, Raymond K.; Pollard, Nancy S.; Desai, Rajiv S.

1990-01-01

The telerobot diagnostic system (TDS) is a knowledge-based system that is being developed for identification and diagnosis of failures in the space robotic domain. The system is able to isolate the symptoms of the failure, generate failure hypotheses based on these symptoms, and test their validity at various levels by interpreting or simulating the effects of the hypotheses on results of plan execution. The implementation of the TDS is outlined. The classification of failures and the types of system models used by the TDS are discussed. A detailed example of the TDS approach to failure diagnosis is provided.

The use of a four-tier wave diagnostic instrument to measure the scientific literacy among students in SMA Negeri 2 Karanganyar

NASA Astrophysics Data System (ADS)

Krisdiana, A.; Aminah, N. S.; Nurosyid, F.

2018-03-01

This study aims to investigate the scientific literacy among 12th grade science students in SMA Negeri 2 Karanganyar. The instrument used is a four-tier wave diagnostic instrument. This instrument was originally used to diagnose students’ conceptions about nature and propagation of waves. This study using quantitative descriptive method. The diagnostic results based on dominant students’ answers show the lack of knowledge percentage of 14.3%-77.1%, alternative conceptions percentage 0%-60%, scientific conceptions percentage 0%-65.7%. Lack of knowledge indicated when there is doubt about at least one tier of the student’s answer. The results of the research shows that the students’ dominant scientific literacy is in the nominal literacy category with the percentage of 22.9% - 91.4%, the functional literacy with the percentage 2.86% - 28.6%, and the conceptual/procedural literacy category with the percentage 0% - 65.7%. Description level of nominal literacy in context of the current study is student have alternative conceptions and lack of knowledge. Student recognize the scientific terms, but is not capable to justify this term.

Energetic particle instabilities in fusion plasmas

NASA Astrophysics Data System (ADS)

Sharapov, S. E.; Alper, B.; Berk, H. L.; Borba, D. N.; Breizman, B. N.; Challis, C. D.; Classen, I. G. J.; Edlund, E. M.; Eriksson, J.; Fasoli, A.; Fredrickson, E. D.; Fu, G. Y.; Garcia-Munoz, M.; Gassner, T.; Ghantous, K.; Goloborodko, V.; Gorelenkov, N. N.; Gryaznevich, M. P.; Hacquin, S.; Heidbrink, W. W.; Hellesen, C.; Kiptily, V. G.; Kramer, G. J.; Lauber, P.; Lilley, M. K.; Lisak, M.; Nabais, F.; Nazikian, R.; Nyqvist, R.; Osakabe, M.; Perez von Thun, C.; Pinches, S. D.; Podesta, M.; Porkolab, M.; Shinohara, K.; Schoepf, K.; Todo, Y.; Toi, K.; Van Zeeland, M. A.; Voitsekhovich, I.; White, R. B.; Yavorskij, V.; TG, ITPA EP; Contributors, JET-EFDA

2013-10-01

Remarkable progress has been made in diagnosing energetic particle instabilities on present-day machines and in establishing a theoretical framework for describing them. This overview describes the much improved diagnostics of Alfvén instabilities and modelling tools developed world-wide, and discusses progress in interpreting the observed phenomena. A multi-machine comparison is presented giving information on the performance of both diagnostics and modelling tools for different plasma conditions outlining expectations for ITER based on our present knowledge.

Conveying Clinical Reasoning Based on Visual Observation via Eye-Movement Modelling Examples

ERIC Educational Resources Information Center

Jarodzka, Halszka; Balslev, Thomas; Holmqvist, Kenneth; Nystrom, Marcus; Scheiter, Katharina; Gerjets, Peter; Eika, Berit

2012-01-01

Complex perceptual tasks, like clinical reasoning based on visual observations of patients, require not only conceptual knowledge about diagnostic classes but also the skills to visually search for symptoms and interpret these observations. However, medical education so far has focused very little on how visual observation skills can be…

Development of scan analysis techniques employing a small computer. Final report, February 1, 1963--July 31, 1976

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuhl, D.E.

1976-08-05

During the thirteen year duration of this contract the goal has been to develop and apply computer based analysis of radionuclide scan data so as to make available improved diagnostic information based on a knowledge of localized quantitative estimates of radionuclide concentration. Results are summarized. (CH)

The KATE shell: An implementation of model-based control, monitor and diagnosis

NASA Technical Reports Server (NTRS)

Cornell, Matthew

1987-01-01

The conventional control and monitor software currently used by the Space Center for Space Shuttle processing has many limitations such as high maintenance costs, limited diagnostic capabilities and simulation support. These limitations have caused the development of a knowledge based (or model based) shell to generically control and monitor electro-mechanical systems. The knowledge base describes the system's structure and function and is used by a software shell to do real time constraints checking, low level control of components, diagnosis of detected faults, sensor validation, automatic generation of schematic diagrams and automatic recovery from failures. This approach is more versatile and more powerful than the conventional hard coded approach and offers many advantages over it, although, for systems which require high speed reaction times or aren't well understood, knowledge based control and monitor systems may not be appropriate.

Case-Based Learning with Worked Examples in Complex Domains: Two Experimental Studies in Undergraduate Medical Education

ERIC Educational Resources Information Center

Stark, Robin; Kopp, Veronika; Fischer, Martin R.

2011-01-01

To investigate the effects of example format (erroneous examples vs. correct examples) and feedback format (elaborated feedback vs. knowledge of results feedback) on medical students' diagnostic competence in the context of a web-based learning environment containing case-based worked examples, two studies with a 2 x 2 design were conducted in the…

A tri-fold hybrid classification approach for diagnostics with unexampled faulty states

NASA Astrophysics Data System (ADS)

Tamilselvan, Prasanna; Wang, Pingfeng

2015-01-01

System health diagnostics provides diversified benefits such as improved safety, improved reliability and reduced costs for the operation and maintenance of engineered systems. Successful health diagnostics requires the knowledge of system failures. However, with an increasing system complexity, it is extraordinarily difficult to have a well-tested system so that all potential faulty states can be realized and studied at product testing stage. Thus, real time health diagnostics requires automatic detection of unexampled system faulty states based upon sensory data to avoid sudden catastrophic system failures. This paper presents a trifold hybrid classification (THC) approach for structural health diagnosis with unexampled health states (UHS), which comprises of preliminary UHS identification using a new thresholded Mahalanobis distance (TMD) classifier, UHS diagnostics using a two-class support vector machine (SVM) classifier, and exampled health states diagnostics using a multi-class SVM classifier. The proposed THC approach, which takes the advantages of both TMD and SVM-based classification techniques, is able to identify and isolate the unexampled faulty states through interactively detecting the deviation of sensory data from the exampled health states and forming new ones autonomously. The proposed THC approach is further extended to a generic framework for health diagnostics problems with unexampled faulty states and demonstrated with health diagnostics case studies for power transformers and rolling bearings.

Sequencing-based diagnostics for pediatric genetic diseases: progress and potential

PubMed Central

Tayoun, Ahmad Abou; Krock, Bryan; Spinner, Nancy B.

2016-01-01

Introduction The last two decades have witnessed revolutionary changes in clinical diagnostics, fueled by the Human Genome Project and advances in high throughput, Next Generation Sequencing (NGS). We review the current state of sequencing-based pediatric diagnostics, associated challenges, and future prospects. Areas Covered We present an overview of genetic disease in children, review the technical aspects of Next Generation Sequencing and the strategies to make molecular diagnoses for children with genetic disease. We discuss the challenges of genomic sequencing including incomplete current knowledge of variants, lack of data about certain genomic regions, mosaicism, and the presence of regions with high homology. Expert Commentary NGS has been a transformative technology and the gap between the research and clinical communities has never been so narrow. Therapeutic interventions are emerging based on genomic findings and the applications of NGS are progressing to prenatal genetics, epigenomics and transcriptomics. PMID:27388938

EMQN best practice guidelines for the molecular genetic testing and reporting of chromosome 11p15 imprinting disorders: Silver–Russell and Beckwith–Wiedemann syndrome

PubMed Central

Eggermann, Katja; Bliek, Jet; Brioude, Frédéric; Algar, Elizabeth; Buiting, Karin; Russo, Silvia; Tümer, Zeynep; Monk, David; Moore, Gudrun; Antoniadi, Thalia; Macdonald, Fiona; Netchine, Irène; Lombardi, Paolo; Soellner, Lukas; Begemann, Matthias; Prawitt, Dirk; Maher, Eamonn R; Mannens, Marcel; Riccio, Andrea; Weksberg, Rosanna; Lapunzina, Pablo; Grønskov, Karen; Mackay, Deborah JG; Eggermann, Thomas

2016-01-01

Molecular genetic testing for the 11p15-associated imprinting disorders Silver–Russell and Beckwith–Wiedemann syndrome (SRS, BWS) is challenging because of the molecular heterogeneity and complexity of the affected imprinted regions. With the growing knowledge on the molecular basis of these disorders and the demand for molecular testing, it turned out that there is an urgent need for a standardized molecular diagnostic testing and reporting strategy. Based on the results from the first external pilot quality assessment schemes organized by the European Molecular Quality Network (EMQN) in 2014 and in context with activities of the European Network of Imprinting Disorders (EUCID.net) towards a consensus in diagnostics and management of SRS and BWS, best practice guidelines have now been developed. Members of institutions working in the field of SRS and BWS diagnostics were invited to comment, and in the light of their feedback amendments were made. The final document was ratified in the course of an EMQN best practice guideline meeting and is in accordance with the general SRS and BWS consensus guidelines, which are in preparation. These guidelines are based on the knowledge acquired from peer-reviewed and published data, as well as observations of the authors in their practice. However, these guidelines can only provide a snapshot of current knowledge at the time of manuscript submission and readers are advised to keep up with the literature. PMID:27165005

Computer-assisted education and interdisciplinary breast cancer diagnosis

NASA Astrophysics Data System (ADS)

Whatmough, Pamela; Gale, Alastair G.; Wilson, A. R. M.

1996-04-01

The diagnosis of breast disease for screening or symptomatic women is largely arrived at by a multi-disciplinary team. We report work on the development and assessment of an inter- disciplinary computer based learning system to support the diagnosis of this disease. The diagnostic process is first modelled from different viewpoints and then appropriate knowledge structures pertinent to the domains of radiologist, pathologist and surgeon are depicted. Initially the underlying inter-relationships of the mammographic diagnostic approach were detailed which is largely considered here. Ultimately a system is envisaged which will link these specialties and act as a diagnostic aid as well as a multi-media educational system.

Effect of an Education Presentation On the Knowledge and Awareness of Urinary Tract Infection among Non-Licensed and Licensed Health Care Workers in Long-Term Care Facilities.

PubMed

Freeman-Jobson, Jennifer H; Rogers, Jamie L; Ward-Smith, Peggy

2016-01-01

This article presents the findings of a pre-test, post-test quality improvement project that describes the change in knowledge from prior to and following an evidence-based education presentation. The presentation addressed the clinical symptoms, diagnostic processes, interventions, and responsibilities of licensed and unlicensed health care workers employed in long-term care facilities related to prevention and detection of non-catheter-related urinary tract infections. Results indicate that the education presentation improved knowledge in specific.

An intelligent interactive simulator of clinical reasoning in general surgery.

PubMed Central

Wang, S.; el Ayeb, B.; Echavé, V.; Preiss, B.

1993-01-01

We introduce an interactive computer environment for teaching in general surgery and for diagnostic assistance. The environment consists of a knowledge-based system coupled with an intelligent interface that allows users to acquire conceptual knowledge and clinical reasoning techniques. Knowledge is represented internally within a probabilistic framework and externally through a interface inspired by Concept Graphics. Given a set of symptoms, the internal knowledge framework computes the most probable set of diseases as well as best alternatives. The interface displays CGs illustrating the results and prompting essential facts of a medical situation or a process. The system is then ready to receive additional information or to suggest further investigation. Based on the new information, the system will narrow the solutions with increased belief coefficients. PMID:8130508

Mixed Methods Survey of Zoonotic Disease Awareness and Practice among Animal and Human Healthcare Providers in Moshi, Tanzania

PubMed Central

Zhang, Helen L.; Mnzava, Kunda W.; Mitchell, Sarah T.; Melubo, Matayo L.; Kibona, Tito J.; Cleaveland, Sarah; Kazwala, Rudovick R.; Crump, John A.; Sharp, Joanne P.; Halliday, Jo E. B.

2016-01-01

Background Zoonoses are common causes of human and livestock illness in Tanzania. Previous studies have shown that brucellosis, leptospirosis, and Q fever account for a large proportion of human febrile illness in northern Tanzania, yet they are infrequently diagnosed. We conducted this study to assess awareness and knowledge regarding selected zoonoses among healthcare providers in Moshi, Tanzania; to determine what diagnostic and treatment protocols are utilized; and obtain insights into contextual factors contributing to the apparent under-diagnosis of zoonoses. Methodology/Results We conducted a questionnaire about zoonoses knowledge, case reporting, and testing with 52 human health practitioners and 10 livestock health providers. Immediately following questionnaire administration, we conducted semi-structured interviews with 60 of these respondents, using the findings of a previous fever etiology study to prompt conversation. Sixty respondents (97%) had heard of brucellosis, 26 (42%) leptospirosis, and 20 (32%) Q fever. Animal sector respondents reported seeing cases of animal brucellosis (4), rabies (4), and anthrax (3) in the previous 12 months. Human sector respondents reported cases of human brucellosis (15, 29%), rabies (9, 18%) and anthrax (6, 12%). None reported leptospirosis or Q fever cases. Nineteen respondents were aware of a local diagnostic test for human brucellosis. Reports of tests for human leptospirosis or Q fever, or for any of the study pathogens in animals, were rare. Many respondents expressed awareness of malaria over-diagnosis and zoonoses under-diagnosis, and many identified low knowledge and testing capacity as reasons for zoonoses under-diagnosis. Conclusions This study revealed differences in knowledge of different zoonoses and low case report frequencies of brucellosis, leptospirosis, and Q fever. There was a lack of known diagnostic services for leptospirosis and Q fever. These findings emphasize a need for improved diagnostic capacity alongside healthcare provider education and improved clinical guidelines for syndrome-based disease management to provoke diagnostic consideration of locally relevant zoonoses in the absence of laboratory confirmation. PMID:26943334

Diagnostic reasoning: where we've been, where we're going.

PubMed

Monteiro, Sandra M; Norman, Geoffrey

2013-01-01

Recently, clinical diagnostic reasoning has been characterized by "dual processing" models, which postulate a fast, unconscious (System 1) component and a slow, logical, analytical (System 2) component. However, there are a number of variants of this basic model, which may lead to conflicting claims. This paper critically reviews current theories and evidence about the nature of clinical diagnostic reasoning. We begin by briefly discussing the history of research in clinical reasoning. We then focus more specifically on the evidence to support dual-processing models. We conclude by identifying knowledge gaps about clinical reasoning and provide suggestions for future research. In contrast to work on analytical and nonanalytical knowledge as a basis for reasoning, these theories focus on the thinking process, not the nature of the knowledge retrieved. Ironically, this appears to be a revival of an outdated concept. Rather than defining diagnostic performance by problem-solving skills, it is now being defined by processing strategy. The version of dual processing that has received most attention in the literature in medical diagnosis might be labeled a "default/interventionist" model,(17) which suggests that a default system of cognitive processes (System 1) is responsible for cognitive biases that lead to diagnostic errors and that System 2 intervenes to correct these errors. Consequently, from this model, the best strategy for reducing errors is to make students aware of the biases and to encourage them to rely more on System 2. However, an accumulation of evidence suggests that (a) strategies directed at increasing analytical (System 2) processing, by slowing down, reducing distractions, paying conscious attention, and (b) strategies directed at making students aware of the effect of cognitive biases, have no impact on error rates. Conversely, strategies based on increasing application of relevant knowledge appear to have some success and are consistent with basic research on concept formation.

Realtime Knowledge Management (RKM): From an International Space Station (ISS) Point of View

NASA Technical Reports Server (NTRS)

Robinson, Peter I.; McDermott, William; Alena, Richard L.

2004-01-01

We are developing automated methods to provide realtime access to spacecraft domain knowledge relevant a spacecraft's current operational state. The method is based upon analyzing state-transition signatures in the telemetry stream. A key insight is that documentation relevant to a specific failure mode or operational state is related to the structure and function of spacecraft systems. This means that diagnostic dependency and state models can provide a roadmap for effective documentation navigation and presentation. Diagnostic models consume the telemetry and derive a high-level state description of the spacecraft. Each potential spacecraft state description is matched against the predictions of models that were developed from information found in the pages and sections in the relevant International Space Station (ISS) documentation and reference materials. By annotating each model fragment with the domain knowledge sources from which it was derived we can develop a system that automatically selects those documents representing the domain knowledge encapsulated by the models that compute the current spacecraft state. In this manner, when the spacecraft state changes, the relevant documentation context and presentation will also change.

Computer decision support system for the stomach cancer diagnosis

NASA Astrophysics Data System (ADS)

Polyakov, E. V.; Sukhova, O. G.; Korenevskaya, P. Y.; Ovcharova, V. S.; Kudryavtseva, I. O.; Vlasova, S. V.; Grebennikova, O. P.; Burov, D. A.; Yemelyanova, G. S.; Selchuk, V. Y.

2017-01-01

The paper considers the creation of the computer knowledge base containing the data of histological, cytologic, and clinical researches. The system is focused on improvement of diagnostics quality of stomach cancer - one of the most frequent death causes among oncologic patients.

Applying Evidence-Centered Design for the Development of Game-Based Assessments in Physics Playground

ERIC Educational Resources Information Center

Kim, Yoon Jeon; Almond, Russell G.; Shute, Valerie J.

2016-01-01

Game-based assessment (GBA) is a specific use of educational games that employs game activities to elicit evidence for educationally valuable skills and knowledge. While this approach can provide individualized and diagnostic information about students, the design and development of assessment mechanics for a GBA is a nontrivial task. In this…

The Buffer Diagnostic Prototype: A fault isolation application using CLIPS

NASA Technical Reports Server (NTRS)

Porter, Ken

1994-01-01

This paper describes problem domain characteristics and development experiences from using CLIPS 6.0 in a proof-of-concept troubleshooting application called the Buffer Diagnostic Prototype. The problem domain is a large digital communications subsystems called the real-time network (RTN), which was designed to upgrade the launch processing system used for shuttle support at KSC. The RTN enables up to 255 computers to share 50,000 data points with millisecond response times. The RTN's extensive built-in test capability but lack of any automatic fault isolation capability presents a unique opportunity for a diagnostic expert system application. The Buffer Diagnostic Prototype addresses RTN diagnosis with a multiple strategy approach. A novel technique called 'faulty causality' employs inexact qualitative models to process test results. Experimental knowledge provides a capability to recognize symptom-fault associations. The implementation utilizes rule-based and procedural programming techniques, including a goal-directed control structure and simple text-based generic user interface that may be reusable for other rapid prototyping applications. Although limited in scope, this project demonstrates a diagnostic approach that may be adapted to troubleshoot a broad range of equipment.

Blood-based diagnostics of traumatic brain injuries

PubMed Central

Mondello, Stefania; Muller, Uwe; Jeromin, Andreas; Streeter, Jackson; Hayes, Ronald L; Wang, Kevin KW

2011-01-01

Traumatic brain injury is a major health and socioeconomic problem that affects all societies. However, traditional approaches to the classification of clinical severity are the subject of debate and are being supplemented with structural and functional neuroimaging, as the need for biomarkers that reflect elements of the pathogenetic process is widely recognized. Basic science research and developments in the field of proteomics have greatly advanced our knowledge of the mechanisms involved in damage and have led to the discovery and rapid detection of new biomarkers that were not available previously. However, translating this research for patients' benefits remains a challenge. In this article, we summarize new developments, current knowledge and controversies, focusing on the potential role of these biomarkers as diagnostic, prognostic and monitoring tools of brain-injured patients. PMID:21171922

Towards a machine learning framework for acquiring and exploiting monitoring and diagnostic knowledge

NASA Technical Reports Server (NTRS)

Manganaris, Stefanos; Fisher, Doug; Kulkarni, Deepak

1993-01-01

In this paper we address the problem of detecting and diagnosing faults in physical systems, for which neither prior expertise for the task nor suitable system models are available. We propose an architecture that integrates the on-line acquisition and exploitation of monitoring and diagnostic knowledge. The focus of the paper is on the component of the architecture that discovers classes of behaviors with similar characteristics by observing a system in operation. We investigate a characterization of behaviors based on best fitting approximation models. An experimental prototype has been implemented to test it. We present preliminary results in diagnosing faults of the Reaction Control System of the Space Shuttle. The merits and limitations of the approach are identified and directions for future work are set.

LEADER - An integrated engine behavior and design analyses based real-time fault diagnostic expert system for Space Shuttle Main Engine (SSME)

NASA Technical Reports Server (NTRS)

Gupta, U. K.; Ali, M.

1989-01-01

The LEADER expert system has been developed for automatic learning tasks encompassing real-time detection, identification, verification, and correction of anomalous propulsion system operations, using a set of sensors to monitor engine component performance to ascertain anomalies in engine dynamics and behavior. Two diagnostic approaches are embodied in LEADER's architecture: (1) learning and identifying engine behavior patterns to generate novel hypotheses about possible abnormalities, and (2) the direction of engine sensor data processing to perform resoning based on engine design and functional knowledge, as well as the principles of the relevant mechanics and physics.

A feature dictionary supporting a multi-domain medical knowledge base.

PubMed

Naeymi-Rad, F

1989-01-01

Because different terminology is used by physicians of different specialties in different locations to refer to the same feature (signs, symptoms, test results), it is essential that our knowledge development tools provide a means to access a common pool of terms. This paper discusses the design of an online medical dictionary that provides a solution to this problem for developers of multi-domain knowledge bases for MEDAS (Medical Emergency Decision Assistance System). Our Feature Dictionary supports phrase equivalents for features, feature interactions, feature classifications, and translations to the binary features generated by the expert during knowledge creation. It is also used in the conversion of a domain knowledge to the database used by the MEDAS inference diagnostic sessions. The Feature Dictionary also provides capabilities for complex queries across multiple domains using the supported relations. The Feature Dictionary supports three methods for feature representation: (1) for binary features, (2) for continuous valued features, and (3) for derived features.

Students' understandings of electrochemistry

NASA Astrophysics Data System (ADS)

O'Grady-Morris, Kathryn

Electrochemistry is considered by students to be a difficult topic in chemistry. This research was a mixed methods study guided by the research question: At the end of a unit of study, what are students' understandings of electrochemistry? The framework of analysis used for the qualitative and quantitative data collected in this study was comprised of three categories: types of knowledge used in problem solving, levels of representation of knowledge in chemistry (macroscopic, symbolic, and particulate), and alternative conceptions. Although individually each of the three categories has been reported in previous studies, the contribution of this study is the inter-relationships among them. Semi-structured, task-based interviews were conducted while students were setting up and operating electrochemical cells in the laboratory, and a two-tiered, multiple-choice diagnostic instrument was designed to identify alternative conceptions that students held at the end of the unit. For familiar problems, those involving routine voltaic cells, students used a working-forwards problem-solving strategy, two or three levels of representation of knowledge during explanations, scored higher on both procedural and conceptual knowledge questions in the diagnostic instrument, and held fewer alternative conceptions related to the operation of these cells. For less familiar problems, those involving non-routine voltaic cells and electrolytic cells, students approached problem-solving with procedural knowledge, used only one level of representation of knowledge when explaining the operation of these cells, scored higher on procedural knowledge than conceptual knowledge questions in the diagnostic instrument, and held a greater number of alternative conceptions. Decision routines that involved memorized formulas and procedures were used to solve both quantitative and qualitative problems and the main source of alternative conceptions in this study was the overgeneralization of theory related to the particulate level of representation of knowledge. The findings from this study may contribute further to our understanding of students' conceptions in electrochemistry. Furthermore, understanding the influence of the three categories in the framework of analysis and their inter-relationships on how students make sense of this field may result in a better understanding of classroom practice that could promote the acquisition of conceptual knowledge --- knowledge that is "rich in relationships".

Developing a Research Agenda to Optimize Diagnostic Imaging in the Emergency Department: An Executive Summary of the 2015 Academic Emergency Medicine Consensus Conference.

PubMed

Marin, Jennifer R; Mills, Angela M

2015-12-01

The 2015 Academic Emergency Medicine consensus conference, "Diagnostic Imaging in the Emergency Department: A Research Agenda to Optimize Utilization" was held on May 12, 2015, with the goal of developing a high-priority research agenda on which to base future research. The specific aims of the conference were to (1) understand the current state of evidence regarding emergency department (ED) diagnostic imaging use and identify key opportunities, limitations, and gaps in knowledge; (2) develop a consensus-driven research agenda emphasizing priorities and opportunities for research in ED diagnostic imaging; and (3) explore specific funding mechanisms available to facilitate research in ED diagnostic imaging. Over a 2-year period, the executive committee and other experts in the field convened regularly to identify specific areas in need of future research. Six content areas within emergency diagnostic imaging were identified before the conference and served as the breakout groups on which consensus was achieved: clinical decision rules; use of administrative data; patient-centered outcomes research; training, education, and competency; knowledge translation and barriers to imaging optimization; and comparative effectiveness research in alternatives to traditional computed tomography use. The executive committee invited key stakeholders to assist with the planning and to participate in the consensus conference to generate a multidisciplinary agenda. There were a total of 164 individuals involved in the conference and spanned various specialties, including general emergency medicine, pediatric emergency medicine, radiology, surgery, medical physics, and the decision sciences.

Artificial intelligence in hematology.

PubMed

Zini, Gina

2005-10-01

Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.

Object-oriented fault tree models applied to system diagnosis

NASA Technical Reports Server (NTRS)

Iverson, David L.; Patterson-Hine, F. A.

1990-01-01

When a diagnosis system is used in a dynamic environment, such as the distributed computer system planned for use on Space Station Freedom, it must execute quickly and its knowledge base must be easily updated. Representing system knowledge as object-oriented augmented fault trees provides both features. The diagnosis system described here is based on the failure cause identification process of the diagnostic system described by Narayanan and Viswanadham. Their system has been enhanced in this implementation by replacing the knowledge base of if-then rules with an object-oriented fault tree representation. This allows the system to perform its task much faster and facilitates dynamic updating of the knowledge base in a changing diagnosis environment. Accessing the information contained in the objects is more efficient than performing a lookup operation on an indexed rule base. Additionally, the object-oriented fault trees can be easily updated to represent current system status. This paper describes the fault tree representation, the diagnosis algorithm extensions, and an example application of this system. Comparisons are made between the object-oriented fault tree knowledge structure solution and one implementation of a rule-based solution. Plans for future work on this system are also discussed.

Nontargeted diagnostic ion network analysis (NINA): A software to streamline the analytical workflow for untargeted characterization of natural medicines.

PubMed

Ye, Hui; Zhu, Lin; Sun, Di; Luo, Xiaozhuo; Lu, Gaoyuan; Wang, Hong; Wang, Jing; Cao, Guoxiu; Xiao, Wei; Wang, Zhenzhong; Wang, Guangji; Hao, Haiping

2016-11-30

The characterization of herbal prescriptions serves as a foundation for quality control and regulation of herbal medicines. Previously, the characterization of herbal chemicals from natural medicines often relied on the analysis of signature fragment ions from the acquired tandem mass spectrometry (MS/MS) spectra with prior knowledge of the herbal species present in the herbal prescriptions of interest. Nevertheless, such an approach is often limited to target components, and it risks missing the critical components that we have no prior knowledge of. We previously reported a "diagnostic ion-guided network bridging" strategy. It is a generally applicable and robust approach to analyze unknown substances from complex mixtures in an untargeted manner. In this study, we have developed a standalone software named "Nontargeted Diagnostic Ion Network Analysis (NINA)" with a graphical user interface based on a strategy for post-acquisition data analysis. NINA allows one to rapidly determine the nontargeted diagnostic ions (NIs) by summarizing all of the fragment ions shared by the precursors from the acquired MS/MS spectra. A NI-guided network using bridging components that possess two or more NIs can then be established via NINA. With such a network, we could sequentially identify the structures of all the NIs once a single compound has been identified de novo. The structures of NIs can then be used as "priori" knowledge to narrow the candidates containing the sub-structure of the corresponding NI from the database hits. Subsequently, we applied the NINA software to the characterization of a model herbal prescription, Re-Du-Ning injection, and rapidly identified 56 herbal chemicals from the prescription using an ultra-performance liquid chromatography quadrupole time-of-flight system in the negative mode with no knowledge of the herbal species or herbal chemicals in the mixture. Therefore, we believe the applications of NINA will greatly facilitate the characterization of complex mixtures, such as natural medicines, especially when no advance information is available. In addition to herbal medicines, the NINA-based workflow will also benefit many other fields, such as environmental analysis, nutritional science, and forensic analysis. Copyright © 2016 Elsevier B.V. All rights reserved.

Diagnosis and sensor validation through knowledge of structure and function

NASA Technical Reports Server (NTRS)

Scarl, Ethan A.; Jamieson, John R.; Delaune, Carl I.

1987-01-01

The liquid oxygen expert system 'LES' is proposed as the first capable of diagnostic reasoning from sensor data, using model-based knowledge of structure and function to find the expected state of all system objects, including sensors. The approach is generally algorithmic rather than heuristic, and represents uncertainties as sets of possibilities. Functional relationships are inverted to determine hypothetical values for potentially faulty objects, and may include conditional functions not normally considered to have inverses.

a Study on Satellite Diagnostic Expert Systems Using Case-Based Approach

NASA Astrophysics Data System (ADS)

Park, Young-Tack; Kim, Jae-Hoon; Park, Hyun-Soo

1997-06-01

Many research works are on going to monitor and diagnose diverse malfunctions of satellite systems as the complexity and number of satellites increase. Currently, many works on monitoring and diagnosis are carried out by human experts but there are needs to automate much of the routine works of them. Hence, it is necessary to study on using expert systems which can assist human experts routine work by doing automatically, thereby allow human experts devote their expertise more critical and important areas of monitoring and diagnosis. In this paper, we are employing artificial intelligence techniques to model human experts' knowledge and inference the constructed knowledge. Especially, case-based approaches are used to construct a knowledge base to model human expert capabilities which use previous typical exemplars. We have designed and implemented a prototype case-based system for diagnosing satellite malfunctions using cases. Our system remembers typical failure cases and diagnoses a current malfunction by indexing the case base. Diverse methods are used to build a more user friendly interface which allows human experts can build a knowledge base in as easy way.

Diagnosis demystified: CT as diagnostic tool in endodontics

PubMed Central

Shruthi, Nagaraja; Sreenivasa Murthy, B V; Sundaresh, K J; Mallikarjuna, Rachappa

2013-01-01

Diagnosis in endodontics is usually based on clinical and radiographical presentations, which are only empirical methods. The role of healing profession is to apply knowledge and skills towards maintaining and restoring the patient's health. Recent advances in imaging technologies have added to correct interpretation and diagnosis. CT is proving to be an effective tool in solving endodontic mysteries through its three-dimensional visualisation. CT imaging offers many diagnostic advantages to produce reconstructed images in selected projection and low-contrast resolution far superior to that of all other X-ray imaging modalities. This case report is an endeavour towards effective treatment planning of cases with root fracture, root resorption using spiral CT as an adjuvant diagnostic tool. PMID:23814212

Integrating HL7 RIM and ontology for unified knowledge and data representation in clinical decision support systems.

PubMed

Zhang, Yi-Fan; Tian, Yu; Zhou, Tian-Shu; Araki, Kenji; Li, Jing-Song

2016-01-01

The broad adoption of clinical decision support systems within clinical practice has been hampered mainly by the difficulty in expressing domain knowledge and patient data in a unified formalism. This paper presents a semantic-based approach to the unified representation of healthcare domain knowledge and patient data for practical clinical decision making applications. A four-phase knowledge engineering cycle is implemented to develop a semantic healthcare knowledge base based on an HL7 reference information model, including an ontology to model domain knowledge and patient data and an expression repository to encode clinical decision making rules and queries. A semantic clinical decision support system is designed to provide patient-specific healthcare recommendations based on the knowledge base and patient data. The proposed solution is evaluated in the case study of type 2 diabetes mellitus inpatient management. The knowledge base is successfully instantiated with relevant domain knowledge and testing patient data. Ontology-level evaluation confirms model validity. Application-level evaluation of diagnostic accuracy reaches a sensitivity of 97.5%, a specificity of 100%, and a precision of 98%; an acceptance rate of 97.3% is given by domain experts for the recommended care plan orders. The proposed solution has been successfully validated in the case study as providing clinical decision support at a high accuracy and acceptance rate. The evaluation results demonstrate the technical feasibility and application prospect of our approach. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Organization and integration of biomedical knowledge with concept maps for key peroxisomal pathways.

PubMed

Willemsen, A M; Jansen, G A; Komen, J C; van Hooff, S; Waterham, H R; Brites, P M T; Wanders, R J A; van Kampen, A H C

2008-08-15

One important area of clinical genomics research involves the elucidation of molecular mechanisms underlying (complex) disorders which eventually may lead to new diagnostic or drug targets. To further advance this area of clinical genomics one of the main challenges is the acquisition and integration of data, information and expert knowledge for specific biomedical domains and diseases. Currently the required information is not very well organized but scattered over biological and biomedical databases, basic text books, scientific literature and experts' minds and may be highly specific, heterogeneous, complex and voluminous. We present a new framework to construct knowledge bases with concept maps for presentation of information and the web ontology language OWL for the representation of information. We demonstrate this framework through the construction of a peroxisomal knowledge base, which focuses on four key peroxisomal pathways and several related genetic disorders. All 155 concept maps in our knowledge base are linked to at least one other concept map, which allows the visualization of one big network of related pieces of information. The peroxisome knowledge base is available from www.bioinformaticslaboratory.nl (Support-->Web applications). Supplementary data is available from www.bioinformaticslaboratory.nl (Research-->Output--> Publications--> KB_SuppInfo)

Distributed Knowledge Base Systems for Diagnosis and Information Retrieval.

DTIC Science & Technology

1983-11-01

social system metaphors State University. for distributed problem solving: Introduction to the issue. IEEE Newell. A. and Simon, H. A. (1972) Human...experts and Sriram Mahalingam wha-helped think out the probLema associated with building Auto-Mech. Research on diagnostic expert systemas for the

Image-based diagnostic aid for interstitial lung disease with secondary data integration

NASA Astrophysics Data System (ADS)

Depeursinge, Adrien; Müller, Henning; Hidki, Asmâa; Poletti, Pierre-Alexandre; Platon, Alexandra; Geissbuhler, Antoine

2007-03-01

Interstitial lung diseases (ILDs) are a relatively heterogeneous group of around 150 illnesses with often very unspecific symptoms. The most complete imaging method for the characterisation of ILDs is the high-resolution computed tomography (HRCT) of the chest but a correct interpretation of these images is difficult even for specialists as many diseases are rare and thus little experience exists. Moreover, interpreting HRCT images requires knowledge of the context defined by clinical data of the studied case. A computerised diagnostic aid tool based on HRCT images with associated medical data to retrieve similar cases of ILDs from a dedicated database can bring quick and precious information for example for emergency radiologists. The experience from a pilot project highlighted the need for detailed database containing high-quality annotations in addition to clinical data. The state of the art is studied to identify requirements for image-based diagnostic aid for interstitial lung disease with secondary data integration. The data acquisition steps are detailed. The selection of the most relevant clinical parameters is done in collaboration with lung specialists from current literature, along with knowledge bases of computer-based diagnostic decision support systems. In order to perform high-quality annotations of the interstitial lung tissue in the HRCT images an annotation software and its own file format is implemented for DICOM images. A multimedia database is implemented to store ILD cases with clinical data and annotated image series. Cases from the University & University Hospitals of Geneva (HUG) are retrospectively and prospectively collected to populate the database. Currently, 59 cases with certified diagnosis and their clinical parameters are stored in the database as well as 254 image series of which 26 have their regions of interest annotated. The available data was used to test primary visual features for the classification of lung tissue patterns. These features show good discriminative properties for the separation of five classes of visual observations.

Fault Tree Based Diagnosis with Optimal Test Sequencing for Field Service Engineers

NASA Technical Reports Server (NTRS)

Iverson, David L.; George, Laurence L.; Patterson-Hine, F. A.; Lum, Henry, Jr. (Technical Monitor)

1994-01-01

When field service engineers go to customer sites to service equipment, they want to diagnose and repair failures quickly and cost effectively. Symptoms exhibited by failed equipment frequently suggest several possible causes which require different approaches to diagnosis. This can lead the engineer to follow several fruitless paths in the diagnostic process before they find the actual failure. To assist in this situation, we have developed the Fault Tree Diagnosis and Optimal Test Sequence (FTDOTS) software system that performs automated diagnosis and ranks diagnostic hypotheses based on failure probability and the time or cost required to isolate and repair each failure. FTDOTS first finds a set of possible failures that explain exhibited symptoms by using a fault tree reliability model as a diagnostic knowledge to rank the hypothesized failures based on how likely they are and how long it would take or how much it would cost to isolate and repair them. This ordering suggests an optimal sequence for the field service engineer to investigate the hypothesized failures in order to minimize the time or cost required to accomplish the repair task. Previously, field service personnel would arrive at the customer site and choose which components to investigate based on past experience and service manuals. Using FTDOTS running on a portable computer, they can now enter a set of symptoms and get a list of possible failures ordered in an optimal test sequence to help them in their decisions. If facilities are available, the field engineer can connect the portable computer to the malfunctioning device for automated data gathering. FTDOTS is currently being applied to field service of medical test equipment. The techniques are flexible enough to use for many different types of devices. If a fault tree model of the equipment and information about component failure probabilities and isolation times or costs are available, a diagnostic knowledge base for that device can be developed easily.

Exploitation of biotechnology in a large company.

PubMed

Dart, E C

1989-08-31

Almost from the outset, most large companies saw the 'new biotechnology' not as a new business but as a set of very powerful techniques that, in time, would radically improve the understanding of biological systems. This new knowledge was generally seen by them as enhancing the process of invention and not as a substitute for tried and tested ways of meeting clearly identified targets. As the knowledge base grows, so the big-company response to biotechnology becomes more positive. Within ICI, biotechnology is now integrated into five bio-businesses (Pharmaceuticals, Agrochemicals, Seeds, Diagnostics and Biological Products). Within the Central Toxicology Laboratory it also contributes to the understanding of the mechanisms of toxic action of chemicals as part of assessing risk. ICI has entered two of these businesses (Seeds and Diagnostics) because it sees biotechnology making a major contribution to the profitability of each.

Computer based extraction of phenoptypic features of human congenital anomalies from the digital literature with natural language processing techniques.

PubMed

Karakülah, Gökhan; Dicle, Oğuz; Koşaner, Ozgün; Suner, Aslı; Birant, Çağdaş Can; Berber, Tolga; Canbek, Sezin

2014-01-01

The lack of laboratory tests for the diagnosis of most of the congenital anomalies renders the physical examination of the case crucial for the diagnosis of the anomaly; and the cases in the diagnostic phase are mostly being evaluated in the light of the literature knowledge. In this respect, for accurate diagnosis, ,it is of great importance to provide the decision maker with decision support by presenting the literature knowledge about a particular case. Here, we demonstrated a methodology for automated scanning and determining of the phenotypic features from the case reports related to congenital anomalies in the literature with text and natural language processing methods, and we created a framework of an information source for a potential diagnostic decision support system for congenital anomalies.

Fusing Symbolic and Numerical Diagnostic Computations

NASA Technical Reports Server (NTRS)

James, Mark

2007-01-01

X-2000 Anomaly Detection Language denotes a developmental computing language, and the software that establishes and utilizes the language, for fusing two diagnostic computer programs, one implementing a numerical analysis method, the other implementing a symbolic analysis method into a unified event-based decision analysis software system for realtime detection of events (e.g., failures) in a spacecraft, aircraft, or other complex engineering system. The numerical analysis method is performed by beacon-based exception analysis for multi-missions (BEAMs), which has been discussed in several previous NASA Tech Briefs articles. The symbolic analysis method is, more specifically, an artificial-intelligence method of the knowledge-based, inference engine type, and its implementation is exemplified by the Spacecraft Health Inference Engine (SHINE) software. The goal in developing the capability to fuse numerical and symbolic diagnostic components is to increase the depth of analysis beyond that previously attainable, thereby increasing the degree of confidence in the computed results. In practical terms, the sought improvement is to enable detection of all or most events, with no or few false alarms.

The Development and Validation of a Three-Tier Diagnostic Test Measuring Pre-Service Elementary Education and Secondary Science Teachers' Understanding of the Water Cycle

ERIC Educational Resources Information Center

Schaffer, Dannah Lynn

2013-01-01

The main goal of this research study was to develop and validate a three-tier diagnostic test to determine pre-service teachers' (PSTs) conceptual knowledge of the water cycle. For a three-tier diagnostic test, the first tier assesses content knowledge; in the second tier, a reason is selected for the content answer; and the third tier allows…

An SSME High Pressure Oxidizer Turbopump diagnostic system using G2 real-time expert system

NASA Technical Reports Server (NTRS)

Guo, Ten-Huei

1991-01-01

An expert system which diagnoses various seal leakage faults in the High Pressure Oxidizer Turbopump of the SSME was developed using G2 real-time expert system. Three major functions of the software were implemented: model-based data generation, real-time expert system reasoning, and real-time input/output communication. This system is proposed as one module of a complete diagnostic system for the SSME. Diagnosis of a fault is defined as the determination of its type, severity, and likelihood. Since fault diagnosis is often accomplished through the use of heuristic human knowledge, an expert system based approach has been adopted as a paradigm to develop this diagnostic system. To implement this approach, a software shell which can be easily programmed to emulate the human decision process, the G2 Real-Time Expert System, was selected. Lessons learned from this implementation are discussed.

An SSME high pressure oxidizer turbopump diagnostic system using G2(TM) real-time expert system

NASA Technical Reports Server (NTRS)

Guo, Ten-Huei

1991-01-01

An expert system which diagnoses various seal leakage faults in the High Pressure Oxidizer Turbopump of the SSME was developed using G2(TM) real-time expert system. Three major functions of the software were implemented: model-based data generation, real-time expert system reasoning, and real-time input/output communication. This system is proposed as one module of a complete diagnostic system for Space Shuttle Main Engine. Diagnosis of a fault is defined as the determination of its type, severity, and likelihood. Since fault diagnosis is often accomplished through the use of heuristic human knowledge, an expert system based approach was adopted as a paradigm to develop this diagnostic system. To implement this approach, a software shell which can be easily programmed to emulate the human decision process, the G2 Real-Time Expert System, was selected. Lessons learned from this implementation are discussed.

Recommendations for the use of molecular diagnostics in the diagnosis of allergic dis-eases.

PubMed

Villalta, D; Tonutti, E; Bizzaro, N; Brusca, I; Sargentini, V; Asero, R; Bilo, M B; Manzotti, G; Murzilli, F; Cecchi, L; Musarra, A

2018-03-01

The Study Group on Allergology of the Italian Society of Clinical Pathology and Laboratory Medicine (SIPMeL) and the Associazione Italiana degli Allergologi e Immunologi Territoriali e Ospedalieri (AAIITO) developed the present recommendations on the diagnosis of allergic diseases based on the use of molecular allergenic components, whose purpose is to provide the pathologists and the clinicians with information and algorithms enabling a proper use of this second-level diagnostics. Molecular diagnostics allows definition of the exact sensitization profile of the allergic patient. The methodology followed to develop these recommendations included an initial phase of discussion between all the components to integrate the knowledge derived from scientific evidence, a revision of the recommendations made by Italian and foreign experts, and the subsequent production of this document to be disseminated to all those who deal with allergy diagnostics.

Diagnostic grand rounds: a new teaching concept to train diagnostic reasoning.

PubMed

Stieger, Stefan; Praschinger, Andrea; Kletter, Kurt; Kainberger, Franz

2011-06-01

Diagnostic reasoning is a core skill in teaching and learning in undergraduate curricula. Diagnostic grand rounds (DGRs) as a subform of grand rounds are intended to train the students' skills in the selection of appropriate tests and in the interpretation of test results. The aim of this study was to test DGRs for their ability to improve diagnostic reasoning by using a pre-post-test design. During one winter term, all 398 fifth-year students (36.1% male, 63.9% female) solved 23 clinical cases presented in 8 DGRs. In an online questionnaire, a Diagnostic Thinking Inventory (DTI) with 41 items was evaluated for flexibility in thinking and structure of knowledge in memory. Results were correlated with those from a summative multiple-choice knowledge test and of the learning objectives in a logbook. The students' DTI scores in the post-test were significantly higher than those reported in the pre-test. DTI scores at either testing time did not correlate with medical knowledge as assessed by a multiple-choice knowledge test. Abilities acquired during clinical clerkships as documented in a logbook could only account for a small proportion of the increase in the flexibility subscale score. This effect still remained significant after accounting for potential confounders. Establishing DGRs proofed to be an effective way of successfully improving both students' diagnostic reasoning and the ability to select the appropriate test method in routine clinical practice. Copyright © 2009 Elsevier Ireland Ltd. All rights reserved.

An Investigation of Expertise: Implications for Adult Educators.

ERIC Educational Resources Information Center

Mandernach, Janice B.

To examine the characteristics of expertise, a study at the University of Minnesota cardiac clinic compared differences in diagnostic ability and strategies between novices (fourth year medical students) and experts (specialists in pediatric cardiology). The investigator presented a model for expertise based on knowledge of subject matter content…

Spatially targeted social interventions to improve BMP adoption in Maryland watersheds

USDA-ARS?s Scientific Manuscript database

The results of surveys of stakeholders knowledge and attitudes related to water resources, pollution and Best Management Practices (BMPs) are analyzed and used to develop a model of BMP adoption likelihood based on socio-economic factors. The model is integrated into a Diagnostic Decision Support Sy...

Brain stem death and organ donation.

PubMed

Davies, C

1996-01-01

Our understanding of the concept and definition of death has changed over time. The British contribution to the body of knowledge on the diagnosis of brain steam death was the publication by the medical royal colleges (1976) of diagnostic criteria. Most literature and research which explores the knowledge and attitudes of nurses towards the concept of brain stem death is from the USA. Several issues which arise from the literature are discussed in relation to organ donation. Further UK-based research is required.

Viral diseases of new world camelids.

PubMed

Kapil, Sanjay; Yeary, Teresa; Evermann, James F

2009-07-01

The increased popularity and population of New World camelids in the United States requires the development of a broader base of knowledge of the health and disease parameters for these animals by the veterinary livestock practitioner. Although our knowledge regarding infectious diseases of camelids has increased greatly over the past decade, the practice of camelid medicine is a relatively new field in North America, so it is important to seek out seasoned colleagues and diagnostic laboratories that are involved in camelid health treatment and diagnosis.

A Three-Tier Diagnostic Test to Assess Pre-Service Teachers' Misconceptions about Global Warming, Greenhouse Effect, Ozone Layer Depletion, and Acid Rain

NASA Astrophysics Data System (ADS)

Ozge Arslan, Harika; Cigdemoglu, Ceyhan; Moseley, Christine

2012-07-01

This study describes the development and validation of a three-tier multiple-choice diagnostic test, the atmosphere-related environmental problems diagnostic test (AREPDiT), to reveal common misconceptions of global warming (GW), greenhouse effect (GE), ozone layer depletion (OLD), and acid rain (AR). The development of a two-tier diagnostic test procedure as described by Treagust constitutes the framework for this study. To differentiate a lack of knowledge from a misconception, a certainty response index is added as a third tier to each item. Based on propositional knowledge statements, related literature, and the identified misconceptions gathered initially from 157 pre-service teachers, the AREPDiT was constructed and administered to 256 pre-service teachers. The Cronbach alpha reliability coefficient of the pre-service teachers' scores was estimated to be 0.74. Content and face validations were established by senior experts. A moderate positive correlation between the participants' both-tiers scores and their certainty scores indicated evidence for construct validity. Therefore, the AREPDiT is a reliable and valid instrument not only to identify pre-service teachers' misconceptions about GW, GE, OLD, and AR but also to differentiate these misconceptions from lack of knowledge. The results also reveal that a majority of the respondents demonstrated limited understandings about atmosphere-related environmental problems and held six common misconceptions. Future studies could test the AREPDiT as a tool for assessing the misconceptions held by pre-service teachers from different programs as well as in-service teachers and high school students.

Developing a Research Agenda to Optimize Diagnostic Imaging in the Emergency Department: An Executive Summary of the 2015 Academic Emergency Medicine Consensus Conference.

PubMed

Marin, Jennifer R; Mills, Angela M

2015-12-01

The 2015 Academic Emergency Medicine (AEM) consensus conference, "Diagnostic Imaging in the Emergency Department: A Research Agenda to Optimize Utilization," was held on May 12, 2015, with the goal of developing a high-priority research agenda on which to base future research. The specific aims of the conference were to: 1) understand the current state of evidence regarding emergency department (ED) diagnostic imaging utilization and identify key opportunities, limitations, and gaps in knowledge; 2) develop a consensus-driven research agenda emphasizing priorities and opportunities for research in ED diagnostic imaging; and 3) explore specific funding mechanisms available to facilitate research in ED diagnostic imaging. Over a 2-year period, the executive committee and other experts in the field convened regularly to identify specific areas in need of future research. Six content areas within emergency diagnostic imaging were identified prior to the conference and served as the breakout groups on which consensus was achieved: clinical decision rules; use of administrative data; patient-centered outcomes research; training, education, and competency; knowledge translation and barriers to imaging optimization; and comparative effectiveness research in alternatives to traditional computed tomography use. The executive committee invited key stakeholders to assist with planning and to participate in the consensus conference to generate a multidisciplinary agenda. There were 164 individuals involved in the conference spanning various specialties, including emergency medicine (EM), radiology, surgery, medical physics, and the decision sciences. This issue of AEM is dedicated to the proceedings of the 16th annual AEM consensus conference as well as original research related to emergency diagnostic imaging. © 2015 by the Society for Academic Emergency Medicine.

Evaluation of Machine Learning and Rules-Based Approaches for Predicting Antimicrobial Resistance Profiles in Gram-negative Bacilli from Whole Genome Sequence Data.

PubMed

Pesesky, Mitchell W; Hussain, Tahir; Wallace, Meghan; Patel, Sanket; Andleeb, Saadia; Burnham, Carey-Ann D; Dantas, Gautam

2016-01-01

The time-to-result for culture-based microorganism recovery and phenotypic antimicrobial susceptibility testing necessitates initial use of empiric (frequently broad-spectrum) antimicrobial therapy. If the empiric therapy is not optimal, this can lead to adverse patient outcomes and contribute to increasing antibiotic resistance in pathogens. New, more rapid technologies are emerging to meet this need. Many of these are based on identifying resistance genes, rather than directly assaying resistance phenotypes, and thus require interpretation to translate the genotype into treatment recommendations. These interpretations, like other parts of clinical diagnostic workflows, are likely to be increasingly automated in the future. We set out to evaluate the two major approaches that could be amenable to automation pipelines: rules-based methods and machine learning methods. The rules-based algorithm makes predictions based upon current, curated knowledge of Enterobacteriaceae resistance genes. The machine-learning algorithm predicts resistance and susceptibility based on a model built from a training set of variably resistant isolates. As our test set, we used whole genome sequence data from 78 clinical Enterobacteriaceae isolates, previously identified to represent a variety of phenotypes, from fully-susceptible to pan-resistant strains for the antibiotics tested. We tested three antibiotic resistance determinant databases for their utility in identifying the complete resistome for each isolate. The predictions of the rules-based and machine learning algorithms for these isolates were compared to results of phenotype-based diagnostics. The rules based and machine-learning predictions achieved agreement with standard-of-care phenotypic diagnostics of 89.0 and 90.3%, respectively, across twelve antibiotic agents from six major antibiotic classes. Several sources of disagreement between the algorithms were identified. Novel variants of known resistance factors and incomplete genome assembly confounded the rules-based algorithm, resulting in predictions based on gene family, rather than on knowledge of the specific variant found. Low-frequency resistance caused errors in the machine-learning algorithm because those genes were not seen or seen infrequently in the test set. We also identified an example of variability in the phenotype-based results that led to disagreement with both genotype-based methods. Genotype-based antimicrobial susceptibility testing shows great promise as a diagnostic tool, and we outline specific research goals to further refine this methodology.

Development of Asset Fault Signatures for Prognostic and Health Management in the Nuclear Industry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vivek Agarwal; Nancy J. Lybeck; Randall Bickford

2014-06-01

Proactive online monitoring in the nuclear industry is being explored using the Electric Power Research Institute’s Fleet-Wide Prognostic and Health Management (FW-PHM) Suite software. The FW-PHM Suite is a set of web-based diagnostic and prognostic tools and databases that serves as an integrated health monitoring architecture. The FW-PHM Suite has four main modules: Diagnostic Advisor, Asset Fault Signature (AFS) Database, Remaining Useful Life Advisor, and Remaining Useful Life Database. This paper focuses on development of asset fault signatures to assess the health status of generator step-up generators and emergency diesel generators in nuclear power plants. Asset fault signatures describe themore » distinctive features based on technical examinations that can be used to detect a specific fault type. At the most basic level, fault signatures are comprised of an asset type, a fault type, and a set of one or more fault features (symptoms) that are indicative of the specified fault. The AFS Database is populated with asset fault signatures via a content development exercise that is based on the results of intensive technical research and on the knowledge and experience of technical experts. The developed fault signatures capture this knowledge and implement it in a standardized approach, thereby streamlining the diagnostic and prognostic process. This will support the automation of proactive online monitoring techniques in nuclear power plants to diagnose incipient faults, perform proactive maintenance, and estimate the remaining useful life of assets.« less

Prostate cancer in East Asia: evolving trend over the last decade

PubMed Central

Zhu, Yao; Wang, Hong-Kai; Qu, Yuan-Yuan; Ye, Ding-Wei

2015-01-01

Prostate cancer is now becoming an emerging health priority in East Asia. Most of our current knowledge on Prostate cancer has been generated from studies conducted in Western population; however, there is considerable heterogeneity of Prostate cancer between East and West. In this article, we reviewed epidemiologic trends, risk factors, disease characteristics and management of Prostate cancer in East Asian population over the last decade. Growing evidence from East Asia suggests an important role of genetic and environmental risk factors interactions in the carcinogenesis of Prostate cancer. Exposure to westernized diet and life style and improvement in health care in combination contribute substantially to the increasing epidemic in this region. Diagnostic and treatment guidelines in East Asia are largely based on Western knowledge. Although there is a remarkable improvement in the outcome over the last decade, ample evidence suggests an inneglectable difference in diagnostic accuracy, treatment efficacy and adverse events between different populations. The knowledge from western countries should be calibrated in the Asian setting to provide a better race-based treatment approach. In this review, we intend to reveal the evolving trend of Prostate cancer in the last decade, in order to gain evidence to improve Prostate cancer prevention and control in East Asia. PMID:25080928

Binge-eating disorder: emerging treatments for a new diagnosis.

PubMed

Tsappis, Michael; Freizinger, Melissa; Forman, Sara F

2016-08-01

This review provides an update on the new Diagnostic and Statistical Manual (DSM) diagnosis of binge-eating disorder (BED) by presenting diagnostic criteria, associated risk factors and co-morbidities, and tools for assessment. An update on the currently available evidence-based treatments for adolescent BED is provided to help with the coordination of treatment planning for identified patients with this condition. BED is now officially included in the DSM. Research with youth has begun to show improvement from treatments such as cognitive behavioral therapy, previously shown to be useful in adults. BED is common and often begins during youth. The availability of diagnostic criteria, along with increasing knowledge about the condition and available treatments, is expected to result in improved identification and management in younger patients.

The role of nurses/social workers in using a multidimensional guideline for diagnosis of anxiety and challenging behaviour in people with intellectual disabilities.

PubMed

Pruijssers, Addy; van Meijel, Berno; Maaskant, Marian; Keeman, Noortje; Teerenstra, Steven; van Achterberg, Theo

2015-07-01

This study seeks (1) to investigate the impact of the implementation of the 'Diagnostic Guideline for Anxiety and challenging behaviours in clients with intellectual disability' on nurses/social workers' knowledge and self-efficacy; and (2) to evaluate the role of nurses/social workers in the diagnostic process when applying the guideline. Nurses/social workers have extensive contact with clients with intellectual disabilities. Despite this key position, the contribution of nurses/social workers to the diagnosis of mental health problems and challenging behaviours is rather limited. The authors developed the multidimensional 'Diagnostic Guideline for Anxiety and challenging behaviours'. In this article, the implementation of this guideline is evaluated concerning knowledge and self-efficacy of nurses/social workers, as well the role of nurses/social workers in the diagnostic process. This study employed a comparative multiple case study design. Qualitative and quantitative research methods. Working with the 'Diagnostic Guideline for Anxiety and challenging behaviours' led to a statistically significant increase in knowledge and self-efficacy among the nurses/social workers in the experimental condition, compared with nurses/social workers in the control condition. Nurses/social workers and psychologists appreciated the more active contribution of the nurses/social workers in the diagnostic process. Working with the guideline increased the knowledge and self-efficacy of nurses/social workers, and led to more active participation of nurses/social workers in the diagnostic process. After following a training programme, nurses/social workers can effectively contribute to the diagnostic process in clients with anxiety and related challenging behaviours. © 2015 John Wiley & Sons Ltd.

[Educating health workers is key in congenital syphilis elimination in Colombia].

PubMed

Garcés, Juan Pablo; Rubiano, Luisa Consuelo; Orobio, Yenifer; Castaño, Martha; Benavides, Elizabeth; Cruz, Adriana

2017-09-01

Colombia promotes the diagnosis and treatment of gestational syphilis in a single visit using rapid diagnostic tests to prevent mother-to-child transmission. Additionally, integrated health programs pursue the coordinated prevention of mother-to-child transmission of syphilis/HIV. To identify knowledge gaps among health workers in the prevention of mother-to-child transmission of syphilis/HIV and to provide recommendations to support these programs. We conducted a descriptive study based on 306 surveys of health workers in 39 health institutions in the city of Cali. Surveys inquired about planning, management and implementation of services for pregnant women, clinical knowledge of HIV/syphilis rapid diagnostic tests, and prior training. Knowledge deficits in the management of gestational syphilis were detected among the surveyed health workers, including physicians. Rapid tests for syphilis are currently used in clinical laboratories in Cali, however, procedural deficiencies were observed in their use, including quality control assurance. During the two years prior to the survey, training of health workers in the prevention of mother-to-child transmission of syphilis/HIV had been limited. Health workers are interested in identifying and treating gestational syphilis in a single event, in using rapid diagnostic tests and in receiving training. Intensive training targeting health workers, policy/decision makers and academic groups is needed to ensure adequate implementation of new strategies for the prevention of mother-to-child transmission of syphilis/HIV.

On-the-spot lung cancer differential diagnosis by label-free, molecular vibrational imaging and knowledge-based classification

NASA Astrophysics Data System (ADS)

Gao, Liang; Li, Fuhai; Thrall, Michael J.; Yang, Yaliang; Xing, Jiong; Hammoudi, Ahmad A.; Zhao, Hong; Massoud, Yehia; Cagle, Philip T.; Fan, Yubo; Wong, Kelvin K.; Wang, Zhiyong; Wong, Stephen T. C.

2011-09-01

We report the development and application of a knowledge-based coherent anti-Stokes Raman scattering (CARS) microscopy system for label-free imaging, pattern recognition, and classification of cells and tissue structures for differentiating lung cancer from non-neoplastic lung tissues and identifying lung cancer subtypes. A total of 1014 CARS images were acquired from 92 fresh frozen lung tissue samples. The established pathological workup and diagnostic cellular were used as prior knowledge for establishment of a knowledge-based CARS system using a machine learning approach. This system functions to separate normal, non-neoplastic, and subtypes of lung cancer tissues based on extracted quantitative features describing fibrils and cell morphology. The knowledge-based CARS system showed the ability to distinguish lung cancer from normal and non-neoplastic lung tissue with 91% sensitivity and 92% specificity. Small cell carcinomas were distinguished from nonsmall cell carcinomas with 100% sensitivity and specificity. As an adjunct to submitting tissue samples to routine pathology, our novel system recognizes the patterns of fibril and cell morphology, enabling medical practitioners to perform differential diagnosis of lung lesions in mere minutes. The demonstration of the strategy is also a necessary step toward in vivo point-of-care diagnosis of precancerous and cancerous lung lesions with a fiber-based CARS microendoscope.

Vascular dementia: Diagnostic criteria and supplementary exams. Recommendations of the Scientific Department of Cognitive Neurology and Aging of the Brazilian Academy of Neurology. Part I

PubMed Central

Engelhardt, Eliasz; Tocquer, Carla; André, Charles; Moreira, Denise Madeira; Okamoto, Ivan Hideyo; Cavalcanti, José Luiz de Sá

2011-01-01

Vascular dementia (VaD) is the most prevalent form of secondary dementia and the second most common of all dementias. The present paper aims to define guidelines on the basic principles for treating patients with suspected VaD (and vascular cognitive impairment - no dementia) using an evidence-based, systematized approach. The knowledge used to define these guidelines was retrieved from searches of several databases (Medline, Scielo, Lilacs) containing scientific articles, systematic reviews, meta-analyses, largely published within the last 15 years or earlier when pertinent. Information retrieved and selected for relevance was used to analyze diagnostic criteria and to propose a diagnostic system encompassing diagnostic criteria, anamnesis, as well as supplementary and clinical exams (neuroimaging and laboratory). Wherever possible, instruments were selected that had versions previously adapted and validated for use in Brazil that take into account both schooling and age. This task led to proposed protocols for supplementary exams based on degree of priority, for application in clinical practice and research settings. PMID:29213752

RDF SKETCH MAPS - KNOWLEDGE COMPLEXITY REDUCTION FOR PRECISION MEDICINE ANALYTICS.

PubMed

Thanintorn, Nattapon; Wang, Juexin; Ersoy, Ilker; Al-Taie, Zainab; Jiang, Yuexu; Wang, Duolin; Verma, Megha; Joshi, Trupti; Hammer, Richard; Xu, Dong; Shin, Dmitriy

2016-01-01

Realization of precision medicine ideas requires significant research effort to be able to spot subtle differences in complex diseases at the molecular level to develop personalized therapies. It is especially important in many cases of highly heterogeneous cancers. Precision diagnostics and therapeutics of such diseases demands interrogation of vast amounts of biological knowledge coupled with novel analytic methodologies. For instance, pathway-based approaches can shed light on the way tumorigenesis takes place in individual patient cases and pinpoint to novel drug targets. However, comprehensive analysis of hundreds of pathways and thousands of genes creates a combinatorial explosion, that is challenging for medical practitioners to handle at the point of care. Here we extend our previous work on mapping clinical omics data to curated Resource Description Framework (RDF) knowledge bases to derive influence diagrams of interrelationships of biomarker proteins, diseases and signal transduction pathways for personalized theranostics. We present RDF Sketch Maps - a computational method to reduce knowledge complexity for precision medicine analytics. The method of RDF Sketch Maps is inspired by the way a sketch artist conveys only important visual information and discards other unnecessary details. In our case, we compute and retain only so-called RDF Edges - places with highly important diagnostic and therapeutic information. To do this we utilize 35 maps of human signal transduction pathways by transforming 300 KEGG maps into highly processable RDF knowledge base. We have demonstrated potential clinical utility of RDF Sketch Maps in hematopoietic cancers, including analysis of pathways associated with Hairy Cell Leukemia (HCL) and Chronic Myeloid Leukemia (CML) where we achieved up to 20-fold reduction in the number of biological entities to be analyzed, while retaining most likely important entities. In experiments with pathways associated with HCL a generated RDF Sketch Map of the top 30% paths retained important information about signaling cascades leading to activation of proto-oncogene BRAF, which is usually associated with a different cancer, melanoma. Recent reports of successful treatments of HCL patients by the BRAF-targeted drug vemurafenib support the validity of the RDF Sketch Maps findings. We therefore believe that RDF Sketch Maps will be invaluable for hypothesis generation for precision diagnostics and therapeutics as well as drug repurposing studies.

Diagnosis by integrating model-based reasoning with knowledge-based reasoning

NASA Technical Reports Server (NTRS)

Bylander, Tom

1988-01-01

Our research investigates how observations can be categorized by integrating a qualitative physical model with experiential knowledge. Our domain is diagnosis of pathologic gait in humans, in which the observations are the gait motions, muscle activity during gait, and physical exam data, and the diagnostic hypotheses are the potential muscle weaknesses, muscle mistimings, and joint restrictions. Patients with underlying neurological disorders typically have several malfunctions. Among the problems that need to be faced are: the ambiguity of the observations, the ambiguity of the qualitative physical model, correspondence of the observations and hypotheses to the qualitative physical model, the inherent uncertainty of experiential knowledge, and the combinatorics involved in forming composite hypotheses. Our system divides the work so that the knowledge-based reasoning suggests which hypotheses appear more likely than others, the qualitative physical model is used to determine which hypotheses explain which observations, and another process combines these functionalities to construct a composite hypothesis based on explanatory power and plausibility. We speculate that the reasoning architecture of our system is generally applicable to complex domains in which a less-than-perfect physical model and less-than-perfect experiential knowledge need to be combined to perform diagnosis.

The Galileo PPS expert monitoring and diagnostic prototype

NASA Technical Reports Server (NTRS)

Bahrami, Khosrow

1989-01-01

The Galileo PPS Expert Monitoring Module (EMM) is a prototype system implemented on the SUN workstation that will demonstrate a knowledge-based approach to monitoring and diagnosis for the Galileo spacecraft Power/Pyro subsystems. The prototype will simulate an analysis module functioning within the SFOC Engineering Analysis Subsystem Environment (EASE). This document describes the implementation of a prototype EMM for the Galileo spacecraft Power Pyro Subsystem. Section 2 of this document provides an overview of the issues in monitoring and diagnosis and comparison between traditional and knowledge-based solutions to this problem. Section 3 describes various tradeoffs which must be considered when designing a knowledge-based approach to monitoring and diagnosis, and section 4 discusses how these issues were resolved in constructing the prototype. Section 5 presents conclusions and recommendations for constructing a full-scale demonstration of the EMM. A Glossary provides definitions of terms used in this text.

A knowledge-based, concept-oriented view generation system for clinical data.

PubMed

Zeng, Q; Cimino, J J

2001-04-01

Information overload is a well-known problem for clinicians who must review large amounts of data in patient records. Concept-oriented views, which organize patient data around clinical concepts such as diagnostic strategies and therapeutic goals, may offer a solution to the problem of information overload. However, although concept-oriented views are desirable, they are difficult to create and maintain. We have developed a general-purpose, knowledge-based approach to the generation of concept-oriented views and have developed a system to test our approach. The system creates concept-oriented views through automated identification of relevant patient data. The knowledge in the system is represented by both a semantic network and rules. The key relevant data identification function is accomplished by a rule-based traversal of the semantic network. This paper focuses on the design and implementation of the system; an evaluation of the system is reported separately.

[Medical expert systems and clinical needs].

PubMed

Buscher, H P

1991-10-18

The rapid expansion of computer-based systems for problem solving or decision making in medicine, the so-called medical expert systems, emphasize the need for reappraisal of their indication and value. Where specialist knowledge is required, in particular where medical decisions are susceptible to error these systems will probably serve as a valuable support. In the near future computer-based systems should be able to aid the interpretation of findings of technical investigations and the control of treatment, especially where rapid reactions are necessary despite the need of complex analysis of investigated parameters. In the distant future complete support of diagnostic procedures from the history to final diagnosis is possible. It promises to be particularly attractive for the diagnosis of seldom diseases, for difficult differential diagnoses, and in the decision making in the case of expensive, risky or new diagnostic or therapeutic methods. The physician needs to be aware of certain dangers, ranging from misleading information up to abuse. Patient information depends often on subjective reports and error-prone observations. Although basing on problematic knowledge computer-born decisions may have an imperative effect on medical decision making. Also it must be born in mind that medical decisions should always combine the rational with a consideration of human motives.

Use of an Online Education Platform to Enhance Patients' Knowledge About Radiation in Diagnostic Imaging.

PubMed

Steele, Joseph R; Jones, A Kyle; Clarke, Ryan K; Shiao, Sue J; Wei, Wei; Shoemaker, Stowe; Parmar, Simrit

2017-03-01

The aim of this study was to compare the impact of a digital interactive education platform and standard paper-based education on patients' knowledge regarding ionizing radiation. Beginning in January 2015, patients at a tertiary cancer center scheduled for diagnostic imaging procedures were randomized to receive information about ionizing radiation delivered through a web-based interactive education platform (interactive education group), the same information in document format (document education group), or no specialized education (control group). Patients who completed at least some education and control group patients were invited to complete a knowledge assessment; interactive education patients were invited to provide feedback about satisfaction with their experience. A total of 2,226 patients participated. Surveys were completed by 302 of 745 patients (40.5%) participating in interactive education, 488 of 993 (49.1%) participating in document education, and 363 of 488 (74.4%) in the control group. Patients in the interactive education group were significantly more likely to say that they knew the definition of ionizing radiation, outperformed the other groups in identifying which imaging examinations used ionizing radiation, were significantly more likely to identify from a list which imaging modality had the highest radiation dose, and tended to perform better when asked about the tissue effects of radiation in diagnostic imaging, although this difference was not significant. In the interactive education group, 84% of patients were satisfied with the experience, and 79% said that they would recommend the program. Complex information on a highly technical subject with personal implications for patients may be conveyed more effectively using electronic platforms, and this approach is well accepted. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

"Something Is Wrong with My Child": A Phenomenological Account of a Search for a Diagnosis.

ERIC Educational Resources Information Center

Ahern, Kathy

2000-01-01

Notes children with movement difficulties do not receive neat diagnostic classification, as they have normal intelligence and minimal neurological signs. Details a study based on interviews of 11 parents of children with movement difficulties that revealed that parent involvement and knowledge is critical to acquiring professional attention.…

Using Task Clarification, Checklists and Performance Feedback To Improve the Appearance of a Grocery Store.

ERIC Educational Resources Information Center

Shier, Leslie; Rae, Christen; Austin, John

2003-01-01

An intervention package of task clarification, checklists, and posted performance feedback was developed to increase completion of tasks contributing to the appearance of a local grocery store. The package was based on an informal diagnostic assessment that examined antecedents, equipment and processes, knowledge and skills, and consequences in…

Learning a Health Knowledge Graph from Electronic Medical Records.

PubMed

Rotmensch, Maya; Halpern, Yoni; Tlimat, Abdulhakim; Horng, Steven; Sontag, David

2017-07-20

Demand for clinical decision support systems in medicine and self-diagnostic symptom checkers has substantially increased in recent years. Existing platforms rely on knowledge bases manually compiled through a labor-intensive process or automatically derived using simple pairwise statistics. This study explored an automated process to learn high quality knowledge bases linking diseases and symptoms directly from electronic medical records. Medical concepts were extracted from 273,174 de-identified patient records and maximum likelihood estimation of three probabilistic models was used to automatically construct knowledge graphs: logistic regression, naive Bayes classifier and a Bayesian network using noisy OR gates. A graph of disease-symptom relationships was elicited from the learned parameters and the constructed knowledge graphs were evaluated and validated, with permission, against Google's manually-constructed knowledge graph and against expert physician opinions. Our study shows that direct and automated construction of high quality health knowledge graphs from medical records using rudimentary concept extraction is feasible. The noisy OR model produces a high quality knowledge graph reaching precision of 0.85 for a recall of 0.6 in the clinical evaluation. Noisy OR significantly outperforms all tested models across evaluation frameworks (p < 0.01).

Adaptive control with an expert system based supervisory level. Thesis

NASA Technical Reports Server (NTRS)

Sullivan, Gerald A.

1991-01-01

Adaptive control is presently one of the methods available which may be used to control plants with poorly modelled dynamics or time varying dynamics. Although many variations of adaptive controllers exist, a common characteristic of all adaptive control schemes, is that input/output measurements from the plant are used to adjust a control law in an on-line fashion. Ideally the adjustment mechanism of the adaptive controller is able to learn enough about the dynamics of the plant from input/output measurements to effectively control the plant. In practice, problems such as measurement noise, controller saturation, and incorrect model order, to name a few, may prevent proper adjustment of the controller and poor performance or instability result. In this work we set out to avoid the inadequacies of procedurally implemented safety nets, by introducing a two level control scheme in which an expert system based 'supervisor' at the upper level provides all the safety net functions for an adaptive controller at the lower level. The expert system is based on a shell called IPEX, (Interactive Process EXpert), that we developed specifically for the diagnosis and treatment of dynamic systems. Some of the more important functions that the IPEX system provides are: (1) temporal reasoning; (2) planning of diagnostic activities; and (3) interactive diagnosis. Also, because knowledge and control logic are separate, the incorporation of new diagnostic and treatment knowledge is relatively simple. We note that the flexibility available in the system to express diagnostic and treatment knowledge, allows much greater functionality than could ever be reasonably expected from procedural implementations of safety nets. The remainder of this chapter is divided into three sections. In section 1.1 we give a detailed review of the literature in the area of supervisory systems for adaptive controllers. In particular, we describe the evolution of safety nets from simple ad hoc techniques, up to the use of expert systems for more advanced supervision capabilities.

SSME fault monitoring and diagnosis expert system

NASA Technical Reports Server (NTRS)

Ali, Moonis; Norman, Arnold M.; Gupta, U. K.

1989-01-01

An expert system, called LEADER, has been designed and implemented for automatic learning, detection, identification, verification, and correction of anomalous propulsion system operations in real time. LEADER employs a set of sensors to monitor engine component performance and to detect, identify, and validate abnormalities with respect to varying engine dynamics and behavior. Two diagnostic approaches are adopted in the architecture of LEADER. In the first approach fault diagnosis is performed through learning and identifying engine behavior patterns. LEADER, utilizing this approach, generates few hypotheses about the possible abnormalities. These hypotheses are then validated based on the SSME design and functional knowledge. The second approach directs the processing of engine sensory data and performs reasoning based on the SSME design, functional knowledge, and the deep-level knowledge, i.e., the first principles (physics and mechanics) of SSME subsystems and components. This paper describes LEADER's architecture which integrates a design based reasoning approach with neural network-based fault pattern matching techniques. The fault diagnosis results obtained through the analyses of SSME ground test data are presented and discussed.

The Effect of Self-Explanation of Pathophysiological Mechanisms of Diseases on Medical Students' Diagnostic Performance

ERIC Educational Resources Information Center

Peixoto, José Maria; Mamede, Sílvia; de Faria, Rosa Malena Delbone; Moura, Alexandre Sampaio; Santos, Silvana Maria Elói; Schmidt, Henk G.

2017-01-01

Self-explanation while diagnosing clinical cases fosters medical students' diagnostic performance. In previous studies on self-explanation, students were free to self-explain any aspect of the case, and mostly clinical knowledge was used. Elaboration on knowledge of pathophysiological mechanisms of diseases has been largely unexplored in studies…

Designing Cognitively Diagnostic Assessment for Algebraic Content Knowledge and Thinking Skills

ERIC Educational Resources Information Center

Zhang, Zhidong

2018-01-01

This study explored a diagnostic assessment method that emphasized the cognitive process of algebra learning. The study utilized a design and a theory-driven model to examine the content knowledge. Using the theory driven model, the thinking skills of algebra learning was also examined. A Bayesian network model was applied to represent the theory…

Imaging More Imagining less: An Insight into Knowledge, Attitude and Practice Regarding Radiation Risk on Pregnant Women among Dentists of Ghaziabad - A Cross Sectional Study.

PubMed

Prasad, Monika; Gupta, Ritu; Patthi, Basavaraj; Singla, Ashish; Pandita, Venisha; Kumar, Jishnu Krishna; Malhi, Ravneet; Vashishtha, Vaibhav

2016-07-01

The safety of diagnostic imaging during pregnancy is an important aspect for all clinicians. Pregnant women often do not receive proper dental care as the dentists are not aware of low diagnostic radiation doses involved in dental radiation. To assess awareness of radiation risks on pregnant women among dentists of Ghaziabad city. A total of 268 practicing dentists in Ghaziabad were selected for a questionnaire based cross-sectional study. Data consisted of 18 questions which assessed the knowledge, attitude and practice of dental professionals regarding radiation risks on pregnant women. The questionnaire was distributed and collected personally by the principal investigator. Data was analyzed by Mann Whitney U test and chi-square test. The level of significance was set at p ≤ 0.05. The results showed that the dentists who had attended continuing dental education program had increased level of knowledge regarding radiation effects among pregnant women as compared to the dentists who had not attended continuing dental education programs (p<0.05). Among them who had attended continuing dental education programs 93.3% were aware of the safe dose of radiation and 62% were aware of threshold radiation doses of pregnancy termination. On the contrary there was no significant difference in the knowledge, attitude and practice scores regarding radiation risks on pregnant women based on their academic qualification (p≥0.05). The level of knowledge among dentists was found to be satisfactory, this outcome shows that continuing dental education regarding radiation protection principles and its risks on pregnant women is required to ensure maximum safety both for clinician as well as pregnant women.

Integrated diagnostics

NASA Technical Reports Server (NTRS)

Hunthausen, Roger J.

1988-01-01

Recently completed projects in which advanced diagnostic concepts were explored and/or demonstrated are summarized. The projects begin with the design of integrated diagnostics for the Army's new gas turbine engines, and advance to the application of integrated diagnostics to other aircraft subsystems. Finally, a recent project is discussed which ties together subsystem fault monitoring and diagnostics with a more complete picture of flight domain knowledge.

Company Profile: Selventa, Inc.

PubMed

Fryburg, David A; Latino, Louis J; Tagliamonte, John; Kenney, Renee D; Song, Diane H; Levine, Arnold J; de Graaf, David

2012-08-01

Selventa, Inc. (MA, USA) is a biomarker discovery company that enables personalized healthcare. Originally founded as Genstruct, Inc., Selventa has undergone significant evolution from a technology-based service provider to an active partner in the development of diagnostic tests, functioning as a molecular dashboard of disease activity using a unique platform. As part of that evolution, approximately 2 years ago the company was rebranded as Selventa to reflect its new identity and mission. The contributions to biomedical research by Selventa are based on in silico, reverse-engineering methods to determine biological causality. That is, given a set of in vitro or in vivo biological observations, which biological mechanisms can explain the measured results? Facilitated by a large and carefully curated knowledge base, these in silico methods generated new insights into the mechanisms driving a disease. As Selventa's methods would enable biomarker discovery and be directly applicable to generating novel diagnostics, the scientists at Selventa have focused on the development of predictive biomarkers of response in autoimmune and oncologic diseases. Selventa is presently building a portfolio of independent, as well as partnered, biomarker projects with the intention to create diagnostic tests that predict response to therapy.

Tracking reflective practice-based learning by medical students during an ambulatory clerkship.

PubMed

Thomas, Patricia A; Goldberg, Harry

2007-11-01

To explore the use of web and palm digital assistant (PDA)-based patient logs to facilitate reflective learning in an ambulatory medicine clerkship. Thematic analysis of convenience sample of three successive rotations of medical students' patient log entries. Johns Hopkins University School of Medicine. MS3 and MS4 students rotating through a required block ambulatory medicine clerkship. Students are required to enter patient encounters into a web-based log system during the clerkship. Patient-linked entries included an open text field entitled, "Learning Need." Students were encouraged to use this field to enter goals for future study or teaching points related to the encounter. The logs of 59 students were examined. These students entered 3,051 patient encounters, and 51 students entered 1,347 learning need entries (44.1% of encounters). The use of the "Learning Need" field was not correlated with MS year, gender or end-of-clerkship knowledge test performance. There were strong correlations between the use of diagnostic thinking comments and observations of therapeutic relationships (Pearson's r=.42, p<0.001), and between diagnostic thinking and primary interpretation skills (Pearson's r=.60, p<0.001), but not between diagnostic thinking and factual knowledge (Pearson's r =.10, p=.46). We found that when clerkship students were cued to reflect on each patient encounter with the electronic log system, student entries grouped into categories that suggested different levels of reflective thinking. Future efforts should explore the use of such entries to encourage and track habits of reflective practice in the clinical curriculum.

Accessing and integrating data and knowledge for biomedical research.

PubMed

Burgun, A; Bodenreider, O

2008-01-01

To review the issues that have arisen with the advent of translational research in terms of integration of data and knowledge, and survey current efforts to address these issues. Using examples form the biomedical literature, we identified new trends in biomedical research and their impact on bioinformatics. We analyzed the requirements for effective knowledge repositories and studied issues in the integration of biomedical knowledge. New diagnostic and therapeutic approaches based on gene expression patterns have brought about new issues in the statistical analysis of data, and new workflows are needed are needed to support translational research. Interoperable data repositories based on standard annotations, infrastructures and services are needed to support the pooling and meta-analysis of data, as well as their comparison to earlier experiments. High-quality, integrated ontologies and knowledge bases serve as a source of prior knowledge used in combination with traditional data mining techniques and contribute to the development of more effective data analysis strategies. As biomedical research evolves from traditional clinical and biological investigations towards omics sciences and translational research, specific needs have emerged, including integrating data collected in research studies with patient clinical data, linking omics knowledge with medical knowledge, modeling the molecular basis of diseases, and developing tools that support in-depth analysis of research data. As such, translational research illustrates the need to bridge the gap between bioinformatics and medical informatics, and opens new avenues for biomedical informatics research.

Enhancing Pre-Service Elementary Teachers' Conceptual Understanding of Solution Chemistry with Conceptual Change Text

ERIC Educational Resources Information Center

Calik, Muammer; Ayas, Alipasa; Coll, Richard Kevin

2007-01-01

This paper reports on the use of a constructivist-based pedagogy to enhance understanding of some features of solution chemistry. Pre-service science teacher trainees' prior knowledge about the dissolution of salts and sugar in water were elicited by the use of a simple diagnostic tool. The test revealed widespread alternative conceptions. These…

Avian cardiology.

PubMed

Strunk, Anneliese; Wilson, G Heather

2003-01-01

The field of avian cardiology is continually expanding. Although a great deal of the current knowledge base has been derived from poultry data, research and clinical reports involving companion avian species have been published. This article will present avian cardiovascular anatomy and physiology, history and physical examination considerations in the avian cardiac disease patient, specific diagnostic tools, cardiovascular disease processes, and current therapeutic modalities.

49 CFR Appendix F to Part 222 - Diagnostic Team Considerations

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 4 2011-10-01 2011-10-01 false Diagnostic Team Considerations F Appendix F to.... 222, App. F Appendix F to Part 222—Diagnostic Team Considerations For purposes of this part, a diagnostic team is a group of knowledgeable representatives of parties of interest in a highway-rail grade...

49 CFR Appendix F to Part 222 - Diagnostic Team Considerations

Code of Federal Regulations, 2014 CFR

2014-10-01

... 49 Transportation 4 2014-10-01 2014-10-01 false Diagnostic Team Considerations F Appendix F to.... 222, App. F Appendix F to Part 222—Diagnostic Team Considerations For purposes of this part, a diagnostic team is a group of knowledgeable representatives of parties of interest in a highway-rail grade...

49 CFR Appendix F to Part 222 - Diagnostic Team Considerations

Code of Federal Regulations, 2013 CFR

2013-10-01

... 49 Transportation 4 2013-10-01 2013-10-01 false Diagnostic Team Considerations F Appendix F to.... 222, App. F Appendix F to Part 222—Diagnostic Team Considerations For purposes of this part, a diagnostic team is a group of knowledgeable representatives of parties of interest in a highway-rail grade...

49 CFR Appendix F to Part 222 - Diagnostic Team Considerations

Code of Federal Regulations, 2012 CFR

2012-10-01

... 49 Transportation 4 2012-10-01 2012-10-01 false Diagnostic Team Considerations F Appendix F to.... 222, App. F Appendix F to Part 222—Diagnostic Team Considerations For purposes of this part, a diagnostic team is a group of knowledgeable representatives of parties of interest in a highway-rail grade...

49 CFR Appendix F to Part 222 - Diagnostic Team Considerations

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 4 2010-10-01 2010-10-01 false Diagnostic Team Considerations F Appendix F to.... 222, App. F Appendix F to Part 222—Diagnostic Team Considerations For purposes of this part, a diagnostic team is a group of knowledgeable representatives of parties of interest in a highway-rail grade...

Optimizing biomedical science learning in a veterinary curriculum: a review.

PubMed

Warren, Amy L; Donnon, Tyrone

2013-01-01

As veterinary medical curricula evolve, the time dedicated to biomedical science teaching, as well as the role of biomedical science knowledge in veterinary education, has been scrutinized. Aside from being mandated by accrediting bodies, biomedical science knowledge plays an important role in developing clinical, diagnostic, and therapeutic reasoning skills in the application of clinical skills, in supporting evidence-based veterinary practice and life-long learning, and in advancing biomedical knowledge and comparative medicine. With an increasing volume and fast pace of change in biomedical knowledge, as well as increased demands on curricular time, there has been pressure to make biomedical science education efficient and relevant for veterinary medicine. This has lead to a shift in biomedical education from fact-based, teacher-centered and discipline-based teaching to applicable, student-centered, integrated teaching. This movement is supported by adult learning theories and is thought to enhance students' transference of biomedical science into their clinical practice. The importance of biomedical science in veterinary education and the theories of biomedical science learning will be discussed in this article. In addition, we will explore current advances in biomedical teaching methodologies that are aimed to maximize knowledge retention and application for clinical veterinary training and practice.

Evaluating a Web-Based Educational Module on Oral Cancer Examination Based on a Behavioral Framework.

PubMed

Wee, Alvin G; Zimmerman, Lani M; Pullen, Carol H; Allen, Carl M; Lambert, Paul M; Paskett, Electra D

2016-03-01

Patients at risk of developing oral and/or oropharyngeal cancer (OPC) are more likely to see primary care providers (PCPs) than a dentist. Many PCPs do not regularly perform oral cancer examination (OCE). The purpose of this study was to design a web-based educational program based on a behavioral framework to encourage PCPs to conduct OCE. PCPs were solicited to provide feedback on the program and to evaluate their short-term knowledge. The integrated behavioral model was used to design the program. Fifteen PCPs (five in each group: physicians, physician assistants, and nurse practitioners) reviewed the program and took a posttest: (1) index of knowledge of risk factors for oral cancer (RiskOC) and (2) index of knowledge of diagnostic procedures for oral cancer (DiagOC). Findings from the process evaluation were mainly positive, with comments on the length of the program comprising the ten negative comments. No significant difference among groups of PCPs (physicians, physician assistants, and nurse practitioners) was detected for DiagOC (p = 0.43) or RiskOC (p = 0.201). A program on OPC for PCPs should be less than 40 min. Postviewing knowledge outcomes were similar for all PCPs. The web-based program on OPC based on a behavioral framework could have similar short-term knowledge outcomes for all PCPs and may increase the number of PCPs performing OCEs.

Diagnosis: Reasoning from first principles and experiential knowledge

NASA Technical Reports Server (NTRS)

Williams, Linda J. F.; Lawler, Dennis G.

1987-01-01

Completeness, efficiency and autonomy are requirements for suture diagnostic reasoning systems. Methods for automating diagnostic reasoning systems include diagnosis from first principles (i.e., reasoning from a thorough description of structure and behavior) and diagnosis from experiential knowledge (i.e., reasoning from a set of examples obtained from experts). However, implementation of either as a single reasoning method fails to meet these requirements. The approach of combining reasoning from first principles and reasoning from experiential knowledge does address the requirements discussed above and can possibly ease some of the difficulties associated with knowledge acquisition by allowing developers to systematically enumerate a portion of the knowledge necessary to build the diagnosis program. The ability to enumerate knowledge systematically facilitates defining the program's scope, completeness, and competence and assists in bounding, controlling, and guiding the knowledge acquisition process.

Evaluating College Students' Conceptual Knowledge of Modern Physics: Test of Understanding on Concepts of Modern Physics (TUCO-MP)

ERIC Educational Resources Information Center

Akarsu, Bayram

2011-01-01

In present paper, we propose a new diagnostic test to measure students' conceptual knowledge of principles of modern physics topics. Over few decades since born of physics education research (PER), many diagnostic instruments that measure students' conceptual understanding of various topics in physics, the earliest tests developed in PER are Force…

Numerical calculation of charge exchange cross sections for plasma diagnostics

NASA Astrophysics Data System (ADS)

Mendez, Luis

2016-09-01

The diagnostics of impurity density and temperature in the plasma core in tokamak plasmas is carried out by applying the charge exchange recombination spectroscopy (CXRS) technique, where a fast beam of H atoms collides with the plasma particles leading to electron capture reactions with the impurity ions. The diagnostics is based on the emission of the excited ions formed in the electron capture. The application of the CXRS requires the knowledge of accurate state-selective cross sections, which in general are not accessible experimentally, and the calculation of cross sections for the high n capture levels, required for the diagnostics in the intermediate energy domain of the probe beam, is particularly difficult. In this work, we present a lattice numerical method to solve the time dependent Schrödinger equation. The method is based on the GridTDSE package, it is applicable in the wide energy range 1 - 500 keV/u and can be used to assess the accuracy of previous calculations. The application of the method will be illustrated with calculations for collisions of multiply charged ions with H. Work partially supported by project ENE2014-52432-R (Secretaria de Estado de I+D+i, Spain).

Phytophthora database 2.0: update and future direction.

PubMed

Park, Bongsoo; Martin, Frank; Geiser, David M; Kim, Hye-Seon; Mansfield, Michele A; Nikolaeva, Ekaterina; Park, Sook-Young; Coffey, Michael D; Russo, Joseph; Kim, Seong H; Balci, Yilmaz; Abad, Gloria; Burgess, Treena; Grünwald, Niklaus J; Cheong, Kyeongchae; Choi, Jaeyoung; Lee, Yong-Hwan; Kang, Seogchan

2013-12-01

The online community resource Phytophthora database (PD) was developed to support accurate and rapid identification of Phytophthora and to help characterize and catalog the diversity and evolutionary relationships within the genus. Since its release in 2008, the sequence database has grown to cover 1 to 12 loci for ≈2,600 isolates (representing 138 described and provisional species). Sequences of multiple mitochondrial loci were added to complement nuclear loci-based phylogenetic analyses and diagnostic tool development. Key characteristics of most newly described and provisional species have been summarized. Other additions to improve the PD functionality include: (i) geographic information system tools that enable users to visualize the geographic origins of chosen isolates on a global-scale map, (ii) a tool for comparing genetic similarity between isolates via microsatellite markers to support population genetic studies, (iii) a comprehensive review of molecular diagnostics tools and relevant references, (iv) sequence alignments used to develop polymerase chain reaction-based diagnostics tools to support their utilization and new diagnostic tool development, and (v) an online community forum for sharing and preserving experience and knowledge accumulated in the global Phytophthora community. Here we present how these improvements can support users and discuss the PD's future direction.

CRI planning and scheduling for space

NASA Technical Reports Server (NTRS)

Aarup, Mads

1994-01-01

Computer Resources International (CRI) has many years of experience in developing space planning and scheduling systems for the European Space Agency. Activities range from AIT/AIV planning over mission planning to research in on-board autonomy using advanced planning and scheduling technologies in conjunction with model based diagnostics. This article presents four projects carried out for ESA by CRI with various subcontractors: (1) DI, Distributed Intelligence for Ground/Space Systems is an on-going research project; (2) GMPT, Generic Mission Planning Toolset, a feasibility study concluded in 1993; (3) OPTIMUM-AIV, Open Planning Tool for AIV, development of a knowledge based AIV planning and scheduling tool ended in 1992; and (4) PlanERS-1, development of an AI and knowledge-based mission planning prototype for the ERS-1 earth observation spacecraft ended in 1991.

The hallmarks of breast cancer by Raman spectroscopy

NASA Astrophysics Data System (ADS)

Abramczyk, H.; Surmacki, J.; Brożek-Płuska, B.; Morawiec, Z.; Tazbir, M.

2009-04-01

This paper presents new biological results on ex vivo breast tissue based on Raman spectroscopy and demonstrates its power as diagnostic tool with the key advantage in breast cancer research. The results presented here demonstrate the ability of Raman spectroscopy to accurately characterize cancer tissue and distinguish between normal, malignant and benign types. The goal of the paper is to develop the diagnostic ability of Raman spectroscopy in order to find an optical marker of cancer in the breast tissue. Applications of Raman spectroscopy in breast cancer research are in the early stages of development in the world. To the best of our knowledge, this paper is one of the most statistically reliable reports (1100 spectra, 99 patients) on Raman spectroscopy-based diagnosis of breast cancers among the world women population.

Converting Radiology Operations in a Six-Hospital Healthcare System from Film-Based to Digital: Another Leadership Role for the Diagnostic Medical Physicist

NASA Astrophysics Data System (ADS)

Arreola, Manuel M.; Rill, Lynn N.

2004-09-01

As medical facilities across the United States continue to convert their radiology operations from film-based to digital environments, partially accomplished and failed endeavors are frequent because of the lack of competent and knowledgeable leadership. The diagnostic medical physicist is, without a doubt, in a privileged position to take such a leadership role, not only because of her/his understanding of the basics principles of new imaging modalities, but also because of her/his inherent participation in workflow design and educational/training activities. A well-structured approach by the physicist will certainly lead the project to a successful completion, opening, in turn, new opportunities for the medical physicist to become an active participant in the decision-making process for an institution.

Experimental Evaluation of a Structure-Based Connectionist Network for Fault Diagnosis of Helicopter Gearboxes

NASA Technical Reports Server (NTRS)

Jammu, V. B.; Danai, K.; Lewicki, D. G.

1998-01-01

This paper presents the experimental evaluation of the Structure-Based Connectionist Network (SBCN) fault diagnostic system introduced in the preceding article. For this vibration data from two different helicopter gearboxes: OH-58A and S-61, are used. A salient feature of SBCN is its reliance on the knowledge of the gearbox structure and the type of features obtained from processed vibration signals as a substitute to training. To formulate this knowledge, approximate vibration transfer models are developed for the two gearboxes and utilized to derive the connection weights representing the influence of component faults on vibration features. The validity of the structural influences is evaluated by comparing them with those obtained from experimental RMS values. These influences are also evaluated ba comparing them with the weights of a connectionist network trained though supervised learning. The results indicate general agreement between the modeled and experimentally obtained influences. The vibration data from the two gearboxes are also used to evaluate the performance of SBCN in fault diagnosis. The diagnostic results indicate that the SBCN is effective in directing the presence of faults and isolating them within gearbox subsystems based on structural influences, but its performance is not as good in isolating faulty components, mainly due to lack of appropriate vibration features.

Qualitative Facets of Prospective Elementary Teachers' Diagnostic Proceeding: Collecting and Interpreting in One-on-One Interviews

ERIC Educational Resources Information Center

Reinhold, Simone

2015-01-01

The research presented in this paper focuses on the cognitive diagnostic strategies that prospective elementary mathematics teachers (PTs) use in their reflections of one-on-one diagnostic interviews with children in grade one. Thereby, it responds to the detected lack of knowledge regarding qualitative facets of diagnostic proceeding in interview…

In vivo study of the effectiveness of quantitative percussion diagnostics as an indicator of the level of the structural pathology of teeth.

PubMed

Sheets, Cherilyn G; Wu, Jean C; Rashad, Samer; Phelan, Michael; Earthman, James C

2016-08-01

Conventional dental diagnostic aids based upon imagery and patient symptoms are at best only partially effective for the detection of fine structural defects such as cracks in teeth. The purpose of this clinical study was to determine whether quantitative percussion diagnostics (QPD) provided knowledge of the structural instability of teeth before restorative work begins. QPD is a mechanics-based methodology that tests the structural integrity of teeth noninvasively. Eight human participants with 60 sites needing restoration were enrolled in an institutional review board-approved clinical study. Comprehensive examinations were performed in each human participant, including QPD testing. Each site was disassembled and microscopically video documented, and the results were recorded on a defect assessment sheet. Each restored site was then tested using QPD. The normal fit error (NFE), which corresponds to the localized defect severity, was correlated with any pretreatment structural pathology. QPD agreed with clinical disassembly in 55 of 60 comparisons (92% agreement). Moreover, the method achieved 98% specificity and 100% sensitivity for detecting structural pathologies found later upon clinical disassembly. Overall, the NFE was found to be highly predictive of advanced structural pathology. The data from the present in vivo study support the hypothesis that QPD can provide the clinician with advance knowledge of the structural instability of teeth before restorative work begins. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Tracking of multimodal therapeutic nanocomplexes targeting breast cancer in vivo.

PubMed

Bardhan, Rizia; Chen, Wenxue; Bartels, Marc; Perez-Torres, Carlos; Botero, Maria F; McAninch, Robin Ward; Contreras, Alejandro; Schiff, Rachel; Pautler, Robia G; Halas, Naomi J; Joshi, Amit

2010-12-08

Nanoparticle-based therapeutics with local delivery and external electromagnetic field modulation holds extraordinary promise for soft-tissue cancers such as breast cancer; however, knowledge of the distribution and fate of nanoparticles in vivo is crucial for clinical translation. Here we demonstrate that multiple diagnostic capabilities can be introduced in photothermal therapeutic nanocomplexes by simultaneously enhancing both near-infrared fluorescence and magnetic resonance imaging (MRI). We track nanocomplexes in vivo, examining the influence of HER2 antibody targeting on nanocomplex distribution over 72 h. This approach provides valuable, detailed information regarding the distribution and fate of complex nanoparticles designed for specific diagnostic and therapeutic functions.

Tracking of Multimodal Therapeutic Nanocomplexes Targeting Breast Cancer in Vivo

PubMed Central

Bardhan, Rizia; Chen, Wenxue; Bartels, Marc; Perez-Torres, Carlos; Botero, Maria F.; McAninch, Robin Ward; Contreras, Alejandro; Schiff, Rachel; Pautler, Robia G.; Halas, Naomi J.; Joshi, Amit

2014-01-01

Nanoparticle-based therapeutics with local delivery and external electromagnetic field modulation holds extraordinary promise for soft-tissue cancers such as breast cancer; however, knowledge of the distribution and fate of nanoparticles in vivo is crucial for clinical translation. Here we demonstrate that multiple diagnostic capabilities can be introduced in photothermal therapeutic nanocomplexes by simultaneously enhancing both near-infrared fluorescence and magnetic resonance imaging (MRI). We track nanocomplexes in vivo, examining the influence of HER2 antibody targeting on nanocomplex distribution over 72 h. This approach provides valuable, detailed information regarding the distribution and fate of complex nanoparticles designed for specific diagnostic and therapeutic functions. PMID:21090693

Betatron radiation based diagnostics for plasma wakefield accelerated electron beams at the SPARC_LAB test facility

NASA Astrophysics Data System (ADS)

Shpakov, V.; Anania, M. P.; Biagioni, A.; Chiadroni, E.; Cianchi, A.; Curcio, A.; Dabagov, S.; Ferrario, M.; Filippi, F.; Marocchino, A.; Paroli, B.; Pompili, R.; Rossi, A. R.; Zigler, A.

2016-09-01

Recent progress with wake-field acceleration has shown a great potential in providing high gradient acceleration fields, while the quality of the beams remains relatively poor. Precise knowledge of the beam size at the exit from the plasma and matching conditions for the externally injected beams are the key for improvement of beam quality. Betatron radiation emitted by the beam during acceleration in the plasma is a powerful tool for the transverse beam size measurement, being also non-intercepting. In this work we report on the technical solutions chosen at SPARC_LAB for such diagnostics tool, along with expected parameters of betatron radiation.

ISACS-DOC: Monitoring and Diagnostic System for AKARI and HINODE

NASA Astrophysics Data System (ADS)

Mizutani, Mitsue; Hirose, Toshinori; Takaki, Ryoji; Honda, Hideyuki

ISACS-DOC (Intelligent Satellite Control Software-DOCtor), which is an automatic monitoring and diagnostic system for scientific satellites or spacecraft, aims to rapidly and accurately capture important changes and sign of anomaly during daily satellite operations. After three systems for deep space missions, the new generation of ISACS-DOC with a higher speed processing performance had been developed for the satellites in earth orbit, AKARI and HINODE. This paper reports on the newest ISACS-DOC about enhanced functions, operating status, and an approach to create standards to build and keep up the knowledge data base. Continuous enhancements through the actual operations are the advantage of ISACS-DOC.

Looking at anything that is green when hearing "frog": how object surface colour and stored object colour knowledge influence language-mediated overt attention.

PubMed

Huettig, Falk; Altmann, Gerry T M

2011-01-01

Three eye-tracking experiments investigated the influence of stored colour knowledge, perceived surface colour, and conceptual category of visual objects on language-mediated overt attention. Participants heard spoken target words whose concepts are associated with a diagnostic colour (e.g., "spinach"; spinach is typically green) while their eye movements were monitored to (a) objects associated with a diagnostic colour but presented in black and white (e.g., a black-and-white line drawing of a frog), (b) objects associated with a diagnostic colour but presented in an appropriate but atypical colour (e.g., a colour photograph of a yellow frog), and (c) objects not associated with a diagnostic colour but presented in the diagnostic colour of the target concept (e.g., a green blouse; blouses are not typically green). We observed that colour-mediated shifts in overt attention are primarily due to the perceived surface attributes of the visual objects rather than stored knowledge about the typical colour of the object. In addition our data reveal that conceptual category information is the primary determinant of overt attention if both conceptual category and surface colour competitors are copresent in the visual environment.

Integration of basic sciences and clinical sciences in oral radiology education for dental students.

PubMed

Baghdady, Mariam T; Carnahan, Heather; Lam, Ernest W N; Woods, Nicole N

2013-06-01

Educational research suggests that cognitive processing in diagnostic radiology requires a solid foundation in the basic sciences and knowledge of the radiological changes associated with disease. Although it is generally assumed that dental students must acquire both sets of knowledge, little is known about the most effective way to teach them. Currently, the basic and clinical sciences are taught separately. This study was conducted to compare the diagnostic accuracy of students when taught basic sciences segregated or integrated with clinical features. Predoctoral dental students (n=51) were taught four confusable intrabony abnormalities using basic science descriptions integrated with the radiographic features or taught segregated from the radiographic features. The students were tested with diagnostic images, and memory tests were performed immediately after learning and one week later. On immediate and delayed testing, participants in the integrated basic science group outperformed those from the segregated group. A main effect of learning condition was found to be significant (p<0.05). The results of this study support the critical role of integrating biomedical knowledge in diagnostic radiology and shows that teaching basic sciences integrated with clinical features produces higher diagnostic accuracy in novices than teaching basic sciences segregated from clinical features.

Does prior domain-specific content knowledge influence students' recall of arguments surrounding interdisciplinary topics?

PubMed

Schmidt, Hiemke K; Rothgangel, Martin; Grube, Dietmar

2017-12-01

Awareness of various arguments can help interactants present opinions, stress points, and build counterarguments during discussions. At school, some topics are taught in a way that students learn to accumulate knowledge and gather arguments, and later employ them during debates. Prior knowledge may facilitate recalling information on well structured, fact-based topics, but does it facilitate recalling arguments during discussions on complex, interdisciplinary topics? We assessed the prior knowledge in domains related to a bioethical topic of 277 students from Germany (approximately 15 years old), their interest in the topic, and their general knowledge. The students read a text with arguments for and against prenatal diagnostics and tried to recall the arguments one week later and again six weeks later. Prior knowledge in various domains related to the topic individually and separately helped students recall the arguments. These relationships were independent of students' interest in the topic and their general knowledge. Copyright © 2017 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Using diagnostic experiences in experience-based innovative design

NASA Astrophysics Data System (ADS)

Prabhakar, Sattiraju; Goel, Ashok K.

1992-03-01

Designing a novel class of devices requires innovation. Often, the design knowledge of these devices does not identify and address the constraints that are required for their performance in the real world operating environment. So any new design adapted from these devices tend to be similarly sketchy. In order to address this problem, we propose a case-based reasoning method called performance driven innovation (PDI). We model the design as a dynamic process, arrive at a design by adaptation from the known designs, generate failures for this design for some new constraints, and then use this failure knowledge to generate the required design knowledge for the new constraints. In this paper, we discuss two aspects of PDI: the representation of PDI cases and the translation of the failure knowledge into design knowledge for a constraint. Each case in PDI has two components: design and failure knowledge. Both of them are represented using a substance-behavior-function model. Failure knowledge has internal device failure behaviors and external environmental behaviors. The environmental behavior, for a constraint, interacting with the design behaviors, results in the failure internal behavior. The failure adaptation strategy generates functions, from the failure knowledge, which can be addressed using the routine design methods. These ideas are illustrated using a coffee-maker example.

Medical knowledge packages and their integration into health-care information systems and the World Wide Web.

PubMed

Adlassnig, Klaus-Peter; Rappelsberger, Andrea

2008-01-01

Software-based medical knowledge packages (MKPs) are packages of highly structured medical knowledge that can be integrated into various health-care information systems or the World Wide Web. They have been established to provide different forms of clinical decision support such as textual interpretation of combinations of laboratory rest results, generating diagnostic hypotheses as well as confirmed and excluded diagnoses to support differential diagnosis in internal medicine, or for early identification and automatic monitoring of hospital-acquired infections. Technically, an MKP may consist of a number of inter-connected Arden Medical Logic Modules. Several MKPs have been integrated thus far into hospital, laboratory, and departmental information systems. This has resulted in useful and widely accepted software-based clinical decision support for the benefit of the patient, the physician, and the organization funding the health care system.

Health-related quality of life, anxiety and depression in the diagnostic phase of suspected cancer, and the influence of diagnosis.

PubMed

Moseholm, Ellen; Rydahl-Hansen, Susan; Overgaard, Dorthe; Wengel, Hanne S; Frederiksen, Rikke; Brandt, Malene; Lindhardt, Bjarne Ø

2016-05-20

Undergoing diagnostic evaluation for cancer has been associated with a high prevalence of anxiety and depression and affected health-related quality of life (HRQoL). The aims of this study were to assess HRQoL, anxiety, and depression pre- and post-diagnosis in patients undergoing diagnostic evaluations for cancer due to non-specific symptoms; to examine changes over time in relation to final diagnosis (cancer yes/no); and to assess the predictive value of pre-diagnostic psychological, socio-demographic and clinical factors. A prospective, multicenter survey study of patients suspected to have cancer based on non-specific symptoms was performed. Participants completed the EORTC-QLQ-C30 quality of life scale, HADS, SOC-13 and self-rated health before and after completing diagnostic evaluations. Intra- and inter-group differences between patients diagnosed with cancer versus patients with non-cancer diagnoses were calculated. The impact of baseline psychological, socio-demographic, and medical factors on HRQoL, anxiety and depression at follow-up was explored by bootstrapped multivariate linear regression analyses and logistic regression analyses. A total of 838 patients participated in this study; 679 (81 %) completed the follow-up. Twenty-two percent of the patients received a cancer diagnosis at the end of the follow-up. Patients presented initially with a high burden of symptoms and affected role and emotional functioning and global health/QL, irrespective of diagnosis. The prevalence of clinical anxiety prior to knowledge of the diagnosis was 32 % in patients with cancer and 35 % in patients who received a non-cancer diagnosis. HRQoL and anxiety improved after diagnosis, and a larger improvement was seen in patients who received a non-cancer diagnosis. There were no intra- or inter-group differences in the depression scores. The strongest predictors of global QL, anxiety, and depression after a known diagnosis were baseline scores, co-morbidity and poor self-rated health. Patients undergoing diagnostic evaluations for cancer based on non-specific symptoms experience a high prevalence of anxiety and affected quality of life prior to knowledge of the diagnosis. The predictive value of the baseline scores is important when assessing the psychological impact of undergoing diagnostic evaluations for cancer.

Diagnosis support system based on clinical guidelines: comparison between case-based fuzzy cognitive maps and Bayesian networks.

PubMed

Douali, Nassim; Csaba, Huszka; De Roo, Jos; Papageorgiou, Elpiniki I; Jaulent, Marie-Christine

2014-01-01

Several studies have described the prevalence and severity of diagnostic errors. Diagnostic errors can arise from cognitive, training, educational and other issues. Examples of cognitive issues include flawed reasoning, incomplete knowledge, faulty information gathering or interpretation, and inappropriate use of decision-making heuristics. We describe a new approach, case-based fuzzy cognitive maps, for medical diagnosis and evaluate it by comparison with Bayesian belief networks. We created a semantic web framework that supports the two reasoning methods. We used database of 174 anonymous patients from several European hospitals: 80 of the patients were female and 94 male with an average age 45±16 (average±stdev). Thirty of the 80 female patients were pregnant. For each patient, signs/symptoms/observables/age/sex were taken into account by the system. We used a statistical approach to compare the two methods. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Effect of patient age awareness on diagnostic agreement of chronic or aggressive periodontitis between clinicians; a pilot study.

PubMed

Oshman, Sarah; El Chaar, Edgard; Lee, Yoonjung Nicole; Engebretson, Steven

2016-07-25

The aim of this pilot study was to test whether diagnostic agreement of aggressive and chronic periodontitis amongst Board Certified Periodontists, is influenced by knowledge of a patient's age. In 1999 at the International World Workshop age was removed as a diagnostic criteria for aggressive periodontitis. The impact of this change on the diagnostic reliability amongst clinicians has not yet been assessed. Nine periodontal case reports were twice presented to sixteen board certified periodontists, once with age withheld and again with patient age provided. Participants were instructed to choose a diagnosis of Chronic Periodontitis or Aggressive Periodontitis. Diagnostic agreement was calculated using the Fleiss Kappa test. Including the patients' age in case report information increased diagnostic agreement (the kappa statistic) from 0.49 (moderate agreement) to 0.61 (substantial agreement). These results suggest that knowledge of a patients' age influenced clinical diagnosis, when distinguishing between aggressive periodontitis and chronic periodontitis, which may in turn impact treatment decision-making.

The researchers' role in knowledge translation: a realist evaluation of the development and implementation of diagnostic pathways for cancer in two United Kingdom localities.

PubMed

Banks, Jon; Wye, Lesley; Hall, Nicola; Rooney, James; Walter, Fiona M; Hamilton, Willie; Gjini, Ardiana; Rubin, Greg

2017-12-13

In examining an initiative to develop and implement new cancer diagnostic pathways in two English localities, this paper evaluates 'what works' and examines the role of researchers in facilitating knowledge translation amongst teams of local clinicians and policy-makers. Using realist evaluation with a mixed methods case study approach, we conducted documentary analysis of meeting minutes and pathway iterations to map pathway development. We interviewed 14 participants to identify the contexts, mechanisms and outcomes (CMOs) that led to successful pathway development and implementation. Interviews were analysed thematically and four CMO configurations were developed. One site produced three fully implemented pathways, while the other produced two that were partly implemented. In explaining the differences, we found that a respected, independent, well-connected leader modelling partnership working and who facilitates a local, stable group that agree about the legitimacy of the data and project (context) can empower local teams to become sufficiently autonomous (mechanism) to develop and implement research-based pathways (outcome). Although both teams designed relevant, research-based cancer pathways, in the site where the pathways were successfully implemented the research team merely assisted, while, in the other, the research team drove the initiative. Based on our study findings, local stakeholders can apply local and research knowledge to develop and implement research-based pathways. However, success will depend on how academics empower local teams to create autonomy. Crucially, after re-packaging and translating research for local circumstances, identifying fertile environments with the right elements for implementation and developing collaborative relationships with local leaders, academics must step back.

Combining principles of Cognitive Load Theory and diagnostic error analysis for designing job aids: Effects on motivation and diagnostic performance in a process control task.

PubMed

Kluge, Annette; Grauel, Britta; Burkolter, Dina

2013-03-01

Two studies are presented in which the design of a procedural aid and the impact of an additional decision aid for process control were assessed. In Study 1, a procedural aid was developed that avoids imposing unnecessary extraneous cognitive load on novices when controlling a complex technical system. This newly designed procedural aid positively affected germane load, attention, satisfaction, motivation, knowledge acquisition and diagnostic speed for novel faults. In Study 2, the effect of a decision aid for use before the procedural aid was investigated, which was developed based on an analysis of diagnostic errors committed in Study 1. Results showed that novices were able to diagnose both novel faults and practised faults, and were even faster at diagnosing novel faults. This research contributes to the question of how to optimally support novices in dealing with technical faults in process control. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Clinical and diagnostic utility of saliva as a non-invasive diagnostic fluid:
a systematic review

PubMed Central

Nunes, Lazaro Alessandro Soares; Mussavira, Sayeeda

2015-01-01

This systematic review presents the latest trends in salivary research and its applications in health and disease. Among the large number of analytes present in saliva, many are affected by diverse physiological and pathological conditions. Further, the non-invasive, easy and cost-effective collection methods prompt an interest in evaluating its diagnostic or prognostic utility. Accumulating data over the past two decades indicates towards the possible utility of saliva to monitor overall health, diagnose and treat various oral or systemic disorders and drug monitoring. Advances in saliva based systems biology has also contributed towards identification of several biomarkers, development of diverse salivary diagnostic kits and other sensitive analytical techniques. However, its utilization should be carefully evaluated in relation to standardization of pre-analytical and analytical variables, such as collection and storage methods, analyte circadian variation, sample recovery, prevention of sample contamination and analytical procedures. In spite of all these challenges, there is an escalating evolution of knowledge with the use of this biological matrix. PMID:26110030

Knowledge Representation Of CT Scans Of The Head

NASA Astrophysics Data System (ADS)

Ackerman, Laurens V.; Burke, M. W.; Rada, Roy

1984-06-01

We have been investigating diagnostic knowledge models which assist in the automatic classification of medical images by combining information extracted from each image with knowledge specific to that class of images. In a more general sense we are trying to integrate verbal and pictorial descriptions of disease via representations of knowledge, study automatic hypothesis generation as related to clinical medicine, evolve new mathematical image measures while integrating them into the total diagnostic process, and investigate ways to augment the knowledge of the physician. Specifically, we have constructed an artificial intelligence knowledge model using the technique of a production system blending pictorial and verbal knowledge about the respective CT scan and patient history. It is an attempt to tie together different sources of knowledge representation, picture feature extraction and hypothesis generation. Our knowledge reasoning and representation system (KRRS) works with data at the conscious reasoning level of the practicing physician while at the visual perceptional level we are building another production system, the picture parameter extractor (PPE). This paper describes KRRS and its relationship to PPE.

Circulating Tumor Cells: What Is in It for the Patient? A Vision towards the Future

PubMed Central

van de Stolpe, Anja; den Toonder, Jaap M. J.

2014-01-01

Knowledge on cellular signal transduction pathways as drivers of cancer growth and metastasis has fuelled development of “targeted therapy” which “targets” aberrant oncogenic signal transduction pathways. These drugs require nearly invariably companion diagnostic tests to identify the tumor-driving pathway and the cause of the abnormal pathway activity in a tumor sample, both for therapy response prediction as well as for monitoring of therapy response and emerging secondary drug resistance. Obtaining sufficient tumor material for this analysis in the metastatic setting is a challenge, and circulating tumor cells (CTCs) may provide an attractive alternative to biopsy on the premise that they can be captured from blood and the companion diagnostic test results are correctly interpreted. We discuss novel companion diagnostic directions, including the challenges, to identify the tumor driving pathway in CTCs, which in combination with a digital pathology platform and algorithms to quantitatively interpret complex CTC diagnostic results may enable optimized therapy response prediction and monitoring. In contrast to CTC-based companion diagnostics, CTC enumeration is envisioned to be largely replaced by cell free tumor DNA measurements in blood for therapy response and recurrence monitoring. The recent emergence of novel in vitro human model systems in the form of cancer-on-a-chip may enable elucidation of some of the so far elusive characteristics of CTCs, and is expected to contribute to more efficient CTC capture and CTC-based diagnostics. PMID:24879438

Digital Tools to Enhance Clinical Reasoning.

PubMed

Manesh, Reza; Dhaliwal, Gurpreet

2018-05-01

Physicians can improve their diagnostic acumen by adopting a simulation-based approach to analyzing published cases. The tight coupling of clinical problems and their solutions affords physicians the opportunity to efficiently upgrade their illness scripts (structured knowledge of a specific disease) and schemas (structured frameworks for common problems). The more times clinicians practice accessing and applying those knowledge structures through published cases, the greater the odds that they will have an enhanced approach to similar patient-cases in the future. This article highlights digital resources that increase the number of cases a clinician experiences and learns from. Copyright © 2017 Elsevier Inc. All rights reserved.

System control module diagnostic Expert Assistant

NASA Technical Reports Server (NTRS)

Flores, Luis M.; Hansen, Roger F.

1990-01-01

The Orbiter EXperiments (OEX) Program was established by NASA's Office of Aeronautics and Space Technology (OAST) to accomplish the precise data collection necessary to support a complete and accurate assessment of Space Transportation System (STS) Orbiter performance during all phases of a mission. During a mission, data generated by the various experiments are conveyed to the OEX System Control Module (SCM) which arranges for and monitors storage of the data on the OEX tape recorder. The SCM Diagnostic Expert Assistant (DEA) is an expert system which provides on demand advice to technicians performing repairs of a malfunctioning SCM. The DEA is a self-contained, data-driven knowledge-based system written in the 'C' Language Production System (CLIPS) for a portable micro-computer of the IBM PC/XT class. The DEA reasons about SCM hardware faults at multiple levels; the most detailed layer of encoded knowledge of the SCM is a representation of individual components and layouts of the custom-designed component boards.

MO-DE-BRA-05: Developing Effective Medical Physics Knowledge Structures: Models and Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sprawls, P

Purpose: Develop a method and supporting online resources to be used by medical physics educators for teaching medical imaging professionals and trainees so they develop highly-effective physics knowledge structures that can contribute to improved diagnostic image quality on a global basis. Methods: The different types of mental knowledge structures were analyzed and modeled with respect to both the learning and teaching process for their development and the functions or tasks that can be performed with the knowledge. While symbolic verbal and mathematical knowledge structures are very important in medical physics for many purposes, the tasks of applying physics in clinicalmore » imaging--especially to optimize image quality and diagnostic accuracy--requires a sensory conceptual knowledge structure, specifically, an interconnected network of visually based concepts. This type of knowledge supports tasks such as analysis, evaluation, problem solving, interacting, and creating solutions. Traditional educational methods including lectures, online modules, and many texts are serial procedures and limited with respect to developing interconnected conceptual networks. A method consisting of the synergistic combination of on-site medical physics teachers and the online resource, CONET (Concept network developer), has been developed and made available for the topic Radiographic Image Quality. This was selected as the inaugural topic, others to follow, because it can be used by medical physicists teaching the large population of medical imaging professionals, such as radiology residents, who can apply the knowledge. Results: Tutorials for medical physics educators on developing effective knowledge structures are being presented and published and CONET is available with open access for all to use. Conclusion: An adjunct to traditional medical physics educational methods with the added focus on sensory concept development provides opportunities for medical physics teachers to share their knowledge and experience at a higher cognitive level and produce medical professionals with the enhanced ability to apply physics to clinical procedures.« less

DSM-5, ICD-10, ICD-11, the Psychodynamic Diagnostic Manual, and Person-Centered Integrative Diagnosis: An Overview for College Mental Health Therapists

ERIC Educational Resources Information Center

Cooper, Stewart E.

2014-01-01

Therapists in the field of college mental health counseling commonly voice an ambivalent orientation towards the utilization of formal psychological diagnostic systems yet often use diagnostic terms. Knowledge of the current and emerging diagnostic systems may contribute to greater syntheses of these differing approaches. This article will first…

Background review for diagnostic test development for Zika virus infection.

PubMed

Charrel, Rémi N; Leparc-Goffart, Isabelle; Pas, Suzan; de Lamballerie, Xavier; Koopmans, Marion; Reusken, Chantal

2016-08-01

To review the state of knowledge about diagnostic testing for Zika virus infection and identify areas of research needed to address the current gaps in knowledge. We made a non-systematic review of the published literature about Zika virus and supplemented this with information from commercial diagnostic test kits and personal communications with researchers in European preparedness networks. The review covered current knowledge about the geographical spread, pathogen characteristics, life cycle and infection kinetics of the virus. The available molecular and serological tests and biosafety issues are described and discussed in the context of the current outbreak strain. We identified the following areas of research to address current knowledge gaps: (i) an urgent assessment of the laboratory capacity and capability of countries to detect Zika virus; (ii) rapid and extensive field validation of the available molecular and serological tests in areas with and without Zika virus transmission, with a focus on pregnant women; (iii) monitoring the genomic diversity of circulating Zika virus strains; (iv) prospective studies into the virus infection kinetics, focusing on diagnostic sampling (specimen types, combinations and timings); and (v) developing external quality assessments for molecular and serological testing, including differential diagnosis for similar viruses and symptom clusters. The availability of reagents for diagnostic development (virus strains and antigens, quantified viral ribonucleic acid) needs to be facilitated. An international laboratory response is needed, including preparation of protocols for prospective studies to address the most pressing information needs.

Background review for diagnostic test development for Zika virus infection

PubMed Central

Charrel, Rémi N; Leparc-Goffart, Isabelle; Pas, Suzan; de Lamballerie, Xavier; Koopmans, Marion; Reusken, Chantal

2016-01-01

Abstract Objective To review the state of knowledge about diagnostic testing for Zika virus infection and identify areas of research needed to address the current gaps in knowledge. Methods We made a non-systematic review of the published literature about Zika virus and supplemented this with information from commercial diagnostic test kits and personal communications with researchers in European preparedness networks. The review covered current knowledge about the geographical spread, pathogen characteristics, life cycle and infection kinetics of the virus. The available molecular and serological tests and biosafety issues are described and discussed in the context of the current outbreak strain. Findings We identified the following areas of research to address current knowledge gaps: (i) an urgent assessment of the laboratory capacity and capability of countries to detect Zika virus; (ii) rapid and extensive field validation of the available molecular and serological tests in areas with and without Zika virus transmission, with a focus on pregnant women; (iii) monitoring the genomic diversity of circulating Zika virus strains; (iv) prospective studies into the virus infection kinetics, focusing on diagnostic sampling (specimen types, combinations and timings); and (v) developing external quality assessments for molecular and serological testing, including differential diagnosis for similar viruses and symptom clusters. The availability of reagents for diagnostic development (virus strains and antigens, quantified viral ribonucleic acid) needs to be facilitated. Conclusion An international laboratory response is needed, including preparation of protocols for prospective studies to address the most pressing information needs. PMID:27516635

Constructing a Pre-Emptive System Based on a Multidimentional Matrix and Autocompletion to Improve Diagnostic Coding in Acute Care Hospitals.

PubMed

Noussa-Yao, Joseph; Heudes, Didier; Escudie, Jean-Baptiste; Degoulet, Patrice

2016-01-01

Short-stay MSO (Medicine, Surgery, Obstetrics) hospitalization activities in public and private hospitals providing public services are funded through charges for the services provided (T2A in French). Coding must be well matched to the severity of the patient's condition, to ensure that appropriate funding is provided to the hospital. We propose the use of an autocompletion process and multidimensional matrix, to help physicians to improve the expression of information and to optimize clinical coding. With this approach, physicians without knowledge of the encoding rules begin from a rough concept, which is gradually refined through semantic proximity and uses information on the associated codes stemming of optimized knowledge bases of diagnosis code.

Accessing and Integrating Data and Knowledge for Biomedical Research

PubMed Central

Burgun, A.; Bodenreider, O.

2008-01-01

Summary Objectives To review the issues that have arisen with the advent of translational research in terms of integration of data and knowledge, and survey current efforts to address these issues. Methods Using examples form the biomedical literature, we identified new trends in biomedical research and their impact on bioinformatics. We analyzed the requirements for effective knowledge repositories and studied issues in the integration of biomedical knowledge. Results New diagnostic and therapeutic approaches based on gene expression patterns have brought about new issues in the statistical analysis of data, and new workflows are needed are needed to support translational research. Interoperable data repositories based on standard annotations, infrastructures and services are needed to support the pooling and meta-analysis of data, as well as their comparison to earlier experiments. High-quality, integrated ontologies and knowledge bases serve as a source of prior knowledge used in combination with traditional data mining techniques and contribute to the development of more effective data analysis strategies. Conclusion As biomedical research evolves from traditional clinical and biological investigations towards omics sciences and translational research, specific needs have emerged, including integrating data collected in research studies with patient clinical data, linking omics knowledge with medical knowledge, modeling the molecular basis of diseases, and developing tools that support in-depth analysis of research data. As such, translational research illustrates the need to bridge the gap between bioinformatics and medical informatics, and opens new avenues for biomedical informatics research. PMID:18660883

The treatable intellectual disability APP www.treatable-id.org: a digital tool to enhance diagnosis & care for rare diseases.

PubMed

van Karnebeek, Clara D M; Houben, Roderick F A; Lafek, Mirafe; Giannasi, Wynona; Stockler, Sylvia

2012-07-23

Intellectual disability (ID) is a devastating and frequent condition, affecting 2-3% of the population worldwide. Early recognition of treatable underlying conditions drastically improves health outcomes and decreases burdens to patients, families and society. Our systematic literature review identified 81 such inborn errors of metabolism, which present with ID as a prominent feature and are amenable to causal therapy. The WebAPP translates this knowledge of rare diseases into a diagnostic tool and information portal. Freely available as a WebAPP via http://www.treatable-id.org and end 2012 via the APP store, this diagnostic tool is designed for all specialists evaluating children with global delay / ID and laboratory scientists. Information on the 81 diseases is presented in different ways with search functions: 15 biochemical categories, neurologic and non-neurologic signs & symptoms, diagnostic investigations (metabolic screening tests in blood and urine identify 65% of all IEM), therapies & effects on primary (IQ/developmental quotient) and secondary outcomes, and available evidence For each rare condition a 'disease page' serves as an information portal with online access to specific genetics, biochemistry, phenotype, diagnostic tests and therapeutic options. As new knowledge and evidence is gained from expert input and PubMed searches this tool will be continually updated. The WebAPP is an integral part of a protocol prioritizing treatability in the work-up of every child with global delay / ID. A 3-year funded study will enable an evaluation of its effectiveness. For rare diseases, a field for which financial and scientific resources are particularly scarce, knowledge translation challenges are abundant. With this WebAPP technology is capitalized to raise awareness for rare treatable diseases and their common presenting clinical feature of ID, with the potential to improve health outcomes. This innovative digital tool is designed to motivate health care providers to search actively for treatable causes of ID, and support an evidence-based approach to rare metabolic diseases. In our current -omics world with continuous information flow, the effective synthesis of data into accessible, clinical knowledge has become ever more essential to bridge the gap between research and care.

The treatable intellectual disability APP www.treatable-id.org: A digital tool to enhance diagnosis & care for rare diseases

PubMed Central

2012-01-01

Background Intellectual disability (ID) is a devastating and frequent condition, affecting 2-3% of the population worldwide. Early recognition of treatable underlying conditions drastically improves health outcomes and decreases burdens to patients, families and society. Our systematic literature review identified 81 such inborn errors of metabolism, which present with ID as a prominent feature and are amenable to causal therapy. The WebAPP translates this knowledge of rare diseases into a diagnostic tool and information portal. Methods & results Freely available as a WebAPP via http://www.treatable-id.org and end 2012 via the APP store, this diagnostic tool is designed for all specialists evaluating children with global delay / ID and laboratory scientists. Information on the 81 diseases is presented in different ways with search functions: 15 biochemical categories, neurologic and non-neurologic signs & symptoms, diagnostic investigations (metabolic screening tests in blood and urine identify 65% of all IEM), therapies & effects on primary (IQ/developmental quotient) and secondary outcomes, and available evidence For each rare condition a ‘disease page’ serves as an information portal with online access to specific genetics, biochemistry, phenotype, diagnostic tests and therapeutic options. As new knowledge and evidence is gained from expert input and PubMed searches this tool will be continually updated. The WebAPP is an integral part of a protocol prioritizing treatability in the work-up of every child with global delay / ID. A 3-year funded study will enable an evaluation of its effectiveness. Conclusions For rare diseases, a field for which financial and scientific resources are particularly scarce, knowledge translation challenges are abundant. With this WebAPP technology is capitalized to raise awareness for rare treatable diseases and their common presenting clinical feature of ID, with the potential to improve health outcomes. This innovative digital tool is designed to motivate health care providers to search actively for treatable causes of ID, and support an evidence-based approach to rare metabolic diseases. In our current –omics world with continuous information flow, the effective synthesis of data into accessible, clinical knowledge has become ever more essential to bridge the gap between research and care. PMID:22824307

Determination of optimal imaging settings for urolithiasis CT using filtered back projection (FBP), statistical iterative reconstruction (IR) and knowledge-based iterative model reconstruction (IMR): a physical human phantom study

PubMed Central

Choi, Se Y; Ahn, Seung H; Choi, Jae D; Kim, Jung H; Lee, Byoung-Il; Kim, Jeong-In

2016-01-01

Objective: The purpose of this study was to compare CT image quality for evaluating urolithiasis using filtered back projection (FBP), statistical iterative reconstruction (IR) and knowledge-based iterative model reconstruction (IMR) according to various scan parameters and radiation doses. Methods: A 5 × 5 × 5 mm3 uric acid stone was placed in a physical human phantom at the level of the pelvis. 3 tube voltages (120, 100 and 80 kV) and 4 current–time products (100, 70, 30 and 15 mAs) were implemented in 12 scans. Each scan was reconstructed with FBP, statistical IR (Levels 5–7) and knowledge-based IMR (soft-tissue Levels 1–3). The radiation dose, objective image quality and signal-to-noise ratio (SNR) were evaluated, and subjective assessments were performed. Results: The effective doses ranged from 0.095 to 2.621 mSv. Knowledge-based IMR showed better objective image noise and SNR than did FBP and statistical IR. The subjective image noise of FBP was worse than that of statistical IR and knowledge-based IMR. The subjective assessment scores deteriorated after a break point of 100 kV and 30 mAs. Conclusion: At the setting of 100 kV and 30 mAs, the radiation dose can be decreased by approximately 84% while keeping the subjective image assessment. Advances in knowledge: Patients with urolithiasis can be evaluated with ultralow-dose non-enhanced CT using a knowledge-based IMR algorithm at a substantially reduced radiation dose with the imaging quality preserved, thereby minimizing the risks of radiation exposure while providing clinically relevant diagnostic benefits for patients. PMID:26577542

Reexamining our bias against heuristics.

PubMed

McLaughlin, Kevin; Eva, Kevin W; Norman, Geoff R

2014-08-01

Using heuristics offers several cognitive advantages, such as increased speed and reduced effort when making decisions, in addition to allowing us to make decision in situations where missing data do not allow for formal reasoning. But the traditional view of heuristics is that they trade accuracy for efficiency. Here the authors discuss sources of bias in the literature implicating the use of heuristics in diagnostic error and highlight the fact that there are also data suggesting that under certain circumstances using heuristics may lead to better decisions that formal analysis. They suggest that diagnostic error is frequently misattributed to the use of heuristics and propose an alternative view whereby content knowledge is the root cause of diagnostic performance and heuristics lie on the causal pathway between knowledge and diagnostic error or success.

Knowledge-driven genomic interactions: an application in ovarian cancer.

PubMed

Kim, Dokyoon; Li, Ruowang; Dudek, Scott M; Frase, Alex T; Pendergrass, Sarah A; Ritchie, Marylyn D

2014-01-01

Effective cancer clinical outcome prediction for understanding of the mechanism of various types of cancer has been pursued using molecular-based data such as gene expression profiles, an approach that has promise for providing better diagnostics and supporting further therapies. However, clinical outcome prediction based on gene expression profiles varies between independent data sets. Further, single-gene expression outcome prediction is limited for cancer evaluation since genes do not act in isolation, but rather interact with other genes in complex signaling or regulatory networks. In addition, since pathways are more likely to co-operate together, it would be desirable to incorporate expert knowledge to combine pathways in a useful and informative manner. Thus, we propose a novel approach for identifying knowledge-driven genomic interactions and applying it to discover models associated with cancer clinical phenotypes using grammatical evolution neural networks (GENN). In order to demonstrate the utility of the proposed approach, an ovarian cancer data from the Cancer Genome Atlas (TCGA) was used for predicting clinical stage as a pilot project. We identified knowledge-driven genomic interactions associated with cancer stage from single knowledge bases such as sources of pathway-pathway interaction, but also knowledge-driven genomic interactions across different sets of knowledge bases such as pathway-protein family interactions by integrating different types of information. Notably, an integration model from different sources of biological knowledge achieved 78.82% balanced accuracy and outperformed the top models with gene expression or single knowledge-based data types alone. Furthermore, the results from the models are more interpretable because they are framed in the context of specific biological pathways or other expert knowledge. The success of the pilot study we have presented herein will allow us to pursue further identification of models predictive of clinical cancer survival and recurrence. Understanding the underlying tumorigenesis and progression in ovarian cancer through the global view of interactions within/between different biological knowledge sources has the potential for providing more effective screening strategies and therapeutic targets for many types of cancer.

Explicit awareness supports conditional visual search in the retrieval guidance paradigm.

PubMed

Buttaccio, Daniel R; Lange, Nicholas D; Hahn, Sowon; Thomas, Rick P

2014-01-01

In four experiments we explored whether participants would be able to use probabilistic prompts to simplify perceptually demanding visual search in a task we call the retrieval guidance paradigm. On each trial a memory prompt appeared prior to (and during) the search task and the diagnosticity of the prompt(s) was manipulated to provide complete, partial, or non-diagnostic information regarding the target's color on each trial (Experiments 1-3). In Experiment 1 we found that the more diagnostic prompts was associated with faster visual search performance. However, similar visual search behavior was observed in Experiment 2 when the diagnosticity of the prompts was eliminated, suggesting that participants in Experiment 1 were merely relying on base rate information to guide search and were not utilizing the prompts. In Experiment 3 participants were informed of the relationship between the prompts and the color of the target and this was associated with faster search performance relative to Experiment 1, suggesting that the participants were using the prompts to guide search. Additionally, in Experiment 3 a knowledge test was implemented and performance in this task was associated with qualitative differences in search behavior such that participants that were able to name the color(s) most associated with the prompts were faster to find the target than participants who were unable to do so. However, in Experiments 1-3 diagnosticity of the memory prompt was manipulated via base rate information, making it possible that participants were merely relying on base rate information to inform search in Experiment 3. In Experiment 4 we manipulated diagnosticity of the prompts without manipulating base rate information and found a similar pattern of results as Experiment 3. Together, the results emphasize the importance of base rate and diagnosticity information in visual search behavior. In the General discussion section we explore how a recent computational model of hypothesis generation (HyGene; Thomas, Dougherty, Sprenger, & Harbison, 2008), linking attention with long-term and working memory, accounts for the present results and provides a useful framework of cued recall visual search. Copyright © 2013 Elsevier B.V. All rights reserved.

Challenges of Making a Diagnosis in the Outpatient Setting: A Multi-Site Survey of Primary Care Physicians

PubMed Central

Sarkar, Urmimala; Bonacum, Doug; Strull, William; Spitzmueller, Christiane; Jin, Nancy; Lopez, Andrea; Giardina, Traber Davis; Meyer, Ashley N.D.; Singh, Hardeep

2013-01-01

Background Although misdiagnosis in the outpatient setting leads to significant patient harm and wasted resources, it is not well studied. We surveyed primary care physicians (PCPs) about barriers to timely diagnosis in the outpatient setting and assessed their perceptions of diagnostic difficulty. Methods We conducted a survey of general internists and family physicians practicing in an integrated health system across 10 geographically dispersed states in 2005. The survey elicited information on key cognitive failures (such as in clinical knowledge or judgment) for a specific case, and solicited strategies for reducing diagnostic delays. Content analysis was used to categorize cognitive failures and strategies for improvement. We examined the extent and predictors of diagnostic difficulty, defined as reporting >5% patients difficult to diagnose. Results Of 1817 physicians surveyed, 1054 (58%) responded; 848 (80%) respondents primarily practiced in outpatient settings and had an assigned patient panel (inclusion sample). Inadequate knowledge (19.9%) was the most commonly reported cognitive factor. Half reported >5% of their patients were difficult to diagnose; more experienced physicians reported less diagnostic difficulty. In adjusted analyses, problems with information processing (information availability and time to review it) and the referral process, were associated with greater diagnostic difficulty. Strategies for improvement most commonly involved workload issues (panel size, non-visit tasks). Conclusions PCPs report a variety of reasons for diagnostic difficulties in primary care practice. In our study, knowledge gaps appear to be a prominent concern. Interventions that address these gaps as well as practice level issues such as time to process diagnostic information and better subspecialty input may reduce diagnostic difficulties in primary care. PMID:22626738

Hybrid approach for robust diagnostics of cutting tools

NASA Astrophysics Data System (ADS)

Ramamurthi, K.; Hough, C. L., Jr.

1994-03-01

A new multisensor based hybrid technique has been developed for robust diagnosis of cutting tools. The technique combines the concepts of pattern classification and real-time knowledge based systems (RTKBS) and draws upon their strengths; learning facility in the case of pattern classification and a higher level of reasoning in the case of RTKBS. It eliminates some of their major drawbacks: false alarms or delayed/lack of diagnosis in case of pattern classification and tedious knowledge base generation in case of RTKBS. It utilizes a dynamic distance classifier, developed upon a new separability criterion and a new definition of robust diagnosis for achieving these benefits. The promise of this technique has been proven concretely through an on-line diagnosis of drill wear. Its suitability for practical implementation is substantiated by the use of practical, inexpensive, machine-mounted sensors and low-cost delivery systems.

Systematic teaching method to enhance the effectiveness of training for paragonimiasis.

PubMed

Zhang, Jian; Zhang, Xilin; Huang, Fusheng; Xu, Wenyue

2013-01-01

The clinical symptoms of human paragonimiasis are complex and variable, and patients can easily be misdiagnosed. Pagumogonimus skrjabini is the species causing this disease found only in China. A 2002 epidemiological survey showed that the rate of paragonimiasis was 21·96% in the migration areas of the Three-Gorge Reservoir, Chongqing, China. Therefore, there is a need to train medical workers to treat individuals in these areas. The Third Military Medical University (TMMU) in Chongqing built a comprehensive and systematic teaching method, which included teaching students about the basic biology of the organism, guiding students to use appropriate diagnostic tests and participate in scientific research to develop diagnostic kits, and visiting endemic areas to provide on-site teaching. The use of on-site teaching is an innovative approach for training undergraduate medical students in human parasitology. Three improvements were implemented during the on-site teaching component of the program: (1) systematizing the learning process; (2) integrating formal knowledge with clinical experience; and (3) enhancing students' knowledge of medical ethics. Based on a survey, 95% of students believed that this systematic teaching system gave them a more comprehensive grasp of knowledge on P. skrjabini, and graduate students were able to provide early diagnosis of P. skrjabini cases in this remote region. Students also participated in the research and development of a P. skrjabini diagnostic kit, for which a patent has been applied, and during the on-site teaching process, data were collected for the government and health sector to assist in public-health planning and decision-making for this disease.

Molecular pathology curriculum for medical laboratory scientists: A report of the association for molecular pathology training and education committee.

PubMed

Taylor, Sara; Bennett, Katie M; Deignan, Joshua L; Hendrix, Ericka C; Orton, Susan M; Verma, Shalini; Schutzbank, Ted E

2014-05-01

Molecular diagnostics is a rapidly growing specialty in the clinical laboratory assessment of pathology. Educational programs in medical laboratory science and specialized programs in molecular diagnostics must address the training of clinical scientists in molecular diagnostics, but the educational curriculum for this field is not well defined. Moreover, our understanding of underlying genetic contributions to specific diseases and the technologies used in molecular diagnostics laboratories change rapidly, challenging providers of training programs in molecular diagnostics to keep their curriculum current and relevant. In this article, we provide curriculum recommendations to molecular diagnostics training providers at both the baccalaureate and master's level of education. We base our recommendations on several factors. First, we considered National Accrediting Agency for Clinical Laboratory Sciences guidelines for accreditation of molecular diagnostics programs, because educational programs in clinical laboratory science should obtain its accreditation. Second, the guidelines of several of the best known certifying agencies for clinical laboratory scientists were incorporated into our recommendations. Finally, we relied on feedback from current employers of molecular diagnostics scientists, regarding the skills and knowledge that they believe are essential for clinical scientists who will be performing molecular testing in their laboratories. We have compiled these data into recommendations for a molecular diagnostics curriculum at both the baccalaureate and master's level of education. Copyright © 2014 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

Case against Diagnosing Developmental Language Disorder by Default: A Single Case Study of Acquired Aphasia Associated with Convulsive Disorder

ERIC Educational Resources Information Center

Marinac, Julie V.; Harper, Laura

2009-01-01

The aim of this article is to inform the diagnostic knowledge base for professionals working in the field of language disorders when classic symptoms, characteristics and sequences are not found. The information reveals the risk of diagnosis with a developmental language disorder (DLD) by default when no underlying cause can be readily identified.…

Difficulties to differentiate mood disorders co-occurring with compulsive gambling. Discussion based on a case study.

PubMed

Pilszyk, Anna; Silczuk, Andrzej; Habrat, Bogusław; Heitzman, Janusz

2018-02-28

Contemporary literature does not take a clear position on the issue of determining civil and criminal liability of persons diagnosed with pathological gambling, and all the more so in case of possible comorbidity of or interference with other mental disorders. Diagnostic difficulties are demonstrated by a clinical picture of a patient with problem gambling who underwent forensic and psychiatric assessments to evaluate the process of making informed (and independent) decisions in view of numerous concluded civil law (mainly financial) agreements. The patient had been examined 5 times by expert psychiatrists who, in 4 opinions, diagnosed her with bipolar affective disorder, including 1 diagnosis of rapid cycling of episodes. Based on the current state of scientific knowledge about the relationship between problem gambling and mood disorders, bipolar affective disorder was not confirmed. Diagnostic difficulties, resulting both from diagnostic haziness and unreliable information obtained during patient interview, that emerged in the course of case study point to the need for multi-dimensional clinical diagnosis of persons with suspected mood disorders and behavioral addictions.

Molecular Diagnostics in Pathology: Time for a Next-Generation Pathologist?

PubMed

Fassan, Matteo

2018-03-01

- Comprehensive molecular investigations of mainstream carcinogenic processes have led to the use of effective molecular targeted agents in most cases of solid tumors in clinical settings. - To update readers regarding the evolving role of the pathologist in the therapeutic decision-making process and the introduction of next-generation technologies into pathology practice. - Current literature on the topic, primarily sourced from the PubMed (National Center for Biotechnology Information, Bethesda, Maryland) database, were reviewed. - Adequate evaluation of cytologic-based and tissue-based predictive diagnostic biomarkers largely depends on both proper pathologic characterization and customized processing of biospecimens. Moreover, increased requests for molecular testing have paralleled the recent, sharp decrease in tumor material to be analyzed-material that currently comprises cytology specimens or, at minimum, small biopsies in most cases of metastatic/advanced disease. Traditional diagnostic pathology has been completely revolutionized by the introduction of next-generation technologies, which provide multigene, targeted mutational profiling, even in the most complex of clinical cases. Combining traditional and molecular knowledge, pathologists integrate the morphological, clinical, and molecular dimensions of a disease, leading to a proper diagnosis and, therefore, the most-appropriate tailored therapy.

A Diagnostic Approach for Electro-Mechanical Actuators in Aerospace Systems

NASA Technical Reports Server (NTRS)

Balaban, Edward; Saxena, Abhinav; Bansal, Prasun; Goebel, Kai Frank; Stoelting, Paul; Curran, Simon

2009-01-01

Electro-mechanical actuators (EMA) are finding increasing use in aerospace applications, especially with the trend towards all all-electric aircraft and spacecraft designs. However, electro-mechanical actuators still lack the knowledge base accumulated for other fielded actuator types, particularly with regard to fault detection and characterization. This paper presents a thorough analysis of some of the critical failure modes documented for EMAs and describes experiments conducted on detecting and isolating a subset of them. The list of failures has been prepared through an extensive Failure Modes and Criticality Analysis (FMECA) reference, literature review, and accessible industry experience. Methods for data acquisition and validation of algorithms on EMA test stands are described. A variety of condition indicators were developed that enabled detection, identification, and isolation among the various fault modes. A diagnostic algorithm based on an artificial neural network is shown to operate successfully using these condition indicators and furthermore, robustness of these diagnostic routines to sensor faults is demonstrated by showing their ability to distinguish between them and component failures. The paper concludes with a roadmap leading from this effort towards developing successful prognostic algorithms for electromechanical actuators.

Epidemiology of and Diagnostic Strategies for Toxoplasmosis

PubMed Central

Dardé, Marie-Laure

2012-01-01

Summary: The apicomplexan parasite Toxoplasma gondii was discovered a little over 100 years ago, but knowledge of its biological life cycle and its medical importance has grown in the last 40 years. This obligate intracellular parasite was identified early as a pathogen responsible for congenital infection, but its clinical expression and the importance of reactivations of infections in immunocompromised patients were recognized later, in the era of organ transplantation and HIV infection. Recent knowledge of host cell-parasite interactions and of parasite virulence has brought new insights into the comprehension of the pathophysiology of infection. In this review, we focus on epidemiological and diagnostic aspects, putting them in perspective with current knowledge of parasite genotypes. In particular, we provide critical information on diagnostic methods according to the patient's background and discuss the implementation of screening tools for congenital toxoplasmosis according to health policies. PMID:22491772

Presentation of Diagnostic Information to Doctors May Change Their Interpretation and Clinical Management: A Web-Based Randomised Controlled Trial.

PubMed

Ben-Shlomo, Yoav; Collin, Simon M; Quekett, James; Sterne, Jonathan A C; Whiting, Penny

2015-01-01

There is little evidence on how best to present diagnostic information to doctors and whether this makes any difference to clinical management. We undertook a randomised controlled trial to see if different data presentations altered clinicians' decision to further investigate or treat a patient with a fictitious disorder ("Green syndrome") and their ability to determine post-test probability. We recruited doctors registered with the United Kingdom's largest online network for medical doctors between 10 July and 6" November 2012. Participants were randomised to one of four arms: (a) text summary of sensitivity and specificity, (b) Fagan's nomogram, (c) probability-modifying plot (PMP), (d) natural frequency tree (NFT). The main outcome measure was the decision whether to treat, not treat or undertake a brain biopsy on the hypothetical patient and the correct post-test probability. Secondary outcome measures included knowledge of diagnostic tests. 917 participants attempted the survey and complete data were available from 874 (95.3%). Doctors randomized to the PMP and NFT arms were more likely to treat the patient than those randomized to the text-only arm. (ORs 1.49, 95% CI 1.02, 2.16) and 1.43, 95% CI 0.98, 2.08 respectively). More patients randomized to the PMP (87/218-39.9%) and NFT (73/207-35.3%) arms than the nomogram (50/194-25.8%) or text only (30/255-11.8%) arms reported the correct post-test probability (p <0.001). Younger age, postgraduate training and higher self-rated confidence all predicted better knowledge performance. Doctors with better knowledge were more likely to view an optional learning tutorial (OR per correct answer 1.18, 95% CI 1.06, 1.31). Presenting diagnostic data using a probability-modifying plot or natural frequency tree influences the threshold for treatment and improves interpretation of tests results compared to text summary of sensitivity and specificity or Fagan's nomogram.

Diagnostic Analyzer for Gearboxes (DAG): User's Guide. Version 3.1 for Microsoft Windows 3.1

NASA Technical Reports Server (NTRS)

Jammu, Vinay B.; Kourosh, Danai

1997-01-01

This documentation describes the Diagnostic Analyzer for Gearboxes (DAG) software for performing fault diagnosis of gearboxes. First, the user would construct a graphical representation of the gearbox using the gear, bearing, shaft, and sensor tools contained in the DAG software. Next, a set of vibration features obtained by processing the vibration signals recorded from the gearbox using a signal analyzer is required. Given this information, the DAG software uses an unsupervised neural network referred to as the Fault Detection Network (FDN) to identify the occurrence of faults, and a pattern classifier called Single Category-Based Classifier (SCBC) for abnormality scaling of individual vibration features. The abnormality-scaled vibration features are then used as inputs to a Structure-Based Connectionist Network (SBCN) for identifying faults in gearbox subsystems and components. The weights of the SBCN represent its diagnostic knowledge and are derived from the structure of the gearbox graphically presented in DAG. The outputs of SBCN are fault possibility values between 0 and 1 for individual subsystems and components in the gearbox with a 1 representing a definite fault and a 0 representing normality. This manual describes the steps involved in creating the diagnostic gearbox model, along with the options and analysis tools of the DAG software.

Addressing the challenges of diagnostics demand and supply: insights from an online global health discussion platform.

PubMed

Engel, Nora; Wachter, Keri; Pai, Madhukar; Gallarda, Jim; Boehme, Catharina; Celentano, Isabelle; Weintraub, Rebecca

2016-01-01

Several barriers challenge development, adoption and scale-up of diagnostics in low and middle income countries. An innovative global health discussion platform allows capturing insights from the global health community on factors driving demand and supply for diagnostics. We conducted a qualitative content analysis of the online discussion 'Advancing Care Delivery: Driving Demand and Supply of Diagnostics' organised by the Global Health Delivery Project (GHD) (http://www.ghdonline.org/) at Harvard University. The discussion, driven by 12 expert panellists, explored what must be done to develop delivery systems, business models, new technologies, interoperability standards, and governance mechanisms to ensure that patients receive the right diagnostic at the right time. The GHD Online (GHDonline) platform reaches over 19 000 members from 185 countries. Participants (N=99) in the diagnostics discussion included academics, non-governmental organisations, manufacturers, policymakers, and physicians. Data was coded and overarching categories analysed using qualitative data analysis software. Participants considered technical characteristics of diagnostics as smaller barriers to effective use of diagnostics compared with operational and health system challenges, such as logistics, poor fit with user needs, cost, workforce, infrastructure, access, weak regulation and political commitment. Suggested solutions included: health system strengthening with patient-centred delivery; strengthened innovation processes; improved knowledge base; harmonised guidelines and evaluation; supply chain innovations; and mechanisms for ensuring quality and capacity. Engaging and connecting different actors involved with diagnostic development and use is paramount for improving diagnostics. While the discussion participants were not representative of all actors involved, the platform enabled a discussion between globally acknowledged experts and physicians working in different countries.

The American Board of Radiology Maintenance of Certification (MOC) Program in Radiologic Physics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomas, Stephen R.; Hendee, William R.; Paliwal, Bhudatt R.

2005-01-01

Maintenance of Certification (MOC) recognizes that in addition to medical knowledge, several essential elements involved in delivering quality care must be developed and maintained throughout one's career. The MOC process is designed to facilitate and document the professional development of each diplomate of The American Board of Radiology (ABR) through its focus on the essential elements of quality care in Diagnostic Radiology and its subspecialties, and in the specialties of Radiation Oncology and Radiologic Physics. The initial elements of the ABR-MOC have been developed in accord with guidelines of The American Board of Medical Specialties. All diplomates with a ten-year,more » time-limited primary certificate in Diagnostic Radiologic Physics, Therapeutic Radiologic Physics, or Medical Nuclear Physics who wish to maintain certification must successfully complete the requirements of the appropriate ABR-MOC program for their specialty. Holders of multiple certificates must meet ABR-MOC requirements specific to the certificates held. Diplomates with lifelong certificates are not required to participate in the MOC, but are strongly encouraged to do so. MOC is based on documentation of individual participation in the four components of MOC: (1) professional standing, (2) lifelong learning and self-assessment, (3) cognitive expertise, and (4) performance in practice. Within these components, MOC addresses six competencies: medical knowledge, patient care, interpersonal and communication skills, professionalism, practice-based learning and improvement, and systems-based practice.« less

Reusable rocket engine turbopump health monitoring system, part 3

NASA Technical Reports Server (NTRS)

Perry, John G.

1989-01-01

Degradation mechanisms and sensor identification/selection resulted in a list of degradation modes and a list of sensors that are utilized in the diagnosis of these degradation modes. The sensor list is divided into primary and secondary indicators of the corresponding degradation modes. The signal conditioning requirements are discussed, describing the methods of producing the Space Shuttle Main Engine (SSME) post-hot-fire test data to be utilized by the Health Monitoring System. Development of the diagnostic logic and algorithms is also presented. The knowledge engineering approach, as utilized, includes the knowledge acquisition effort, characterization of the expert's problem solving strategy, conceptually defining the form of the applicable knowledge base, and rule base, and identifying an appropriate inferencing mechanism for the problem domain. The resulting logic flow graphs detail the diagnosis/prognosis procedure as followed by the experts. The nature and content of required support data and databases is also presented. The distinction between deep and shallow types of knowledge is identified. Computer coding of the Health Monitoring System is shown to follow the logical inferencing of the logic flow graphs/algorithms.

Quantifying Novice and Expert Differences in Visual Diagnostic Reasoning in Veterinary Pathology Using Eye-Tracking Technology.

PubMed

Warren, Amy L; Donnon, Tyrone L; Wagg, Catherine R; Priest, Heather; Fernandez, Nicole J

2018-01-18

Visual diagnostic reasoning is the cognitive process by which pathologists reach a diagnosis based on visual stimuli (cytologic, histopathologic, or gross imagery). Currently, there is little to no literature examining visual reasoning in veterinary pathology. The objective of the study was to use eye tracking to establish baseline quantitative and qualitative differences between the visual reasoning processes of novice and expert veterinary pathologists viewing cytology specimens. Novice and expert participants were each shown 10 cytology images and asked to formulate a diagnosis while wearing eye-tracking equipment (10 slides) and while concurrently verbalizing their thought processes using the think-aloud protocol (5 slides). Compared to novices, experts demonstrated significantly higher diagnostic accuracy (p<.017), shorter time to diagnosis (p<.017), and a higher percentage of time spent viewing areas of diagnostic interest (p<.017). Experts elicited more key diagnostic features in the think-aloud protocol and had more efficient patterns of eye movement. These findings suggest that experts' fast time to diagnosis, efficient eye-movement patterns, and preference for viewing areas of interest supports system 1 (pattern-recognition) reasoning and script-inductive knowledge structures with system 2 (analytic) reasoning to verify their diagnosis.

Incorporating personalized gene sequence variants, molecular genetics knowledge, and health knowledge into an EHR prototype based on the Continuity of Care Record standard.

PubMed

Jing, Xia; Kay, Stephen; Marley, Thomas; Hardiker, Nicholas R; Cimino, James J

2012-02-01

The current volume and complexity of genetic tests, and the molecular genetics knowledge and health knowledge related to interpretation of the results of those tests, are rapidly outstripping the ability of individual clinicians to recall, understand and convey to their patients information relevant to their care. The tailoring of molecular genetics knowledge and health knowledge in clinical settings is important both for the provision of personalized medicine and to reduce clinician information overload. In this paper we describe the incorporation, customization and demonstration of molecular genetic data (mainly sequence variants), molecular genetics knowledge and health knowledge into a standards-based electronic health record (EHR) prototype developed specifically for this study. We extended the CCR (Continuity of Care Record), an existing EHR standard for representing clinical data, to include molecular genetic data. An EHR prototype was built based on the extended CCR and designed to display relevant molecular genetics knowledge and health knowledge from an existing knowledge base for cystic fibrosis (OntoKBCF). We reconstructed test records from published case reports and represented them in the CCR schema. We then used the EHR to dynamically filter molecular genetics knowledge and health knowledge from OntoKBCF using molecular genetic data and clinical data from the test cases. The molecular genetic data were successfully incorporated in the CCR by creating a category of laboratory results called "Molecular Genetics" and specifying a particular class of test ("Gene Mutation Test") in this category. Unlike other laboratory tests reported in the CCR, results of tests in this class required additional attributes ("Molecular Structure" and "Molecular Position") to support interpretation by clinicians. These results, along with clinical data (age, sex, ethnicity, diagnostic procedures, and therapies) were used by the EHR to filter and present molecular genetics knowledge and health knowledge from OntoKBCF. This research shows a feasible model for delivering patient sequence variants and presenting tailored molecular genetics knowledge and health knowledge via a standards-based EHR system prototype. EHR standards can be extended to include the necessary patient data (as we have demonstrated in the case of the CCR), while knowledge can be obtained from external knowledge bases that are created and maintained independently from the EHR. This approach can form the basis for a personalized medicine framework, a more comprehensive standards-based EHR system and a potential platform for advancing translational research by both disseminating results and providing opportunities for new insights into phenotype-genotype relationships. Copyright © 2011 Elsevier Inc. All rights reserved.

Decision support systems in health economics.

PubMed

Quaglini, S; Dazzi, L; Stefanelli, M; Barosi, G; Marchetti, M

1999-08-01

This article describes a system addressed to different health care professionals for building, using, and sharing decision support systems for resource allocation. The system deals with selected areas, namely the choice of diagnostic tests, the therapy planning, and the instrumentation purchase. Decision support is based on decision-analytic models, incorporating an explicit knowledge representation of both the medical domain knowledge and the economic evaluation theory. Application models are built on top of meta-models, that are used as guidelines for making explicit both the cost and effectiveness components. This approach improves the transparency and soundness of the collaborative decision-making process and facilitates the result interpretation.

Do Students Know What They Know and What They Don't Know? Using a Four-Tier Diagnostic Test to Assess the Nature of Students' Alternative Conceptions

ERIC Educational Resources Information Center

Caleon, Imelda S.; Subramaniam, R.

2010-01-01

This study reports on the development and application of a four-tier multiple-choice (4TMC) diagnostic instrument, which has not been reported in the literature. It is an enhanced version of the two-tier multiple-choice (2TMC) test. As in 2TMC tests, its answer and reason tiers measure students' content knowledge and explanatory knowledge,…

A Clinical Approach to the Diagnosis of Acid-Base Disorders

PubMed Central

Bear, Robert A.

1986-01-01

The ability to diagnose and manage acid-base disorders rapidly and effectively is essential to the care of critically ill patients. This article presents an approach to the diagnosis of pure and mixed acid-base disorders, metabolic or respiratory. The approach taken is based on using the law of mass-action equation as it applies to the bicarbonate buffer system (Henderson equation), using sub-classifications for diagnostic purposes of causes of metabolic acidosis and metabolic alkalosis, and using a knowledge of the well-defined and predictable compensatory responses that attempt to limit the change in pH in each of the primary acid-base disorders. PMID:21267134

Clinical Dental Faculty Members' Perceptions of Diagnostic Errors and How to Avoid Them.

PubMed

Nikdel, Cathy; Nikdel, Kian; Ibarra-Noriega, Ana; Kalenderian, Elsbeth; Walji, Muhammad F

2018-04-01

Diagnostic errors are increasingly recognized as a source of preventable harm in medicine, yet little is known about their occurrence in dentistry. The aim of this study was to gain a deeper understanding of clinical dental faculty members' perceptions of diagnostic errors, types of errors that may occur, and possible contributing factors. The authors conducted semi-structured interviews with ten domain experts at one U.S. dental school in May-August 2016 about their perceptions of diagnostic errors and their causes. The interviews were analyzed using an inductive process to identify themes and key findings. The results showed that the participants varied in their definitions of diagnostic errors. While all identified missed diagnosis and wrong diagnosis, only four participants perceived that a delay in diagnosis was a diagnostic error. Some participants perceived that an error occurs only when the choice of treatment leads to harm. Contributing factors associated with diagnostic errors included the knowledge and skills of the dentist, not taking adequate time, lack of communication among colleagues, and cognitive biases such as premature closure based on previous experience. Strategies suggested by the participants to prevent these errors were taking adequate time when investigating a case, forming study groups, increasing communication, and putting more emphasis on differential diagnosis. These interviews revealed differing perceptions of dental diagnostic errors among clinical dental faculty members. To address the variations, the authors recommend adopting shared language developed by the medical profession to increase understanding.

Semantics-based plausible reasoning to extend the knowledge coverage of medical knowledge bases for improved clinical decision support.

PubMed

Mohammadhassanzadeh, Hossein; Van Woensel, William; Abidi, Samina Raza; Abidi, Syed Sibte Raza

2017-01-01

Capturing complete medical knowledge is challenging-often due to incomplete patient Electronic Health Records (EHR), but also because of valuable, tacit medical knowledge hidden away in physicians' experiences. To extend the coverage of incomplete medical knowledge-based systems beyond their deductive closure, and thus enhance their decision-support capabilities, we argue that innovative, multi-strategy reasoning approaches should be applied. In particular, plausible reasoning mechanisms apply patterns from human thought processes, such as generalization, similarity and interpolation, based on attributional, hierarchical, and relational knowledge. Plausible reasoning mechanisms include inductive reasoning , which generalizes the commonalities among the data to induce new rules, and analogical reasoning , which is guided by data similarities to infer new facts. By further leveraging rich, biomedical Semantic Web ontologies to represent medical knowledge, both known and tentative, we increase the accuracy and expressivity of plausible reasoning, and cope with issues such as data heterogeneity, inconsistency and interoperability. In this paper, we present a Semantic Web-based, multi-strategy reasoning approach, which integrates deductive and plausible reasoning and exploits Semantic Web technology to solve complex clinical decision support queries. We evaluated our system using a real-world medical dataset of patients with hepatitis, from which we randomly removed different percentages of data (5%, 10%, 15%, and 20%) to reflect scenarios with increasing amounts of incomplete medical knowledge. To increase the reliability of the results, we generated 5 independent datasets for each percentage of missing values, which resulted in 20 experimental datasets (in addition to the original dataset). The results show that plausibly inferred knowledge extends the coverage of the knowledge base by, on average, 2%, 7%, 12%, and 16% for datasets with, respectively, 5%, 10%, 15%, and 20% of missing values. This expansion in the KB coverage allowed solving complex disease diagnostic queries that were previously unresolvable, without losing the correctness of the answers. However, compared to deductive reasoning, data-intensive plausible reasoning mechanisms yield a significant performance overhead. We observed that plausible reasoning approaches, by generating tentative inferences and leveraging domain knowledge of experts, allow us to extend the coverage of medical knowledge bases, resulting in improved clinical decision support. Second, by leveraging OWL ontological knowledge, we are able to increase the expressivity and accuracy of plausible reasoning methods. Third, our approach is applicable to clinical decision support systems for a range of chronic diseases.

Oncology Patient Perceptions of the Use of Ionizing Radiation in Diagnostic Imaging.

PubMed

Steele, Joseph R; Jones, Aaron K; Clarke, Ryan K; Giordano, Sharon H; Shoemaker, Stowe

2016-07-01

To measure the knowledge of oncology patients regarding use and potential risks of ionizing radiation in diagnostic imaging. A 30-question survey was developed and e-mailed to 48,736 randomly selected patients who had undergone a diagnostic imaging study at a comprehensive cancer center between November 1, 2013 and January 31, 2014. The survey was designed to measure patients' knowledge about use of ionizing radiation in diagnostic imaging and attitudes about radiation. Nonresponse bias was quantified by sending an abbreviated survey to patients who did not respond to the original survey. Of the 48,736 individuals who were sent the initial survey, 9,098 (18.7%) opened it, and 5,462 (11.2%) completed it. A total of 21.7% of respondents reported knowing the definition of ionizing radiation; 35.1% stated correctly that CT used ionizing radiation; and 29.4% stated incorrectly that MRI used ionizing radiation. Many respondents did not understand risks from exposure to diagnostic doses of ionizing radiation: Of 3,139 respondents who believed that an abdominopelvic CT scan carried risk, 1,283 (40.9%) believed sterility was a risk; 669 (21.3%) believed heritable mutations were a risk; 657 (20.9%) believed acute radiation sickness was a risk; and 135 (4.3%) believed cataracts were a risk. Most patients and caregivers do not possess basic knowledge regarding the use of ionizing radiation in oncologic diagnostic imaging. To ensure health literacy and high-quality patient decision making, efforts to educate patients and caregivers should be increased. Such education might begin with information about effects that are not risks of diagnostic imaging. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Knowledge and Adherence to the National Guidelines for Malaria Diagnosis in Pregnancy among Health-Care Providers and Drug-Outlet Dispensers in Rural Western Kenya.

PubMed

Riley, Christina; Dellicour, Stephanie; Ouma, Peter; Kioko, Urbanus; Omar, Ahmeddin; Kariuki, Simon; Ng'ang'a, Zipporah; Desai, Meghna; Buff, Ann M; Gutman, Julie R

2018-05-01

Prompt diagnosis and effective treatment of acute malaria in pregnancy (MiP) is important for the mother and fetus; data on health-care provider adherence to diagnostic guidelines in pregnancy are limited. From September to November 2013, a cross-sectional survey was conducted in 51 health facilities and 39 drug outlets in Western Kenya. Provider knowledge of national diagnostic guidelines for uncomplicated MiP were assessed using standardized questionnaires. The use of parasitologic testing was assessed in health facilities via exit interviews with febrile women of childbearing age and in drug outlets via simulated-client scenarios, posing as pregnant women or their spouses. Overall, 93% of providers tested for malaria or accurately described signs and symptoms consistent with clinical malaria. Malaria was parasitologically confirmed in 77% of all patients presenting with febrile illness at health facilities and 5% of simulated clients at drug outlets. Parasitological testing was available in 80% of health facilities; 92% of patients evaluated at these facilities were tested. Only 23% of drug outlets had malaria rapid diagnostic tests (RDTs); at these outlets, RDTs were offered in 17% of client simulations. No differences were observed in testing rates by pregnancy trimester. The study highlights gaps among health providers in diagnostic knowledge and practice related to MiP, and the lack of malaria diagnostic capacity, particularly in drug outlets. The most important factor associated with malaria testing of pregnant women was the availability of diagnostics at the point of service. Interventions that increase the availability of malaria diagnostic services might improve malaria case management in pregnant women.

The role of general practice in routes to diagnosis of lung cancer in Denmark: a population-based study of general practice involvement, diagnostic activity and diagnostic intervals.

PubMed

Guldbrandt, Louise Mahncke; Fenger-Grøn, Morten; Rasmussen, Torben Riis; Jensen, Henry; Vedsted, Peter

2015-01-22

Lung cancer stage at diagnosis predicts possible curative treatment. In Denmark and the UK, lung cancer patients have lower survival rates than citizens in most other European countries, which may partly be explained by a comparatively longer diagnostic interval in these two countries. In Denmark, a pathway was introduced in 2008 allowing general practitioners (GPs) to refer patients suspected of having lung cancer directly to fast-track diagnostics. However, symptom presentation of lung cancer in general practice is known to be diverse and complex, and systematic knowledge of the routes to diagnosis is needed to enable earlier lung cancer diagnosis in Denmark. This study aims to describe the routes to diagnosis, the diagnostic activity preceding diagnosis and the diagnostic intervals for lung cancer in the Danish setting. We conducted a national registry-based cohort study on 971 consecutive incident lung cancer patients in 2010 using data from national registries and GP questionnaires. GPs were involved in 68.3% of cancer patients' diagnostic pathways, and 27.4% of lung cancer patients were referred from the GP to fast-track diagnostic work-up. A minimum of one X-ray was performed in 85.6% of all cases before diagnosis. Patients referred through a fast-track route more often had diagnostic X-rays (66.0%) than patients who did not go through fast-track (49.4%). Overall, 33.6% of all patients had two or more X-rays performed during the 90 days before diagnosis. Patients whose symptoms were interpreted as non-alarm symptoms or who were not referred to fast-track were more likely to experience a long diagnostic interval than patients whose symptoms were interpreted as alarm symptoms or who were referred to fast-track. Lung cancer patients followed several diagnostic pathways. The existing fast-track pathway must be supplemented to ensure earlier detection of lung cancer. The high incidence of multiple X-rays warrants a continued effort to develop more accurate lung cancer tests for use in primary care.

The biasing effect of clinical history on physical examination diagnostic accuracy.

PubMed

Sibbald, Matthew; Cavalcanti, Rodrigo B

2011-08-01

Literature on diagnostic test interpretation has shown that access to clinical history can both enhance diagnostic accuracy and increase diagnostic error. Knowledge of clinical history has also been shown to enhance the more complex cognitive task of physical examination diagnosis, possibly by enabling early hypothesis generation. However, it is unclear whether clinicians adhere to these early hypotheses in the face of unexpected physical findings, thus resulting in diagnostic error. A sample of 180 internal medicine residents received a short clinical history and conducted a cardiac physical examination on a high-fidelity simulator. Resident Doctors (Residents) were randomised to three groups based on the physical findings in the simulator. The concordant group received physical examination findings consistent with the diagnosis that was most probable based on the clinical history. Discordant groups received findings associated with plausible alternative diagnoses which either lacked expected findings (indistinct discordant) or contained unexpected findings (distinct discordant). Physical examination diagnostic accuracy and physical examination findings were analysed. Physical examination diagnostic accuracy varied significantly among groups (75 ± 44%, 2 ± 13% and 31 ± 47% in the concordant, indistinct discordant and distinct discordant groups, respectively (F(2,177)  = 53, p < 0.0001). Of the 115 Residents who were diagnostically unsuccessful, 33% adhered to their original incorrect hypotheses. Residents verbalised an average of 12 findings (interquartile range: 10-14); 58 ± 17% were correct and the percentage of correct findings was similar in all three groups (p = 0.44). Residents showed substantially decreased diagnostic accuracy when faced with discordant physical findings. The majority of trainees given discordant physical findings rejected their initial hypotheses, but were still diagnostically unsuccessful. These results suggest that overcoming the bias induced by a misleading clinical history may involve two independent steps: rejection of the incorrect initial hypothesis, and selection of the correct diagnosis. Educational strategies focused solely on prompting clinicians to re-examine their hypotheses may be insufficient to reduce diagnostic error. © Blackwell Publishing Ltd 2011.

Process-based upscaling of surface-atmosphere exchange

NASA Astrophysics Data System (ADS)

Keenan, T. F.; Prentice, I. C.; Canadell, J.; Williams, C. A.; Wang, H.; Raupach, M. R.; Collatz, G. J.; Davis, T.; Stocker, B.; Evans, B. J.

2015-12-01

Empirical upscaling techniques such as machine learning and data-mining have proven invaluable tools for the global scaling of disparate observations of surface-atmosphere exchange, but are not based on a theoretical understanding of the key processes involved. This makes spatial and temporal extrapolation outside of the training domain difficult at best. There is therefore a clear need for the incorporation of knowledge of ecosystem function, in combination with the strength of data mining. Here, we present such an approach. We describe a novel diagnostic process-based model of global photosynthesis and ecosystem respiration, which is directly informed by a variety of global datasets relevant to ecosystem state and function. We use the model framework to estimate global carbon cycling both spatially and temporally, with a specific focus on the mechanisms responsible for long-term change. Our results show the importance of incorporating process knowledge into upscaling approaches, and highlight the effect of key processes on the terrestrial carbon cycle.

A CLIPS based personal computer hardware diagnostic system

NASA Technical Reports Server (NTRS)

Whitson, George M.

1991-01-01

Often the person designated to repair personal computers has little or no knowledge of how to repair a computer. Described here is a simple expert system to aid these inexperienced repair people. The first component of the system leads the repair person through a number of simple system checks such as making sure that all cables are tight and that the dip switches are set correctly. The second component of the system assists the repair person in evaluating error codes generated by the computer. The final component of the system applies a large knowledge base to attempt to identify the component of the personal computer that is malfunctioning. We have implemented and tested our design with a full system to diagnose problems for an IBM compatible system based on the 8088 chip. In our tests, the inexperienced repair people found the system very useful in diagnosing hardware problems.

Engineering Applications of Neural Computing: A State-of-the-Art Survey

DTIC Science & Technology

1991-05-01

results of the neural networks and compare with doctor’s knowledge. In veterinary medicine, a system for diag- nosis of mastitis in dairy cows is...construction of a hybrid system for diagnosing mastitis in COWS . Perhaps the most noteworthy application is the neural network-based explosive...diagnosis of mastitis in a limited set of experimental data showed excellent accuracy. In engineering facility management, monitoring and diagnostics are

Expert systems in the process industries

NASA Technical Reports Server (NTRS)

Stanley, G. M.

1992-01-01

This paper gives an overview of industrial applications of real-time knowledge based expert systems (KBES's) in the process industries. After a brief overview of the features of a KBES useful in process applications, the general roles of KBES's are covered. A particular focus is diagnostic applications, one of the major applications areas. Many applications are seen as an expansion of supervisory control. The lessons learned from numerous online applications are summarized.

Radiation hazards in scoliosis management

DOE Office of Scientific and Technical Information (OSTI.GOV)

Drummond, D.; Ranallo, F.; Lonstein, J.

1983-10-01

Safe radiography in scoliosis management is based on a sound knowledge of 1) the radiographic imaging process, 2) the degree of risk to the patient from radiation exposure, and 3) the radiographic requirements to both evaluate and follow patients with spine deformity. This paper is a current review of the subject and work done at the authors' centers. It includes recommendations for reducing the radiation risk while maintaining necessary diagnostic information.

Problems in shortening the time to confirmation of ALS diagnosis: lessons from the 1st Consensus Conference, Chicago, May 1998.

PubMed

Brooks, B R

2000-03-01

The 2nd Consensus Conference (Versailles) on the early diagnosis of amyotrophic lateral sclerosis (ALS) developed themes identified at the 1st Consensus Conference (Chicago) on defining optimal management in ALS. These themes included describing the problems and limitations in current diagnostic practices, identifying consequences of early diagnosis on patient management, establishing recommendations to help healthcare personnel achieve the early diagnosis and proposing solutions to facilitate early diagnosis of ALS. Lessons from the ISIS Survey and the 1st Consensus Conference focused on the variability of the first-contact physician, supply factors for specialists and variability of application of medical techniques. The recently introduced concept of 'ALS health states or stages' was reviewed in terms of ongoing and potential prospective studies. The relative contribution of neuroimaging or clinical neurophysiological investigations to accelerating the diagnosis of ALS in clinical practice was debated. The role of a common ALS knowledge-base among patients, initial healthcare providers, diagnosing neurologists and confirming neurologists was critically appraised with regard to simplified 'ALS diagnostic algorithm', 'ten aphorisms in the diagnosis of ALS' and 'ALS axioms of referral'. Refining this ALS knowledge-base is required to identify a minimum dataset required for the evaluation and diagnosis of ALS.

High School Biology Students' Knowledge and Certainty about Diffusion and Osmosis Concepts

ERIC Educational Resources Information Center

Odom, Arthur L.; Barrow, Lloyd H.

2007-01-01

The purpose of this study was to investigate students' understanding about scientifically acceptable content knowledge by exploring the relationship between knowledge of diffusion and osmosis and the students' certainty in their content knowledge. Data was collected from a high school biology class with the Diffusion and Osmosis Diagnostic Test…

Combining knowledge discovery from databases (KDD) and case-based reasoning (CBR) to support diagnosis of medical images

NASA Astrophysics Data System (ADS)

Stranieri, Andrew; Yearwood, John; Pham, Binh

1999-07-01

The development of data warehouses for the storage and analysis of very large corpora of medical image data represents a significant trend in health care and research. Amongst other benefits, the trend toward warehousing enables the use of techniques for automatically discovering knowledge from large and distributed databases. In this paper, we present an application design for knowledge discovery from databases (KDD) techniques that enhance the performance of the problem solving strategy known as case- based reasoning (CBR) for the diagnosis of radiological images. The problem of diagnosing the abnormality of the cervical spine is used to illustrate the method. The design of a case-based medical image diagnostic support system has three essential characteristics. The first is a case representation that comprises textual descriptions of the image, visual features that are known to be useful for indexing images, and additional visual features to be discovered by data mining many existing images. The second characteristic of the approach presented here involves the development of a case base that comprises an optimal number and distribution of cases. The third characteristic involves the automatic discovery, using KDD techniques, of adaptation knowledge to enhance the performance of the case based reasoner. Together, the three characteristics of our approach can overcome real time efficiency obstacles that otherwise mitigate against the use of CBR to the domain of medical image analysis.

Knowledge, attitudes and practices of food handlers in food safety: An integrative review.

PubMed

Zanin, Laís Mariano; da Cunha, Diogo Thimoteo; de Rosso, Veridiana Vera; Capriles, Vanessa Dias; Stedefeldt, Elke

2017-10-01

This study presents an overview of the relationship between knowledge, attitudes and practices (KAP) of food handlers with training in food safety, in addition to proposing reflections on the training of food handlers, considering its responsibility for food safety and health of consumers. The review was based on the integrative method. The descriptors used were: (food handler), (knowledge, attitudes and practice) and (training). Six databases were searched, 253 articles were consulted and 36 original articles were included. Fifty per cent of the articles pointed that there was no proper translation of knowledge into attitudes/practices or attitudes into practices after training. Knowledge, attitudes and practices of food handlers are important for identifying how efficient training in food safety is allowing prioritize actions in planning training. The evaluation of KAP is the first step to understand the food handler's point of view. After this evaluation other diagnostic strategies become necessary to enhance this understanding. Copyright © 2017. Published by Elsevier Ltd.

A tuberculosis biomarker database: the key to novel TB diagnostics.

PubMed

Yerlikaya, Seda; Broger, Tobias; MacLean, Emily; Pai, Madhukar; Denkinger, Claudia M

2017-03-01

New diagnostic innovations for tuberculosis (TB), including point-of-care solutions, are critical to reach the goals of the End TB Strategy. However, despite decades of research, numerous reports on new biomarker candidates, and significant investment, no well-performing, simple and rapid TB diagnostic test is yet available on the market, and the search for accurate, non-DNA biomarkers remains a priority. To help overcome this 'biomarker pipeline problem', FIND and partners are working on the development of a well-curated and user-friendly TB biomarker database. The web-based database will enable the dynamic tracking of evidence surrounding biomarker candidates in relation to target product profiles (TPPs) for needed TB diagnostics. It will be able to accommodate raw datasets and facilitate the verification of promising biomarker candidates and the identification of novel biomarker combinations. As such, the database will simplify data and knowledge sharing, empower collaboration, help in the coordination of efforts and allocation of resources, streamline the verification and validation of biomarker candidates, and ultimately lead to an accelerated translation into clinically useful tools. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

A General Architecture for Intelligent Tutoring of Diagnostic Classification Problem Solving

PubMed Central

Crowley, Rebecca S.; Medvedeva, Olga

2003-01-01

We report on a general architecture for creating knowledge-based medical training systems to teach diagnostic classification problem solving. The approach is informed by our previous work describing the development of expertise in classification problem solving in Pathology. The architecture envelops the traditional Intelligent Tutoring System design within the Unified Problem-solving Method description Language (UPML) architecture, supporting component modularity and reuse. Based on the domain ontology, domain task ontology and case data, the abstract problem-solving methods of the expert model create a dynamic solution graph. Student interaction with the solution graph is filtered through an instructional layer, which is created by a second set of abstract problem-solving methods and pedagogic ontologies, in response to the current state of the student model. We outline the advantages and limitations of this general approach, and describe it’s implementation in SlideTutor–a developing Intelligent Tutoring System in Dermatopathology. PMID:14728159

How can we reliably identify a taxon based on humeral morphology? Comparative morphology of desmostylian humeri

PubMed Central

2017-01-01

Desmostylia is a clade of marine mammals belonging to either Tethytheria or Perissodactyla. Rich fossil records of Desmostylia were found in the Oligocene to Miocene strata of the Northern Pacific Rim, especially in the northwestern region, which includes the Japanese archipelago. Fossils in many shapes and forms, including whole or partial skeletons, skulls, teeth, and fragmentary bones have been discovered from this region. Despite the prevalent availability of fossil records, detailed taxonomic identification based on fragmentary postcranial materials has been difficult owing to to our limited knowledge of the postcranial diagnostic features of many desmostylian taxa. In this study, I propose the utilization of diagnostic characters found in the humerus to identify desmostylian genus. These characters can be used to identify isolated desmostylian humeri at the genus level, contributing to a better understanding of the stratigraphic and geographic distributions of each genus. PMID:29134151

Development and Evaluation of a Three-Tier Diagnostic Test to Assess Undergraduate Primary Teachers' Understanding of Ecological Footprint

NASA Astrophysics Data System (ADS)

Liampa, Vasiliki; Malandrakis, George N.; Papadopoulou, Penelope; Pnevmatikos, Dimitrios

2017-08-01

This study focused on the development and validation of a three-tier multiple-choice diagnostic instrument about the ecological footprint. Each question in the three-tier test comprised by; (a) the content tier, assessing content knowledge; (b) the reason tier, assessing explanatory knowledge; and (c) the confidence tier that differentiates lack of knowledge from misconception through the use of a certainty response index. Based on the literature, the propositional knowledge statements and the identified misconceptions of 97 student-teachers, a first version of the test was developed and subsequently administered to another group of 219 student-teachers from Primary and Early Childhood Education Departments. Due to the complexity of the ecological footprint concept, and that it is a newly introduced concept, unknown to the public, both groups have been previously exposed to relevant instruction. Experts in the field established face and content validity. The reliability, in terms of Cronbach's alpha, was found adequate (α = 0.839), and the test-retest reliability, as indicated by Pearson r, was also satisfactory (0.554). The mean performance of the students was 56.24% in total score, 59.75% in content tiers and 48.05% in reason tiers. A variety of concepts about the ecological footprint were also observed. The test can help educators to understand the alternative views that students hold about the ecological footprint concept and assist them in developing the concept through appropriately designed teaching methods and materials.

[Management accounting in hospital setting].

PubMed

Brzović, Z; Richter, D; Simunić, S; Bozić, R; Hadjina, N; Piacun, D; Harcet, B

1998-12-01

The periodic income and expenditure accounts produced at the hospital and departmental level enable successful short term management, but, in the long run do not help remove tensions between health care demand and limited resources, nor do they enable optimal medical planning within the limited financial resources. We are trying to estabilish disease category costs based on case mixing according to diagnostic categories (diagnosis related groups, DRG, or health care resource groups, HRG) and calculation of hospital standard product costs, e.g., radiology cost, preoperative nursing cost etc. The average DRG cost is composed of standard product costs plus any costs specific to a diagnostic category. As an example, current costing procedure for hip artheroplasty in the University Hospital Center Zagreb is compared to the management accounting approach based on British Health Care Resource experience. The knowledge of disease category costs based on management accounting requirements facilitates the implementation of medical programs within the given financial resources and devolves managerial responsibility closer to the clinical level where medical decisions take place.

Knowledge and practice regarding dengue and chikungunya: a cross-sectional study among Healthcare workers and community in Northern Tanzania.

PubMed

Kajeguka, Debora C; Desrochers, Rachelle E; Mwangi, Rose; Mgabo, Maseke R; Alifrangis, Michael; Kavishe, Reginald A; Mosha, Franklin W; Kulkarni, Manisha A

2017-05-01

To investigate knowledge and prevention practices regarding dengue and chikungunya amongst community members, as well as knowledge, treatment and diagnostic practices among healthcare workers. We conducted a cross-sectional survey with 125 community members and 125 healthcare workers from 13 health facilities in six villages in the Hai district of Tanzania. A knowledge score was generated based on participant responses to a structured questionnaire, with a score of 40 or higher (of 80 and 50 total scores for community members and healthcare workers, respectively) indicating good knowledge. We conducted qualitative survey (n = 40) to further assess knowledge and practice regarding dengue and chikungunya fever. 15.2% (n = 19) of community members had good knowledge regarding dengue, whereas 53.6%, (n = 67) of healthcare workers did. 20.3% (n = 16) of participants from lowland areas and 6.5% (n = 3) from highland areas had good knowledge of dengue (χ 2 = 4.25, P = 0.03). Only 2.4% (n = 3) of all participants had a good knowledge score for chikungunya. In the qualitative study, community members expressed uncertainty about dengue and chikungunya. Some healthcare workers thought that they were new diseases. There is insufficient knowledge regarding dengue and chikungunya fever among community members and healthcare workers. Health promotion activities on these diseases based on Ecological Health Mode components to increase knowledge and improve preventive practices should be developed. © 2017 John Wiley & Sons Ltd.

A Prototype of Pilot Knowledge Evaluation by an Intelligent CAI (Computer -Aided Instruction) System Using a Bayesian Diagnostic Model.

DTIC Science & Technology

1987-06-01

to a field of research called Computer-Aided Instruction (CAI). CAI is a powerful methodology for enhancing the overall quaiity and effectiveness of...provides a very powerful tool for statistical inference, especially when pooling informations from different source is appropriate. Thus. prior...04 , 2 ’ .. ."k, + ++ ,,;-+-,..,,..v ->’,0,,.’ I The power of the model lies in its ability to adapt a diagnostic session to the level of knowledge

Early resident-to-resident physics education in diagnostic radiology.

PubMed

Kansagra, Akash P

2014-01-01

The revised ABR board certification process has updated the method by which diagnostic radiology residents are evaluated for competency in clinical radiologic physics. In this work, the author reports the successful design and implementation of a resident-taught physics course consisting of 5 weekly, hour-long lectures intended for incoming first-year radiology residents in their first month of training. To the author's knowledge, this is the first description of a course designed to provide a very early framework for ongoing physics education throughout residency without increasing the didactic burden on faculty members. Twenty-six first-year residents spanning 2 academic years took the course and reported subjective improvement in their knowledge (90%) and interest (75%) in imaging physics and a high level of satisfaction with the use of senior residents as physics educators. Based on the success of this course and the minimal resources required for implementation, this work may serve as a blueprint for other radiology residency programs seeking to develop revised physics curricula. Copyright © 2014 American College of Radiology. Published by Elsevier Inc. All rights reserved.

CO2 exposure as translational cross-species experimental model for panic.

PubMed

Leibold, N K; van den Hove, D L A; Viechtbauer, W; Buchanan, G F; Goossens, L; Lange, I; Knuts, I; Lesch, K P; Steinbusch, H W M; Schruers, K R J

2016-09-06

The current diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders are being challenged by the heterogeneity and the symptom overlap of psychiatric disorders. Therefore, a framework toward a more etiology-based classification has been initiated by the US National Institute of Mental Health, the research domain criteria project. The basic neurobiology of human psychiatric disorders is often studied in rodent models. However, the differences in outcome measurements hamper the translation of knowledge. Here, we aimed to present a translational panic model by using the same stimulus and by quantitatively comparing the same outcome measurements in rodents, healthy human subjects and panic disorder patients within one large project. We measured the behavioral-emotional and bodily response to CO2 exposure in all three samples, allowing for a reliable cross-species comparison. We show that CO2 exposure causes a robust fear response in terms of behavior in mice and panic symptom ratings in healthy volunteers and panic disorder patients. To improve comparability, we next assessed the respiratory and cardiovascular response to CO2, demonstrating corresponding respiratory and cardiovascular effects across both species. This project bridges the gap between basic and human research to improve the translation of knowledge between these disciplines. This will allow significant progress in unraveling the etiological basis of panic disorder and will be highly beneficial for refining the diagnostic categories as well as treatment strategies.

CO2 exposure as translational cross-species experimental model for panic

PubMed Central

Leibold, N K; van den Hove, D L A; Viechtbauer, W; Buchanan, G F; Goossens, L; Lange, I; Knuts, I; Lesch, K P; Steinbusch, H W M; Schruers, K R J

2016-01-01

The current diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders are being challenged by the heterogeneity and the symptom overlap of psychiatric disorders. Therefore, a framework toward a more etiology-based classification has been initiated by the US National Institute of Mental Health, the research domain criteria project. The basic neurobiology of human psychiatric disorders is often studied in rodent models. However, the differences in outcome measurements hamper the translation of knowledge. Here, we aimed to present a translational panic model by using the same stimulus and by quantitatively comparing the same outcome measurements in rodents, healthy human subjects and panic disorder patients within one large project. We measured the behavioral–emotional and bodily response to CO2 exposure in all three samples, allowing for a reliable cross-species comparison. We show that CO2 exposure causes a robust fear response in terms of behavior in mice and panic symptom ratings in healthy volunteers and panic disorder patients. To improve comparability, we next assessed the respiratory and cardiovascular response to CO2, demonstrating corresponding respiratory and cardiovascular effects across both species. This project bridges the gap between basic and human research to improve the translation of knowledge between these disciplines. This will allow significant progress in unraveling the etiological basis of panic disorder and will be highly beneficial for refining the diagnostic categories as well as treatment strategies. PMID:27598969

Approach to the critically ill camelid.

PubMed

Bedenice, Daniela

2009-07-01

The estimation of fluid deficits in camelids is challenging. However, early recognition and treatment of shock and hypovolemia is instrumental to improve morbidity and mortality of critically ill camelids. Early goal-directed fluid therapy requires specific knowledge of clinical indicators of hypovolemia and assessment of resuscitation endpoints, but may significantly enhance the understanding, monitoring, and safety of intravenous fluid therapy in South American camelids (SAC). It is important to recognize that over-aggressive fluid resuscitation is just as detrimental as under resuscitation. Nonetheless, a protocol of conservative fluid management is often indicated in the treatment of camelids with pulmonary inflammation, to counteract edema formation. The early recognition of lung dysfunction is often based on advanced diagnostic techniques, including arterial blood gas analysis, diagnostic imaging, and noninvasive pulmonary function testing.

Machine Learning Approach to Extract Diagnostic and Prognostic Thresholds: Application in Prognosis of Cardiovascular Mortality

PubMed Central

Mena, Luis J.; Orozco, Eber E.; Felix, Vanessa G.; Ostos, Rodolfo; Melgarejo, Jesus; Maestre, Gladys E.

2012-01-01

Machine learning has become a powerful tool for analysing medical domains, assessing the importance of clinical parameters, and extracting medical knowledge for outcomes research. In this paper, we present a machine learning method for extracting diagnostic and prognostic thresholds, based on a symbolic classification algorithm called REMED. We evaluated the performance of our method by determining new prognostic thresholds for well-known and potential cardiovascular risk factors that are used to support medical decisions in the prognosis of fatal cardiovascular diseases. Our approach predicted 36% of cardiovascular deaths with 80% specificity and 75% general accuracy. The new method provides an innovative approach that might be useful to support decisions about medical diagnoses and prognoses. PMID:22924062

Biomedical visual data analysis to build an intelligent diagnostic decision support system in medical genetics.

PubMed

Kuru, Kaya; Niranjan, Mahesan; Tunca, Yusuf; Osvank, Erhan; Azim, Tayyaba

2014-10-01

In general, medical geneticists aim to pre-diagnose underlying syndromes based on facial features before performing cytological or molecular analyses where a genotype-phenotype interrelation is possible. However, determining correct genotype-phenotype interrelationships among many syndromes is tedious and labor-intensive, especially for extremely rare syndromes. Thus, a computer-aided system for pre-diagnosis can facilitate effective and efficient decision support, particularly when few similar cases are available, or in remote rural districts where diagnostic knowledge of syndromes is not readily available. The proposed methodology, visual diagnostic decision support system (visual diagnostic DSS), employs machine learning (ML) algorithms and digital image processing techniques in a hybrid approach for automated diagnosis in medical genetics. This approach uses facial features in reference images of disorders to identify visual genotype-phenotype interrelationships. Our statistical method describes facial image data as principal component features and diagnoses syndromes using these features. The proposed system was trained using a real dataset of previously published face images of subjects with syndromes, which provided accurate diagnostic information. The method was tested using a leave-one-out cross-validation scheme with 15 different syndromes, each of comprised 5-9 cases, i.e., 92 cases in total. An accuracy rate of 83% was achieved using this automated diagnosis technique, which was statistically significant (p<0.01). Furthermore, the sensitivity and specificity values were 0.857 and 0.870, respectively. Our results show that the accurate classification of syndromes is feasible using ML techniques. Thus, a large number of syndromes with characteristic facial anomaly patterns could be diagnosed with similar diagnostic DSSs to that described in the present study, i.e., visual diagnostic DSS, thereby demonstrating the benefits of using hybrid image processing and ML-based computer-aided diagnostics for identifying facial phenotypes. Copyright © 2014. Published by Elsevier B.V.

Improving the Performance of the Structure-Based Connectionist Network for Diagnosis of Helicopter Gearboxes

NASA Technical Reports Server (NTRS)

Jammu, Vinay B.; Danai, Koroush; Lewicki, David G.

1996-01-01

A diagnostic method is introduced for helicopter gearboxes that uses knowledge of the gear-box structure and characteristics of the 'features' of vibration to define the influences of faults on features. The 'structural influences' in this method are defined based on the root mean square value of vibration obtained from a simplified lumped-mass model of the gearbox. The structural influences are then converted to fuzzy variables, to account for the approximate nature of the lumped-mass model, and used as the weights of a connectionist network. Diagnosis in this Structure-Based Connectionist Network (SBCN) is performed by propagating the abnormal vibration features through the weights of SBCN to obtain fault possibility values for each component in the gearbox. Upon occurrence of misdiagnoses, the SBCN also has the ability to improve its diagnostic performance. For this, a supervised training method is presented which adapts the weights of SBCN to minimize the number of misdiagnoses. For experimental evaluation of the SBCN, vibration data from a OH-58A helicopter gearbox collected at NASA Lewis Research Center is used. Diagnostic results indicate that the SBCN is able to diagnose about 80% of the faults without training, and is able to improve its performance to nearly 100% after training.

Applications of antibodies in microfluidics-based analytical systems: challenges and strategies for success

NASA Astrophysics Data System (ADS)

O’Kennedy, Richard; Fitzgerald, Jenny; Cassedy, Arabelle; Crawley, Aoife; Zhang, Xin; Carrera, Sandro

2018-06-01

This review is designed to focus on antibodies and the attributes that make them ideal for applications in microfluidics-based diagnostic/separation platforms. The structures of different antibody formats and how they can be engineered to be highly effective in microfluidics-based environments will be highlighted. Suggested novel stratagems on the ideal way in which they can be employed in microfluidics systems, based on an informed knowledge of their structures and properties rather than random choice selection, as is often currently employed, will be provided. Finally, a critical assessment of current shortcomings in the approaches used along with possible ways for their resolution will be given.

Lack of knowledge and availability of diagnostic equipment could hinder the diagnosis of sarcopenia and its management.

PubMed

Reijnierse, Esmee M; de van der Schueren, Marian A E; Trappenburg, Marijke C; Doves, Marjan; Meskers, Carel G M; Maier, Andrea B

2017-01-01

Sarcopenia is an emerging clinical challenge in an ageing population and is associated with serious negative health outcomes. This study aimed to assess the current state of the art regarding the knowledge about the concept of sarcopenia and practice of the diagnostic strategy and management of sarcopenia in a cohort of Dutch healthcare professionals (physicians, physiotherapists, dietitians and others) attending a lecture cycle on sarcopenia. This longitudinal study included Dutch healthcare professionals (n = 223) who were asked to complete a questionnaire before, directly after and five months after (n = 80) attending a lecture cycle on the pathophysiology of sarcopenia, diagnostic strategy and management of sarcopenia, i.e. interventions and collaboration. Before attendance, 69.7% of healthcare professionals stated to know the concept of sarcopenia, 21.4% indicated to know how to diagnose sarcopenia and 82.6% had treated patients with suspected sarcopenia. 47.5% used their clinical view as diagnostic strategy. Handgrip strength was the most frequently used objective diagnostic measure (33.9%). Five months after attendance, reported use of diagnostic tests was increased, i.e. handgrip strength up to 67.4%, gait speed up to 72.1% and muscle mass up to 20.9%. Bottlenecks during implementation of the diagnostic strategy were experienced by 67.1%; lack of awareness among other healthcare professionals, acquisition of equipment and time constraints to perform the diagnostic measures were reported most often. Before attendance, 36.4% stated not to consult a physiotherapists or exercise therapists (PT/ET) or dietitian for sarcopenia interventions, 10.5% consulted a PT/ET, 32.7% a dietitian and 20.5% both a PT/ET and dietitian. Five months after attendance, these percentages were 28.3%, 21.7%, 30.0% and 20.0% respectively. The concept of sarcopenia is familiar to most Dutch healthcare professionals but application in practice is hampered, mostly by lack of knowledge, availability of equipment, time constraints and lack of collaboration.

Lack of knowledge and availability of diagnostic equipment could hinder the diagnosis of sarcopenia and its management

PubMed Central

Reijnierse, Esmee M.; de van der Schueren, Marian A. E.; Trappenburg, Marijke C.; Doves, Marjan; Meskers, Carel G. M.

2017-01-01

Objectives Sarcopenia is an emerging clinical challenge in an ageing population and is associated with serious negative health outcomes. This study aimed to assess the current state of the art regarding the knowledge about the concept of sarcopenia and practice of the diagnostic strategy and management of sarcopenia in a cohort of Dutch healthcare professionals (physicians, physiotherapists, dietitians and others) attending a lecture cycle on sarcopenia. Material and methods This longitudinal study included Dutch healthcare professionals (n = 223) who were asked to complete a questionnaire before, directly after and five months after (n = 80) attending a lecture cycle on the pathophysiology of sarcopenia, diagnostic strategy and management of sarcopenia, i.e. interventions and collaboration. Results Before attendance, 69.7% of healthcare professionals stated to know the concept of sarcopenia, 21.4% indicated to know how to diagnose sarcopenia and 82.6% had treated patients with suspected sarcopenia. 47.5% used their clinical view as diagnostic strategy. Handgrip strength was the most frequently used objective diagnostic measure (33.9%). Five months after attendance, reported use of diagnostic tests was increased, i.e. handgrip strength up to 67.4%, gait speed up to 72.1% and muscle mass up to 20.9%. Bottlenecks during implementation of the diagnostic strategy were experienced by 67.1%; lack of awareness among other healthcare professionals, acquisition of equipment and time constraints to perform the diagnostic measures were reported most often. Before attendance, 36.4% stated not to consult a physiotherapists or exercise therapists (PT/ET) or dietitian for sarcopenia interventions, 10.5% consulted a PT/ET, 32.7% a dietitian and 20.5% both a PT/ET and dietitian. Five months after attendance, these percentages were 28.3%, 21.7%, 30.0% and 20.0% respectively. Conclusion The concept of sarcopenia is familiar to most Dutch healthcare professionals but application in practice is hampered, mostly by lack of knowledge, availability of equipment, time constraints and lack of collaboration. PMID:28968456

Exploring Ways to Provide Diagnostic Feedback with an ESL Placement Test: Cognitive Diagnostic Assessment of L2 Reading Ability

ERIC Educational Resources Information Center

Kim, Ah-Young

2015-01-01

Previous research in cognitive diagnostic assessment (CDA) of L2 reading ability has been frequently conducted using large-scale English proficiency exams (e.g., TOEFL, MELAB). Using CDA, it is possible to analyze individual learners' strengths and weaknesses in multiple attributes (i.e., knowledge, skill, strategy) measured at the item level.…

Research Reports from the First Pre-ICME Satellite Conference on Diagnostic and Prescriptive Mathematics (Monash University, Melbourne, Australia, August 21-22, 1984).

ERIC Educational Resources Information Center

Blane, Dudley, Ed.

Provided are the papers presented at a conference which served as an international forum on diagnostic and prescriptive mathematics education. They are: (1) "The Evolution of the Research Council for Diagnostic and Prescriptive Mathematics" by Robert Underhill; (2) "The Interaction of Knowledge and Cognitive Processes in Diagnosis…

Pneumothorax, pneumomediastinum, pneumoperitoneum, pneumoretroperitoneum and subcutaneous emphysema following diagnostic colonoscopy.

PubMed

Marwan, K; Farmer, K C; Varley, C; Chapple, K S

2007-07-01

Colonic perforation is an unusual complication of colonoscopy. We present a case of pneumothorax, pneumomediastinum, pneumoperitoneum and extensive subcutaneous emphysema resulting from a diagnostic colonoscopy. To our knowledge, only two such cases have been described previously.

Diagnostic imaging of the nasolacrimal drainage system. Part I. Radiological anatomy of lacrimal pathways. Physiology of tear secretion and tear outflow.

PubMed

Maliborski, Artur; Różycki, Radosław

2014-04-17

Excessive watering of the eye is a common condition in ophthalmological practice. It may be the result of excessive production of tear fluid or obstruction and insufficiency of efferent tear pathways. The differentiation between obstruction and insufficiency of the lacrimal pathways is still clinically questionable. In the diagnostic process it is necessary to perform clinical tests and additional diagnostic imaging is often needed. Dacryocystography, with or without the extension of the dynamic phase or subtraction option, still remains the criterion standard for diagnostic imaging of the lacrimal obstruction. It may help to clarify the cause and exact place of the obstruction and provide information for further management, especially surgical treatment. Increasingly, new techniques are used in diagnostic imaging of the lacrimal tract, such as computed tomography, magnetic resonance, and isotopic methods. Adequate knowledge of the anatomy and physiology of the lacrimal system and the secretion and outflow of tears is the basis for proper diagnostic imaging. The purpose of this paper is to present the exact anatomy of the lacrimal system, with particular emphasis on the radiological anatomy and the current state of knowledge about the physiology of tear secretion and drainage.

How do gut feelings feature in tutorial dialogues on diagnostic reasoning in GP traineeship?

PubMed

Stolper, C F; Van de Wiel, M W J; Hendriks, R H M; Van Royen, P; Van Bokhoven, M A; Van der Weijden, T; Dinant, G J

2015-05-01

Diagnostic reasoning is considered to be based on the interaction between analytical and non-analytical cognitive processes. Gut feelings, a specific form of non-analytical reasoning, play a substantial role in diagnostic reasoning by general practitioners (GPs) and may activate analytical reasoning. In GP traineeships in the Netherlands, trainees mostly see patients alone but regularly consult with their supervisors to discuss patients and problems, receive feedback, and improve their competencies. In the present study, we examined the discussions of supervisors and their trainees about diagnostic reasoning in these so-called tutorial dialogues and how gut feelings feature in these discussions. 17 tutorial dialogues focussing on diagnostic reasoning were video-recorded and transcribed and the protocols were analysed using a detailed bottom-up and iterative content analysis and coding procedure. The dialogues were segmented into quotes. Each quote received a content code and a participant code. The number of words per code was used as a unit of analysis to quantitatively compare the contributions to the dialogues made by supervisors and trainees, and the attention given to different topics. The dialogues were usually analytical reflections on a trainee's diagnostic reasoning. A hypothetico-deductive strategy was often used, by listing differential diagnoses and discussing what information guided the reasoning process and might confirm or exclude provisional hypotheses. Gut feelings were discussed in seven dialogues. They were used as a tool in diagnostic reasoning, inducing analytical reflection, sometimes on the entire diagnostic reasoning process. The emphasis in these tutorial dialogues was on analytical components of diagnostic reasoning. Discussing gut feelings in tutorial dialogues seems to be a good educational method to familiarize trainees with non-analytical reasoning. Supervisors need specialised knowledge about these aspects of diagnostic reasoning and how to deal with them in medical education.

Reducing a Knowledge-Base Search Space When Data Are Missing

NASA Technical Reports Server (NTRS)

James, Mark

2007-01-01

This software addresses the problem of how to efficiently execute a knowledge base in the presence of missing data. Computationally, this is an exponentially expensive operation that without heuristics generates a search space of 1 + 2n possible scenarios, where n is the number of rules in the knowledge base. Even for a knowledge base of the most modest size, say 16 rules, it would produce 65,537 possible scenarios. The purpose of this software is to reduce the complexity of this operation to a more manageable size. The problem that this system solves is to develop an automated approach that can reason in the presence of missing data. This is a meta-reasoning capability that repeatedly calls a diagnostic engine/model to provide prognoses and prognosis tracking. In the big picture, the scenario generator takes as its input the current state of a system, including probabilistic information from Data Forecasting. Using model-based reasoning techniques, it returns an ordered list of fault scenarios that could be generated from the current state, i.e., the plausible future failure modes of the system as it presently stands. The scenario generator models a Potential Fault Scenario (PFS) as a black box, the input of which is a set of states tagged with priorities and the output of which is one or more potential fault scenarios tagged by a confidence factor. The results from the system are used by a model-based diagnostician to predict the future health of the monitored system.

X-ray Imaging and preliminary studies of the X-ray self-emission from an innovative plasma-trap based on the Bernstein waves heating mechanism

NASA Astrophysics Data System (ADS)

Caliri, C.; Romano, F. P.; Mascali, D.; Gammino, S.; Musumarra, A.; Castro, G.; Celona, L.; Neri, L.; Altana, C.

2013-10-01

Electron Cyclotron Resonance Ion Sources (ECRIS) are based on ECR heated plasmas emitting high fluxes of X-rays. Here we illustrate a pilot study of the X-ray emission from a compact plasma-trap in which an off-resonance microwave-plasma interaction has been attempted, highlighting a possible Bernstein-Waves based heating mechanism. EBWs-heating is obtained via the inner plasma EM-to-ES wave conversion and enables to reach densities much larger than the cut-off ones. At LNS-INFN, an innovative diagnostic technique based on the design of a Pinhole Camera (PHC) coupled to a CCD device for X-ray Imaging of the plasma (XRI) has been developed, in order to integrate X-ray traditional diagnostics (XRS). The complementary use of electrostatic probes measurements and X-ray diagnostics enabled us to gain knowledge about the high energy electrons density and temperature and about the spatial structure of the source. The combination of the experimental data with appropriate modeling of the plasma-source allowed to estimate the X-ray emission intensity in different energy domains (ranging from EUV up to Hard X-rays). The use of ECRIS as X-ray source for multidisciplinary applications, is now a concrete perspective due to the intense fluxes produced by the new plasma heating mechanism.

Using a web-based system for the continuous distance education in cytopathology.

PubMed

Stergiou, Nikolaos; Georgoulakis, Giannis; Margari, Niki; Aninos, Dionisios; Stamataki, Melina; Stergiou, Efi; Pouliakis, Abraam; Karakitsos, Petros

2009-12-01

The evolution of information technologies and telecommunications has made the World Wide Web a low cost and easily accessible tool for the dissemination of information and knowledge. Continuous Medical Education (CME) sites dedicated in cytopathology field are rather poor, they do not succeed in following the constant changes and lack the ability of providing cytopathologists with a dynamic learning environment, adaptable to the development of cytopathology. Learning methods including skills such as decision making, reasoning and problem solving are critical in the development of such a learning environment. The objectives of this study are (1) to demonstrate on the basis of a web-based training system the successful application of traditional learning theories and methods and (2) to effectively evaluate users' perception towards the educational program, using a combination of observers, theories and methods. Trainees are given the opportunity to browse through the educational material, collaborate in synchronous and asynchronous mode, practice their skills through problems and tasks and test their knowledge using the self-evaluation tool. On the other hand, the trainers are responsible for editing learning material, attending students' progress and organizing the problem-based and task-based scenarios. The implementation of the web-based training system is based on the three-tier architecture and uses an Apache Tomcat web server and a MySQL database server. By December 2008, CytoTrainer's learning environment contains two courses in cytopathology: Gynaecological Cytology and Thyroid Cytology offering about 2000 digital images and 20 case sessions. Our evaluation method is a combination of both qualitative and quantitative approaches to explore how the various parts of the system and students' attitudes work together. Trainees approved of the course's content, methodology and learning activities. The triangulation of evaluation methods revealed that the training program is suitable for the continuous distance education in cytopathology and that it has improved the trainees' skills in diagnostic cytopathology. The web-based training system can be successfully involved in the continuous distance education in cytopathology. It provides the opportunity to access learning material from any place at any time and supports the acquisition of diagnostic knowledge.

Characteristics of binge eating disorder in relation to diagnostic criteria

PubMed Central

Wilfley, Denise E; Citrome, Leslie; Herman, Barry K

2016-01-01

The objective of this review was to examine the evidentiary basis for binge eating disorder (BED) with reference to the Diagnostic and Statistical Manual of Mental Disorders – Fifth Edition (DSM-5) diagnostic criteria for BED. A PubMed search restricted to titles and abstracts of English-language reviews, meta-analyses, clinical trials, randomized controlled trials, journal articles, and letters using human participants was conducted on August 7, 2015, using keywords that included “binge eating disorder,” DSM-5, DSM-IV, guilt, shame, embarrassment, quantity, psychological, behavior, and “shape and weight concerns.” Of the 257 retrieved publications, 60 publications were considered relevant to discussions related to DSM-5 diagnostic criteria and were included in the current review, and 20 additional references were also included on the basis of the authors’ knowledge and/or on a review of the reference lists from relevant articles obtained through the literature search. Evidence supports the duration/frequency criterion for BED and the primary importance of loss of control and marked distress in identifying individuals with BED. Although overvaluation of shape/weight is not a diagnostic criterion, its relationship to the severity of BED psychopathology may identify a unique subset of individuals with BED. Additionally, individuals with BED often exhibit a clinical profile consisting of psychiatric (eg, mood, obsessive–compulsive, and impulsive disorders) and medical (eg, gastrointestinal symptoms, metabolic syndrome, and type 2 diabetes) comorbidities and behavioral profiles (eg, overconsumption of calories outside of a binge eating episode and emotional eating). Future revisions of the BED diagnostic criteria should consider the inclusion of BED subtypes, perhaps based on the overvaluation of shape/weight, and an evidence-based reassessment of severity criteria. PMID:27621631

Reasoning process characteristics in the diagnostic skills of beginner, competent, and expert dentists.

PubMed

Crespo, Kathleen E; Torres, José E; Recio, María E

2004-12-01

The purpose of this study was to evaluate qualitative differences in the diagnostic reasoning process at different developmental stages of expertise. A qualitative design was used to study cognitive processes that characterize the diagnosis of oral disease at the stages of beginner (five junior students who had passed the NBDE I), competent (five GPR first-year residents), and expert dentists (five general dentists with ten or more years of experience). Individually, each participant was asked to determine the diagnosis of an oral condition based on a written clinical case, using the think aloud technique and retrospective reports. A subsequent interview was conducted to obtain the participants' diagnostic process model and pathophysiology of the case. The analysis of the verbal protocols indicated that experts referred to the patient's sociomedical context more frequently, demonstrated better organization of ideas, could determine key clinical findings, and had an ability to plan for the search of pertinent information. Fewer diagnostic hypotheses were formulated by participants who used forward reasoning, independent of the stage of development. Beginners requested additional diagnostic aids (radiographs, laboratory tests) more frequently than the competent/expert dentists. Experts recalled typical experiences with patients, while competent/beginner dentists recalled information from didactic courses. Experts evidenced cognitive diagnostic schemas that integrate pathophysiology of disease, while competent and beginner participants had not achieved this integration. We conclude that expert performance is a combination of a knowledge base, reasoning skills, and an accumulation of experiences with patients that is qualitatively different from that of competent and beginner dentists. It is important for dental education to emphasize the teaching of cognitive processes and to incorporate a wide variety of clinical experiences in addition to the teaching of disciplinary content.

Impact of knowledge-based iterative model reconstruction on myocardial late iodine enhancement in computed tomography and comparison with cardiac magnetic resonance.

PubMed

Tanabe, Yuki; Kido, Teruhito; Kurata, Akira; Fukuyama, Naoki; Yokoi, Takahiro; Kido, Tomoyuki; Uetani, Teruyoshi; Vembar, Mani; Dhanantwari, Amar; Tokuyasu, Shinichi; Yamashita, Natsumi; Mochizuki, Teruhito

2017-10-01

We evaluated the image quality and diagnostic performance of late iodine enhancement computed tomography (LIE-CT) with knowledge-based iterative model reconstruction (IMR) for the detection of myocardial infarction (MI) in comparison with late gadolinium enhancement magnetic resonance imaging (LGE-MRI). The study investigated 35 patients who underwent a comprehensive cardiac CT protocol and LGE-MRI for the assessment of coronary artery disease. The CT protocol consisted of stress dynamic myocardial CT perfusion, coronary CT angiography (CTA) and LIE-CT using 256-slice CT. LIE-CT scans were acquired 5 min after CTA without additional contrast medium and reconstructed with filtered back projection (FBP), a hybrid iterative reconstruction (HIR), and IMR. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were assessed. Sensitivity and specificity of LIE-CT for detecting MI were assessed according to the 16-segment model. Image quality scores, and diagnostic performance were compared among LIE-CT with FBP, HIR and IMR. Among the 35 patients, 139 of 560 segments showed MI in LGE-MRI. On LIE-CT with FBP, HIR, and IMR, the median SNRs were 2.1, 2.9, and 6.1; and the median CNRs were 1.7, 2.2, and 4.7, respectively. Sensitivity and specificity were 56 and 93% for FBP, 62 and 91% for HIR, and 80 and 91% for IMR. LIE-CT with IMR showed the highest image quality and sensitivity (p < 0.05). The use of IMR enables significant improvement of image quality and diagnostic performance of LIE-CT for detecting MI in comparison with FBP and HIR.

Awareness of allergic enterocolitis among primary-care paediatricians: A web-based pilot survey.

PubMed

Comberiati, P; Landi, M; Martelli, A; Piacentini, G L; Capristo, C; Paiola, G; Peroni, D G

2016-01-01

Allergic enterocolitis, also known as food protein-induced enterocolitis syndrome (FPIES), is an increasingly reported and potentially severe non-IgE mediated food allergy of the first years of life, which is often misdiagnosed due to its non-specific presenting symptoms and lack of diagnostic guidelines. We sought to determine the knowledge of clinical, diagnostic and therapeutic features of FPIES among Italian primary-care paediatricians. A 16-question anonymous web-based survey was sent via email to randomly selected primary care paediatricians working in the north of Italy. There were 194 completed surveys (48.5% response rate). Among respondents, 12.4% declared full understanding of FPIES, 49% limited knowledge, 31.4% had simply heard about FPIES and 7.2% had never heard about it. When presented with clinical anecdotes, 54.1% recognised acute FPIES and 12.9% recognised all chronic FPIES, whereas 10.3% misdiagnosed FPIES as allergic proctocolitis or infantile colic. To diagnose FPIES 55.7% declared to need negative skin prick test or specific-IgE to the trigger food, whereas 56.7% considered necessary a confirmatory oral challenge. Epinephrine was considered the mainstay in treating acute FPIES by 25.8% of respondents. Only 59.8% referred out to an allergist for the long-term reintroduction of the culprit food. Overall, 20.1% reported to care children with FPIES in their practice, with cow's milk formula and fish being the most common triggers; the diagnosis was self-made by the participant in 38.5% of these cases and by an allergist in 48.7%. There is a need for promoting awareness of FPIES to minimise delay in diagnosis and unnecessary diagnostic and therapeutic interventions. Copyright © 2016 SEICAP. Published by Elsevier España, S.L.U. All rights reserved.

Molecular pathogenesis and clinical management of Fanconi anemia

PubMed Central

Kee, Younghoon; D’Andrea, Alan D.

2012-01-01

Fanconi anemia (FA) is a rare genetic disorder associated with a high frequency of hematological abnormalities and congenital anomalies. Based on multilateral efforts from basic scientists and clinicians, significant advances in our knowledge of FA have been made in recent years. Here we review the clinical features, the diagnostic criteria, and the current and future therapies of FA and describe the current understanding of the molecular basis of the disease. PMID:23114602

Pneumothorax, Pneumomediastinum, Pneumoperitoneum, Pneumoretroperitoneum and Subcutaneous Emphysema Following Diagnostic Colonoscopy

PubMed Central

Marwan, K; Farmer, KC; Varley, C; Chapple, KS

2007-01-01

Colonic perforation is an unusual complication of colonoscopy. We present a case of pneumothorax, pneumomediastinum, pneumoperitoneum and extensive subcutaneous emphysema resulting from a diagnostic colonoscopy. To our knowledge, only two such cases have been described previously. PMID:17688713

Diagnostics of the power oil-filled transformer equipment of thermal power plants

NASA Astrophysics Data System (ADS)

Eltyshev, D. K.; Khoroshev, N. I.

2016-08-01

Problems concerning improvement of the diagnostics efficiency of the electrical facilities and functioning of the generation and distribution systems through the examples of the power oil-filled transformers, as the responsible elements referring to the electrical part of thermal power plants (TPP), were considered. Research activity is based on the fuzzy logic system allowing working both with statistical and expert information presented in the form of knowledge accumulated during operation of the power oil-filled transformer facilities. The diagnostic algorithm for various types of transformers, with the use of the intellectual estimation model of its thermal state on the basis of the key diagnostic parameters and fuzzy inference hierarchy, was developed. Criteria for taking measures allowing preventing emergencies in the electric power systems were developed. The fuzzy hierarchical model for the state assessment of the power oil-filled transformers of 110 kV, possessing high degree of credibility and setting quite strict requirements to the limits of variables of the equipment diagnostic parameters, was developed. The most frequent defects of the transformer standard elements, related with the disturbance of the isolation properties and instrumentation operation, were revealed after model testing on the real object. Presented results may be used both for the express diagnostics of the transformers state without disconnection from the power line and for more detailed analysis of the defects causes on the basis of the advanced list of the diagnostic parameters; information on those parameters may be received only after complete or partial disconnection.

Aptamer-Based Methods for Detection of Circulating Tumor Cells and Their Potential for Personalized Diagnostics.

PubMed

Zamay, Anna S; Zamay, Galina S; Kolovskaya, Olga S; Zamay, Tatiana N; Berezovski, Maxim V

2017-01-01

Cancer diagnostics and treatment monitoring rely on sensing and counting of rare cells such as cancer circulating tumor cells (CTCs) in blood. Many analytical techniques have been developed to reliably detect and quantify CTCs using unique physical shape and size of tumor cells and/or distinctive patterns of cell surface biomarkers. Main problems of CTC bioanalysis are in the small number of cells that are present in the circulation and heterogeneity of CTCs. In this chapter, we describe recent progress towards the selection and application of synthetic DNA or RNA aptamers to capture and detect CTCs in blood. Antibody-based approaches for cell isolation and purification are limited because of an antibody's negative effect on cell viability and purity. Aptamers transform cell isolation technology, because they bind and release cells on-demand. The unique feature of anti-CTC aptamers is that the aptamers are selected for cell surface biomarkers in their native state, and conformation without previous knowledge of their biomarkers. Once aptamers are produced, they can be used to identify CTC biomarkers using mass spectrometry. The biomarkers and corresponding aptamers can be exploited to improve cancer diagnostics and therapies .

Role of Genetics in the Etiology of Autistic Spectrum Disorder: Towards a Hierarchical Diagnostic Strategy

PubMed Central

Robert, Cyrille; Pasquier, Laurent; Cohen, David; Fradin, Mélanie; Canitano, Roberto; Damaj, Léna; Odent, Sylvie; Tordjman, Sylvie

2017-01-01

Progress in epidemiological, molecular and clinical genetics with the development of new techniques has improved knowledge on genetic syndromes associated with autism spectrum disorder (ASD). The objective of this article is to show the diversity of genetic disorders associated with ASD (based on an extensive review of single-gene disorders, copy number variants, and other chromosomal disorders), and consequently to propose a hierarchical diagnostic strategy with a stepwise evaluation, helping general practitioners/pediatricians and child psychiatrists to collaborate with geneticists and neuropediatricians, in order to search for genetic disorders associated with ASD. The first step is a clinical investigation involving: (i) a child psychiatric and psychological evaluation confirming autism diagnosis from different observational sources and assessing autism severity; (ii) a neuropediatric evaluation examining neurological symptoms and developmental milestones; and (iii) a genetic evaluation searching for dysmorphic features and malformations. The second step involves laboratory and if necessary neuroimaging and EEG studies oriented by clinical results based on clinical genetic and neuropediatric examinations. The identification of genetic disorders associated with ASD has practical implications for diagnostic strategies, early detection or prevention of co-morbidity, specific treatment and follow up, and genetic counseling. PMID:28287497

Role of Genetics in the Etiology of Autistic Spectrum Disorder: Towards a Hierarchical Diagnostic Strategy.

PubMed

Robert, Cyrille; Pasquier, Laurent; Cohen, David; Fradin, Mélanie; Canitano, Roberto; Damaj, Léna; Odent, Sylvie; Tordjman, Sylvie

2017-03-12

Progress in epidemiological, molecular and clinical genetics with the development of new techniques has improved knowledge on genetic syndromes associated with autism spectrum disorder (ASD). The objective of this article is to show the diversity of genetic disorders associated with ASD (based on an extensive review of single-gene disorders, copy number variants, and other chromosomal disorders), and consequently to propose a hierarchical diagnostic strategy with a stepwise evaluation, helping general practitioners/pediatricians and child psychiatrists to collaborate with geneticists and neuropediatricians, in order to search for genetic disorders associated with ASD. The first step is a clinical investigation involving: (i) a child psychiatric and psychological evaluation confirming autism diagnosis from different observational sources and assessing autism severity; (ii) a neuropediatric evaluation examining neurological symptoms and developmental milestones; and (iii) a genetic evaluation searching for dysmorphic features and malformations. The second step involves laboratory and if necessary neuroimaging and EEG studies oriented by clinical results based on clinical genetic and neuropediatric examinations. The identification of genetic disorders associated with ASD has practical implications for diagnostic strategies, early detection or prevention of co-morbidity, specific treatment and follow up, and genetic counseling.

[Expert systems and automatic diagnostic systems in histopathology--a review].

PubMed

Tamai, S

1999-02-01

In this decade, the pathological information system has gradually been settled in many hospitals in Japan. Pathological reports and images are now digitized and managed in the database, and are referred by clinicians at the peripherals. Tele-pathology is also developing; and its users are increasing. However, in many occasions, the problem solving in diagnostic pathology is completely dependent on the solo-pathologist. Considering the need for timely and efficient supports to the solo-pathologist, I reviewed the papers on the knowledge-based interactive expert systems. The interpretations of the histopathological images are dependent on the pathologist, and these expert systems have been evaluated as "educational". With the view of the success in the cytological screening, the development of "image-analysis-based" automatic "histopathological image" classifier has been on ongoing challenges. Our 3 years experience of the development of the pathological image classifier using the artificial neural networks technology is briefly presented. This classifier provides us a "fitting rate" for the individual diagnostic pattern of the breast tumors, such as "fibroadenoma pattern". The diagnosis assisting system with computer technology should provide pathologists, especially solo-pathologists, a useful tool for the quality assurance and improvement of pathological diagnosis.

Lyme disease

PubMed Central

Henry, Bonnie; Crabtree, Alexis; Roth, David; Blackman, Doug; Morshed, Muhammad

2012-01-01

Abstract Objective To determine physicians’ level of awareness and knowledge of Lyme disease (LD) in a low-prevalence area and whether physicians’ practices align with current guidelines for treatment of LD. Design A 23-item questionnaire assessing demographic characteristics, general knowledge about LD, laboratory testing for LD, and responses to 3 clinical scenarios. Setting British Columbia (BC). Participants Pediatricians, FPs, and internal medicine specialists who were licensed to practise in BC. Main outcome measures Knowledge of signs and symptoms of LD, beliefs about risk of LD, attitudes toward LD in patients in their practices, and application of accepted practice guidelines for the treatment of LD in clinical scenarios. Results Overall, 80.6% of respondents were FPs. Average knowledge score was 72.5% for FPs and 75.0% for other specialists. Most respondents (75.6% of FPs and 71.8% of other specialists) underestimated the occurrence of erythema migrans (EM), and only 26.1% and 28.3%, respectively, knew that EM alone was diagnostic for LD. A total of 30.5% of FPs and 12.1% of other specialists reported having treated a patient for the disease despite not believing that the patient had LD. Of all the respondents, 62.1% knew that LD was a reportable disease in BC. Respondents’ reports of risk of LD in their areas were appropriately associated with actual risk based on ecological niche. Conclusion Physicians are knowledgeable about the clinical signs and symptoms of LD and aware of the risk of the disease despite being in a low-endemic area. Physicians in BC are comfortable with treating patients empirically for LD. Education is needed to inform physicians that EM is diagnostic and no laboratory testing is indicated before treatment. Raising awareness among physicians that LD is reportable might improve reporting of future cases. PMID:22734172

[New physiopathological knowledge applied to migraine therapy and prophylaxis].

PubMed

Visens, Laura S

2014-01-01

Migraine is a very common condition that has a significant socioeconomic impact. Based on the most recent reports from the World Health Organization, its diagnosis and treatment are far from being optimal. Specialists have made great efforts to classify headaches, including migraines, in order to have a useful diagnostic tool and to guide treatment. On the other hand, advances made in the knowledge of the pathophysiology of migraines, new treatment options were developed. These new options include onabotulinum toxin A and topiramate. The prompt detection of migraine disorders and an appropriate treatment, both symptomatic and preventive, are key to relieve the personal, familiar, and social burden with special focus on chronic migraine.

Elicitation of neurological knowledge with argument-based machine learning.

PubMed

Groznik, Vida; Guid, Matej; Sadikov, Aleksander; Možina, Martin; Georgiev, Dejan; Kragelj, Veronika; Ribarič, Samo; Pirtošek, Zvezdan; Bratko, Ivan

2013-02-01

The paper describes the use of expert's knowledge in practice and the efficiency of a recently developed technique called argument-based machine learning (ABML) in the knowledge elicitation process. We are developing a neurological decision support system to help the neurologists differentiate between three types of tremors: Parkinsonian, essential, and mixed tremor (comorbidity). The system is intended to act as a second opinion for the neurologists, and most importantly to help them reduce the number of patients in the "gray area" that require a very costly further examination (DaTSCAN). We strive to elicit comprehensible and medically meaningful knowledge in such a way that it does not come at the cost of diagnostic accuracy. To alleviate the difficult problem of knowledge elicitation from data and domain experts, we used ABML. ABML guides the expert to explain critical special cases which cannot be handled automatically by machine learning. This very efficiently reduces the expert's workload, and combines expert's knowledge with learning data. 122 patients were enrolled into the study. The classification accuracy of the final model was 91%. Equally important, the initial and the final models were also evaluated for their comprehensibility by the neurologists. All 13 rules of the final model were deemed as appropriate to be able to support its decisions with good explanations. The paper demonstrates ABML's advantage in combining machine learning and expert knowledge. The accuracy of the system is very high with respect to the current state-of-the-art in clinical practice, and the system's knowledge base is assessed to be very consistent from a medical point of view. This opens up the possibility to use the system also as a teaching tool. Copyright © 2012 Elsevier B.V. All rights reserved.

Diagnostics Research and Development Resources | Resources | CDP

Cancer.gov

The Cancer Diagnosis Program strives to improve the diagnosis and assessment of cancer by effectively moving new scientific knowledge into clinical practice. This national program stimulates, coordinates and funds resources and research for the development of innovative in vitro diagnostics, novel diagnostic technologies and appropriate human specimens in order to better characterize cancers and allow improved medical decision making and evaluation of response to treatment.

Functional reasoning in diagnostic problem solving

NASA Technical Reports Server (NTRS)

Sticklen, Jon; Bond, W. E.; Stclair, D. C.

1988-01-01

This work is one facet of an integrated approach to diagnostic problem solving for aircraft and space systems currently under development. The authors are applying a method of modeling and reasoning about deep knowledge based on a functional viewpoint. The approach recognizes a level of device understanding which is intermediate between a compiled level of typical Expert Systems, and a deep level at which large-scale device behavior is derived from known properties of device structure and component behavior. At this intermediate functional level, a device is modeled in three steps. First, a component decomposition of the device is defined. Second, the functionality of each device/subdevice is abstractly identified. Third, the state sequences which implement each function are specified. Given a functional representation and a set of initial conditions, the functional reasoner acts as a consequence finder. The output of the consequence finder can be utilized in diagnostic problem solving. The paper also discussed ways in which this functional approach may find application in the aerospace field.

Gold nanoshelled liquid perfluorocarbon nanocapsules for combined dual modal ultrasound/CT imaging and photothermal therapy of cancer.

PubMed

Ke, Hengte; Yue, Xiuli; Wang, Jinrui; Xing, Sen; Zhang, Qian; Dai, Zhifei; Tian, Jie; Wang, Shumin; Jin, Yushen

2014-03-26

The integration of multimodal contrast-enhanced diagnostic imaging and therapeutic capabilities could utilize imaging guided therapy to plan the treatment strategy based on the diagnostic results and to guide/monitor the therapeutic procedures. Herein, gold nanoshelled perfluorooctylbromide (PFOB) nanocapsules with PEGylation (PGsP NCs) are constructed by oil-in-water emulsion method to form polymeric PFOB nanocapsules, followed by the formation of PEGylated gold nanoshell on the surface. PGsP NCs could not only provide excellent contrast enhancement for dual modal ultrasound and CT imaging in vitro and in vivo, but also serve as efficient photoabsorbers for photothermal ablation of tumors on xenografted nude mouse model. To our best knowledge, this is the first report of gold nanoshell serving as both CT contrast agents and photoabsorbers for photothermal therapy. The novel multifunctional nanomedicine would be of great value to offer more comprehensive diagnostic information to guide more accurate and effective cancer therapy. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Meta-analysis of diagnostic tests accounting for disease prevalence: a new model using trivariate copulas.

PubMed

Hoyer, A; Kuss, O

2015-05-20

In real life and somewhat contrary to biostatistical textbook knowledge, sensitivity and specificity (and not only predictive values) of diagnostic tests can vary with the underlying prevalence of disease. In meta-analysis of diagnostic studies, accounting for this fact naturally leads to a trivariate expansion of the traditional bivariate logistic regression model with random study effects. In this paper, a new model is proposed using trivariate copulas and beta-binomial marginal distributions for sensitivity, specificity, and prevalence as an expansion of the bivariate model. Two different copulas are used, the trivariate Gaussian copula and a trivariate vine copula based on the bivariate Plackett copula. This model has a closed-form likelihood, so standard software (e.g., SAS PROC NLMIXED) can be used. The results of a simulation study have shown that the copula models perform at least as good but frequently better than the standard model. The methods are illustrated by two examples. Copyright © 2015 John Wiley & Sons, Ltd.

Evidence and evidence gaps - an introduction.

PubMed

Dreier, Gabriele; Löhler, Jan

2016-01-01

Background: Medical treatment requires the implementation of existing evidence in the decision making process in order to be able to find the best possible diagnostic, therapeutic or prognostic measure for the individual patient based on the physician's own expertise. Clinical trials form the evidence base and ideally, their results are assembled, analyzed, summarized, and made available in systematic review articles. Beside planning, conducting, and evaluating clinical trials in conformity with GCP (good clinical practice), it is essential that all results of conducted studies are publicly available in order to avoid publication bias. This includes also the public registration of planned and cancelled trials. History: During the last 25 years, evidence-based medicine became increasingly important in medical care and research. It is closely associated with the names of Archibald Cochrane and David Sackett. About 15 years ago, the Deutsche Cochrane Zentrum (Cochrane Germany) and the Deutsche Netzwerk Evidenzbasierte Medizin e.V. (German Network for Evidence-based Medicine, DNEbM) were founded in Germany. In the International Cochrane Collaboration, clinicians and methodologists come together on an interdisciplinary level to further develop methods of evidence-based medicine and to discuss the topics of evidence generation and processing as well as knowledge transfer. Problem: Evidence is particularly important for physicians in the process of decision making, however, at the same time it is the base of a scientific proof of benefit for the patient and finally for the payers in health care. The closure of evidence gaps requires enormously high staff and financial resources, significant organizational efforts, and it is only successful when clinical and methodical expertise as well as specific knowledge in the field of clinical research are included. On the other hand, the knowledge has to be transferred into practice. For this purpose, practice guidelines, meetings, databases, information portals with processed evidence as well as specific journals and finally teaching are appropriate vehicles. One problem is the multitude of information so that knowledge gaps may affect the clinical routine despite actually existing evidence. Generally, it still takes several years until new knowledge is implemented in daily routine. Tasks: The German Society of Oto-Rhino-Laryngology, Head and Neck Surgery (Deutsche Gesellschaft für Hals-, Nasen- und Ohren-Heilkunde, Kopf- und Hals-Chirurgie e.V., DGHNOKHC) and the Professional Association of Otolaryngologists (Deutscher Berufsverband der HNO-Ärzte e.V., BVHNO) have fundamental interest in supporting their members in generating, processing, and providing evidence as well as accompanying knowledge transfer. It encompasses the fields of diagnostics, therapy, and prognosis in the same way as prevention and applies to medicinal products as well as to medical devices or surgical procedures. The base for this is the regular assessment of evidence gaps, also in the area of established procedures, that has to be followed by a prioritization of research questions and the subsequent initiation of clinical research. In addition, large trials verifying therapies and diagnostics, for example in the context of daily conditions after approval, can only be conducted combining all resources in the ENT community. Method, results, and outlook: Together, the executive committees of the DGHNOKHC and the BVHNO founded the German Study Center of Oto-Rhino-Laryngology, Head and Neck Surgery (Deutsches Studienzentrum für Hals-, Nasen- und Ohren-Heilkunde, Kopf- und Hals-Chirurgie, DSZ-HNO). First projects have been initiated, among those a clinical trial on the therapy of sudden hearing loss supported by the BMBF and a survey on evidence gaps in oto-rhino-laryngology. It seems to be both reasonable and feasible to make available methodological expertise via such an infrastructure of a study center for physicians in hospitals and private practices in order to support clinical research and to implement the principles of evidence-based medicine in daily routine.

Improving the understanding of schistosomiasis among adolescents in endemic areas in Brazil: A comparison of educational methods.

PubMed

Gazzinelli, Maria Flávia; Lobato, Lucas; Andrade, Gisele; Matoso, Leonardo Ferreira; Diemert, David J; Gazzinelli, Andréa

2016-10-01

To evaluate the effectiveness of two teaching strategies, both guided by the concept of dialogicity, on adolescents' knowledge about schistosomiasis and adherence to diagnostic fecal testing. Two teaching strategies related to schistosomiasis were developed, an educational video and group conversation, which were tested in two groups of students aged 10-15 years old. Before and after the intervention, a questionnaire was applied to assess participants' knowledge about schistosomiasis and, after the intervention, two fecal samples were requested from each participant. Comparisons were performed by paired t- and McNemar tests. Both strategies resulted in statistically significant improvements in knowledge between the pre- and post-tests. Students who watched the video had a higher return rate of fecal samples and percentage of correct questionnaire answers, mainly on questions about schistosomiasis infection. Teaching strategies based on dialogue favored the construction of concepts about schistosomiasis that can influence the adoption of positives attitudes related to health. Using teaching strategies based on the concept of dialogicity can favor the increase of knowledge of school age children about schistosomiasis and can influence behavioral change related to health. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Improving the Understanding of Schistosomiasis among Adolescents in Endemic Areas in Brazil: a Comparison of Educational Methods

PubMed Central

Gazzinelli, Maria Flávia; Lobato, Lucas; Andrade, Gisele; Matoso, Leonardo Ferreira; Diemert, David J.; Gazzinelli, Andréa

2016-01-01

Objective To evaluate the effectiveness of two teaching strategies, both guided by the concept of dialogicity, on adolescents’ knowledge about schistosomiasis and adherence to diagnostic fecal testing. Methods Two teaching strategies related to schistosomiasis were developed, an educational video and group conversation, which were tested in two groups of students aged 10–15 years old. Before and after the intervention, a questionnaire was applied to assess participants' knowledge about schistosomiasis and, after the intervention, two fecal samples were requested from each participant. Comparisons were performed by paired t- and McNemar tests. Results Both strategies resulted in statistically significant improvements in knowledge between the pre- and post-tests. Students who watched the video had a higher return rate of fecal samples and percentage of correct questionnaire answers, mainly on questions about schistosomiasis infection. Conclusion teaching strategies based on dialogue favored the construction of concepts about schistosomiasis that can influence the adoption of positives attitudes related to health. Practical Implications Using teaching strategies based on the concept of dialogicity can favor the increase of knowledge of school age children about schistosomiasis and can influence behavioral change related to health. PMID:27180618

Disseminating sexually transmitted infections diagnostics information: the SDI web publication review series.

PubMed

Kuypers, J; Tam, M R; Holmes, K K; Peeling, R W

2006-12-01

The World Health Organization Sexually Transmitted Diseases Diagnostics Initiative (SDI) website publication review seeks to provide health care providers in all geographic and economic settings with timely, critical, and concise information concerning new developments in laboratory and field diagnosis of sexually transmitted infections (STI). Since 2003, the website (www.who.int/std_diagnostics/literature_reviews) has disseminated information in the form of annotated abstracts and commentaries on articles covering studies of STI laboratory-based and rapid assays that are commercially available or under development. Articles identified through searches of PubMed, specific journals, and by referrals from Editorial Board members are selected for inclusion if they meet pre-specified criteria. The objectives, methods, results, and conclusions for each article are summarised and board members are invited to prepare commentaries addressing study design and applicability of findings to end users. Currently, 91 STI diagnostics experts from 17 countries on six continents serve on the Editorial Board. Twelve quarterly issues have been posted that include summaries of 214 original and 17 review articles published from January 2002 through March 2005, with expert commentaries on 153 articles. Interest in the site has increased every year. In 2005, over 36 700 unique visitors from more than 100 countries viewed over 75,000 pages of information. The SDI Publication Review series has the potential to contribute to SDI's goal of improving care for patients with STI by increasing knowledge and awareness of STI diagnostics. Given the proliferation of internet-based STI testing services, this website may be broadened to meet the needs of a wider range of users.

Diagnostic performance and useful findings of ultrasound re-evaluation for patients with equivocal CT features of acute appendicitis.

PubMed

Kim, Mi Sung; Kwon, Heon-Ju; Kang, Kyung A; Do, In-Gu; Park, Hee-Jin; Kim, Eun Young; Hong, Hyun Pyo; Choi, Yoon Jung; Kim, Young Hwan

2018-02-01

To evaluate the diagnostic performance of ultrasound and to determine which ultrasound findings are useful to differentiate appendicitis from non-appendicitis in patients who underwent ultrasound re-evaluation owing to equivocal CT features of acute appendicitis. 62 patients who underwent CT examinations for suspected appendicitis followed by ultrasound re-evaluation owing to equivocal CT findings were included. Equivocal CT findings were considered based on the presence of only one or two findings among the CT criteria, and ultrasound re-evaluation was done based on a predefined structured report form. The diagnostic performance of ultrasound and independent variables to discriminate appendicitis from non-appendicitis were assessed. There were 27 patients in the appendicitis group. The overall diagnostic performance of ultrasound re-evaluation was sensitivity of 96.3%, specificity of 91.2% and accuracy of 91.9%. In terms of the performance of individual ultrasound findings, probe-induced tenderness showed the highest accuracy (86.7%) with sensitivity of 74% and specificity of 97%, followed by non-compressibility (accuracy 71.7%, sensitivity 85.2% and specificity 60.6%). The independent ultrasound findings for discriminating appendicitis were non-compressibility (p = 0.002) and increased flow on the appendiceal wall (p = 0.001). Ultrasound re-evaluation can be used to improve diagnostic accuracy in cases with equivocal CT features for diagnosing appendicitis. The presence of non-compressibility and increased vascular flow on the appendix wall are useful ultrasound findings to discriminate appendicitis from non-appendicitis. Advances in knowledge: Ultrasound re-evaluation is useful to discriminate appendicitis from non-appendicitis when CT features are inconclusive.

Portuguese Family Physicians’ Awareness of Diagnostic and Laboratory Test Costs: A Cross-Sectional Study

PubMed Central

Sá, Luísa; Costa-Santos, Cristina; Teixeira, Andreia; Couto, Luciana; Costa-Pereira, Altamiro; Hespanhol, Alberto; Santos, Paulo; Martins, Carlos

2015-01-01

Background Physicians’ ability to make cost-effective decisions has been shown to be affected by their knowledge of health care costs. This study assessed whether Portuguese family physicians are aware of the costs of the most frequently prescribed diagnostic and laboratory tests. Methods A cross-sectional study was conducted in a representative sample of Portuguese family physicians, using computer-assisted telephone interviews for data collection. A Likert scale was used to assess physician’s level of agreement with four statements about health care costs. Family physicians were also asked to estimate the costs of diagnostic and laboratory tests. Each physician’s cost estimate was compared with the true cost and the absolute error was calculated. Results One-quarter (24%; 95% confidence interval: 23%–25%) of all cost estimates were accurate to within 25% of the true cost, with 55% (95% IC: 53–56) overestimating and 21% (95% IC: 20–22) underestimating the true actual cost. The majority (76%) of family physicians thought they did not have or were uncertain as to whether they had adequate knowledge of diagnostic and laboratory test costs, and only 7% reported receiving adequate education. The majority of the family physicians (82%) said that they had adequate access to information about the diagnostic and laboratory test costs. Thirty-three percent thought that costs did not influence their decision to order tests, while 27% were uncertain. Conclusions Portuguese family physicians have limited awareness of diagnostic and laboratory test costs, and our results demonstrate a need for improved education in this area. Further research should focus on identifying whether interventions in cost knowledge actually change ordering behavior, in identifying optimal methods to disseminate cost information, and on improving the cost-effectiveness of care. PMID:26356625

CLIPS: A tool for corn disease diagnostic system and an aid to neural network for automated knowledge acquisition

NASA Technical Reports Server (NTRS)

Wu, Cathy; Taylor, Pam; Whitson, George; Smith, Cathy

1990-01-01

This paper describes the building of a corn disease diagnostic expert system using CLIPS, and the development of a neural expert system using the fact representation method of CLIPS for automated knowledge acquisition. The CLIPS corn expert system diagnoses 21 diseases from 52 symptoms and signs with certainty factors. CLIPS has several unique features. It allows the facts in rules to be broken down to object-attribute-value (OAV) triples, allows rule-grouping, and fires rules based on pattern-matching. These features combined with the chained inference engine result to a natural user query system and speedy execution. In order to develop a method for automated knowledge acquisition, an Artificial Neural Expert System (ANES) is developed by a direct mapping from the CLIPS system. The ANES corn expert system uses the same OAV triples in the CLIPS system for its facts. The LHS and RHS facts of the CLIPS rules are mapped into the input and output layers of the ANES, respectively; and the inference engine of the rules is imbedded in the hidden layer. The fact representation by OAC triples gives a natural grouping of the rules. These features allow the ANES system to automate rule-generation, and make it efficient to execute and easy to expand for a large and complex domain.

Determining the pregnancy status of patients before diagnostic nuclear medicine procedures: the Australian experience.

PubMed

James, Daphne J; Cardew, Paul; Warren-Forward, Helen M

2011-09-01

Ionizing radiation used in diagnostic nuclear medicine procedures has the potential to have biologic effects on a fetus. Nuclear medicine technologists (NMTs) therefore have a responsibility to ensure that they question all patients of childbearing age about their pregnancy status before starting any procedure, to avoid unnecessary fetal irradiation. In Australia, there are no clearly defined practice guidelines to assist NMTs in determining whom to question or how to question their patients. Semistructured interviews were conducted with chief NMTs and staff NMTs in 8 nuclear medicine departments in Australia. Questions were based around 5 areas: regulations and policy, fetal radiation exposure, questioning of the patient, difficulties in determining pregnancy status, and the impact of the use of hybrid imaging. Audio files of the interviews were transcribed and coded. Topics were coded into 5 themes: policy and awareness of guidelines, questioning the patient, radiation knowledge, decisions and assumptions made by NMTs, and the use of pregnancy testing. There was a wide variation in practice between and within departments. NMTs demonstrated a lack of knowledge and awareness of the possible biologic effects of radiation. This study identified a need in Australia for nuclear medicine to arrive at a consensus approach to verifying a patient's pregnancy status so that NMTs can successfully question patients about their pregnancy status. Continuing education programs are also required to keep NMTs up to date in their knowledge.

In vivo study of the effectiveness of quantitative percussion diagnostics as an indicator of the level of structural pathology of teeth after restoration.

PubMed

Sheets, Cherilyn G; Wu, Jean C; Rashad, Samer; Phelan, Michael; Earthman, James C

2017-02-01

Conventional diagnostic aids based upon imagery and patient symptoms do not indicate whether restorative treatments have eliminated structural pathology. The purpose of this clinical study was to evaluate quantitative percussion diagnostics (QPD), a mechanics-based methodology that tests the structural integrity of teeth noninvasively. The study hypothesis was that QPD would provide knowledge of the structural instability of teeth after restorative work. Eight participants with 60 sites needing restoration were enrolled in an IRB-approved clinical study. Each participant was examined comprehensively, including QPD testing. Each site was disassembled and microscopically video documented, and the results were recorded on a defect assessment sheet. A predictive model was developed for the pathology rating based on normalized fit error (NFE) values using data from the before treatment phase of the study published previously. Each restored site was then tested using QPD. The mean change in NFE values after restoration was evaluated by the pathology rating before treatment. The model was then used to predictively classify the rating after restoration based on the NFE values after treatment. The diagnostic potential of the rating was explored as a marker for risk of pathology after restoration. After restoration, 51 of the 60 sites fell below an NFE of 0.04, representing a greatly stabilized tooth site sample group. Several sites remained in the high-risk category and some increased in pathologic micromovement. Two models were used to determine severity with indicative cutoff points to group sites with similar values. The data support the hypothesis that QPD can indicate a revised level of structural instability of teeth after restoration. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Diagnostic decision-making and strategies to improve diagnosis.

PubMed

Thammasitboon, Satid; Cutrer, William B

2013-10-01

A significant portion of diagnostic errors arises through cognitive errors resulting from inadequate knowledge, faulty data gathering, and/or faulty verification. Experts estimate that 75% of diagnostic failures can be attributed to clinician diagnostic thinking failure. The cognitive processes that underlie diagnostic thinking of clinicians are complex and intriguing, and it is imperative that clinicians acquire explicit appreciation and application of different cognitive approaches to make decisions better. A dual-process model that unifies many theories of decision-making has emerged as a promising template for understanding how clinicians think and judge efficiently in a diagnostic reasoning process. The identification and implementation of strategies for decreasing or preventing such diagnostic errors has become a growing area of interest and research. Suggested strategies to decrease diagnostic error incidence include increasing clinician's clinical expertise and avoiding inherent cognitive errors to make decisions better. Implementing Interventions focused solely on avoiding errors may work effectively for patient safety issues such as medication errors. Addressing cognitive errors, however, requires equal effort on expanding the individual clinician's expertise. Providing cognitive support to clinicians for robust diagnostic decision-making serves as the final strategic target for decreasing diagnostic errors. Clinical guidelines and algorithms offer another method for streamlining decision-making and decreasing likelihood of cognitive diagnostic errors. Addressing cognitive processing errors is undeniably the most challenging task in reducing diagnostic errors. While many suggested approaches exist, they are mostly based on theories and sciences in cognitive psychology, decision-making, and education. The proposed interventions are primarily suggestions and very few of them have been tested in the actual practice settings. Collaborative research effort is required to effectively address cognitive processing errors. Researchers in various areas, including patient safety/quality improvement, decision-making, and problem solving, must work together to make medical diagnosis more reliable. © 2013 Mosby, Inc. All rights reserved.

A diagnostic expert system for aircraft generator control unit (GCU)

NASA Astrophysics Data System (ADS)

Ho, Ting-Long; Bayles, Robert A.; Havlicsek, Bruce L.

The modular VSCF (variable-speed constant-frequency) generator families are described as using standard modules to reduce the maintenance cost and to improve the product's testability. A general diagnostic expert system shell that guides troubleshooting of modules or line replaceable units (LRUs) is introduced. An application of the diagnostic system to a particular LRU, the generator control unit (GCU) is reported. The approach to building the diagnostic expert system is first to capture general diagnostic strategy in an expert system shell. This shell can be easily applied to different devices or LRUs by writing rules to capture only additional device-specific diagnostic information from expert repair personnel. The diagnostic system has the necessary knowledge embedded in its programs and exhibits expertise to troubleshoot the GCU.

Pattern Search in Multi-structure Data: A Framework for the Next-Generation Evidence-based Medicine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sukumar, Sreenivas R; Ainsworth, Keela C

With the advent of personalized and evidence-based medicine, the need for a framework to analyze/interpret quantitative measurements (blood work, toxicology, etc.) with qualitative descriptions (specialist reports after reading images, bio-medical knowledge-bases) to predict diagnostic risks is fast emerging. Addressing this need, we pose and address the following questions (i) How can we jointly analyze both qualitative and quantitative data ? (ii) Is the fusion of multi-structure data expected to provide better insights than either of them individually ? We present experiments on two bio-medical data sets - mammography and traumatic brain studies to demonstrate architectures and tools for evidence-pattern search.

Blueprint for the Diagnosis of Difficulties with Cardinality.

ERIC Educational Resources Information Center

Dunlap, William P.; Brennen, Alison H.

1981-01-01

The article describes a diagnostic procedure for assessing children's mental images and knowledge of cardinal numbers, 0 through 9. The diagnostic procedure includes the assessment of a child's visual memory, visual perception, symbol recognition, oral naming of numerals, and symbol-set linkage. (Author/SBH)

Presentation of Diagnostic Information to Doctors May Change Their Interpretation and Clinical Management: A Web-Based Randomised Controlled Trial

PubMed Central

Ben-Shlomo, Yoav; Collin, Simon M.; Quekett, James; Sterne, Jonathan A. C.; Whiting, Penny

2015-01-01

Background There is little evidence on how best to present diagnostic information to doctors and whether this makes any difference to clinical management. We undertook a randomised controlled trial to see if different data presentations altered clinicians’ decision to further investigate or treat a patient with a fictitious disorder (“Green syndrome”) and their ability to determine post-test probability. Methods We recruited doctors registered with the United Kingdom’s largest online network for medical doctors between 10 July and 6” November 2012. Participants were randomised to one of four arms: (a) text summary of sensitivity and specificity, (b) Fagan’s nomogram, (c) probability-modifying plot (PMP), (d) natural frequency tree (NFT). The main outcome measure was the decision whether to treat, not treat or undertake a brain biopsy on the hypothetical patient and the correct post-test probability. Secondary outcome measures included knowledge of diagnostic tests. Results 917 participants attempted the survey and complete data were available from 874 (95.3%). Doctors randomized to the PMP and NFT arms were more likely to treat the patient than those randomized to the text-only arm. (ORs 1.49, 95% CI 1.02, 2.16) and 1.43, 95% CI 0.98, 2.08 respectively). More patients randomized to the PMP (87/218–39.9%) and NFT (73/207–35.3%) arms than the nomogram (50/194–25.8%) or text only (30/255–11.8%) arms reported the correct post-test probability (p <0.001). Younger age, postgraduate training and higher self-rated confidence all predicted better knowledge performance. Doctors with better knowledge were more likely to view an optional learning tutorial (OR per correct answer 1.18, 95% CI 1.06, 1.31). Conclusions Presenting diagnostic data using a probability-modifying plot or natural frequency tree influences the threshold for treatment and improves interpretation of tests results compared to text summary of sensitivity and specificity or Fagan’s nomogram. PMID:26147744

The Interaction between Surface Color and Color Knowledge: Behavioral and Electrophysiological Evidence

ERIC Educational Resources Information Center

Bramao, Ines; Faisca, Luis; Forkstam, Christian; Inacio, Filomena; Araujo, Susana; Petersson, Karl Magnus; Reis, Alexandra

2012-01-01

In this study, we used event-related potentials (ERPs) to evaluate the contribution of surface color and color knowledge information in object identification. We constructed two color-object verification tasks--a surface and a knowledge verification task--using high color diagnostic objects; both typical and atypical color versions of the same…

Screening and assessment of chronic pain among children with cerebral palsy: a process evaluation of a pain toolbox.

PubMed

Orava, Taryn; Provvidenza, Christine; Townley, Ashleigh; Kingsnorth, Shauna

2018-06-08

Though high numbers of children with cerebral palsy experience chronic pain, it remains under-recognized. This paper describes an evaluation of implementation supports and adoption of the Chronic Pain Assessment Toolbox for Children with Disabilities (the Toolbox) to enhance pain screening and assessment practices within a pediatric rehabilitation and complex continuing care hospital. A multicomponent knowledge translation strategy facilitated Toolbox adoption, inclusive of a clinical practice guideline, cerebral palsy practice points and assessment tools. Across the hospital, seven ambulatory care clinics with cerebral palsy caseloads participated in a staggered roll-out (Group 1: exclusive CP caseloads, March-December; Group 2: mixed diagnostic caseloads, August-December). Evaluation measures included client electronic medical record audit, document review and healthcare provider survey and interviews. A significant change in documentation of pain screening and assessment practice from pre-Toolbox (<2%) to post-Toolbox adoption (53%) was found. Uptake in Group 2 clinics lagged behind Group 1. Opportunities to use the Toolbox consistently (based on diagnostic caseload) and frequently (based on client appointments) were noted among contextual factors identified. Overall, the Toolbox was positively received and clinically useful. Findings affirm that the Toolbox, in conjunction with the application of integrated knowledge translation principles and an established knowledge translation framework, has potential to be a useful resource to enrich and standardize chronic pain screening and assessment practices among children with cerebral palsy. Implications for Rehabilitation It is important to engage healthcare providers in the conceptualization, development, implementation and evaluation of a knowledge-to-action best practice product. The Chronic Pain Toolbox for Children with Disabilities provides rehabilitation staff with guidance on pain screening and assessment best practice and offers a range of validated tools that can be incorporated in ambulatory clinic settings to meet varied client needs. Considering unique clinical contexts (i.e., opportunities for use, provider engagement, staffing absences/turnover) is required to optimize and sustain chronic pain screening and assessment practices in rehabilitation outpatient settings.

Radiation safety.

PubMed

Skinner, Sarah

2013-06-01

Diagnostic radiology procedures, such as computed tomography (CT) and X-ray, are an increasing source of ionising radiation exposure to our community. Exposure to ionising radiation is associated with increased risk of malignancy, proportional to the level of exposure. Every diagnostic test using ionising radiation needs to be justified by clinical need. General practitioners need a working knowledge of radiation safety so they can adequately inform their patients of the risks and benefits of diagnostic imaging procedures.

Object knowledge modulates colour appearance.

PubMed

Witzel, Christoph; Valkova, Hanna; Hansen, Thorsten; Gegenfurtner, Karl R

2011-01-01

We investigated the memory colour effect for colour diagnostic artificial objects. Since knowledge about these objects and their colours has been learned in everyday life, these stimuli allow the investigation of the influence of acquired object knowledge on colour appearance. These investigations are relevant for questions about how object and colour information in high-level vision interact as well as for research about the influence of learning and experience on perception in general. In order to identify suitable artificial objects, we developed a reaction time paradigm that measures (subjective) colour diagnosticity. In the main experiment, participants adjusted sixteen such objects to their typical colour as well as to grey. If the achromatic object appears in its typical colour, then participants should adjust it to the opponent colour in order to subjectively perceive it as grey. We found that knowledge about the typical colour influences the colour appearance of artificial objects. This effect was particularly strong along the daylight axis.

Object knowledge modulates colour appearance

PubMed Central

Witzel, Christoph; Valkova, Hanna; Hansen, Thorsten; Gegenfurtner, Karl R

2011-01-01

We investigated the memory colour effect for colour diagnostic artificial objects. Since knowledge about these objects and their colours has been learned in everyday life, these stimuli allow the investigation of the influence of acquired object knowledge on colour appearance. These investigations are relevant for questions about how object and colour information in high-level vision interact as well as for research about the influence of learning and experience on perception in general. In order to identify suitable artificial objects, we developed a reaction time paradigm that measures (subjective) colour diagnosticity. In the main experiment, participants adjusted sixteen such objects to their typical colour as well as to grey. If the achromatic object appears in its typical colour, then participants should adjust it to the opponent colour in order to subjectively perceive it as grey. We found that knowledge about the typical colour influences the colour appearance of artificial objects. This effect was particularly strong along the daylight axis. PMID:23145224

Exploring cognitive integration of basic science and its effect on diagnostic reasoning in novices.

PubMed

Lisk, Kristina; Agur, Anne M R; Woods, Nicole N

2016-06-01

Integration of basic and clinical science knowledge is increasingly being recognized as important for practice in the health professions. The concept of 'cognitive integration' places emphasis on the value of basic science in providing critical connections to clinical signs and symptoms while accounting for the fact that clinicians may not spontaneously articulate their use of basic science knowledge in clinical reasoning. In this study we used a diagnostic justification test to explore the impact of integrated basic science instruction on novices' diagnostic reasoning process. Participants were allocated to an integrated basic science or clinical science training group. The integrated basic science group was taught the clinical features along with the underlying causal mechanisms of four musculoskeletal pathologies while the clinical science group was taught only the clinical features. Participants completed a diagnostic accuracy test immediately after initial learning, and one week later a diagnostic accuracy and justification test. The results showed that novices who learned the integrated causal mechanisms had superior diagnostic accuracy and better understanding of the relative importance of key clinical features. These findings further our understanding of cognitive integration by providing evidence of the specific changes in clinical reasoning when basic and clinical sciences are integrated during learning.

NESTOR: A Computer-Based Medical Diagnostic Aid That Integrates Causal and Probabilistic Knowledge.

DTIC Science & Technology

1984-11-01

indiidual conditional probabilities between one cause node and its effect node, but less common to know a joint conditional probability between a...PERFOAMING ORG. REPORT NUMBER * 7. AUTI4ORs) O Gregory F. Cooper 1 CONTRACT OR GRANT NUMBERIa) ONR N00014-81-K-0004 g PERFORMING ORGANIZATION NAME AND...ADDRESS 10. PROGRAM ELEMENT, PROJECT. TASK Department of Computer Science AREA & WORK UNIT NUMBERS Stanford University Stanford, CA 94305 USA 12. REPORT

Navigating highly homologous genes in a molecular diagnostic setting: a resource for clinical next-generation sequencing.

PubMed

Mandelker, Diana; Schmidt, Ryan J; Ankala, Arunkanth; McDonald Gibson, Kristin; Bowser, Mark; Sharma, Himanshu; Duffy, Elizabeth; Hegde, Madhuri; Santani, Avni; Lebo, Matthew; Funke, Birgit

2016-12-01

Next-generation sequencing (NGS) is now routinely used to interrogate large sets of genes in a diagnostic setting. Regions of high sequence homology continue to be a major challenge for short-read technologies and can lead to false-positive and false-negative diagnostic errors. At the scale of whole-exome sequencing (WES), laboratories may be limited in their knowledge of genes and regions that pose technical hurdles due to high homology. We have created an exome-wide resource that catalogs highly homologous regions that is tailored toward diagnostic applications. This resource was developed using a mappability-based approach tailored to current Sanger and NGS protocols. Gene-level and exon-level lists delineate regions that are difficult or impossible to analyze via standard NGS. These regions are ranked by degree of affectedness, annotated for medical relevance, and classified by the type of homology (within-gene, different functional gene, known pseudogene, uncharacterized noncoding region). Additionally, we provide a list of exons that cannot be analyzed by short-amplicon Sanger sequencing. This resource can help guide clinical test design, supplemental assay implementation, and results interpretation in the context of high homology.Genet Med 18 12, 1282-1289.

Clinical Assessment and Management of Toddlers With Suspected Autism Spectrum Disorder: Insights From Studies of High-Risk Infants

PubMed Central

Zwaigenbaum, Lonnie; Bryson, Susan; Lord, Catherine; Rogers, Sally; Carter, Alice; Carver, Leslie; Chawarska, Kasia; Constantino, John; Dawson, Geraldine; Dobkins, Karen; Fein, Deborah; Iverson, Jana; Klin, Ami; Landa, Rebecca; Messinger, Daniel; Ozonoff, Sally; Sigman, Marian; Stone, Wendy; Tager-Flusberg, Helen; Yirmiya, Nurit

2010-01-01

With increased public awareness of the early signs and recent American Academy of Pediatrics recommendations that all 18- and 24-month-olds be screened for autism spectrum disorders, there is an increasing need for diagnostic assessment of very young children. However, unique challenges exist in applying current diagnostic guidelines for autism spectrum disorders to children under the age of 2 years. In this article, we address challenges related to early detection, diagnosis, and treatment of autism spectrum disorders in this age group. We provide a comprehensive review of findings from recent studies on the early development of children with autism spectrum disorders, summarizing current knowledge on early signs of autism spectrum disorders, the screening properties of early detection tools, and current best practice for diagnostic assessment of autism spectrum disorders before 2 years of age. We also outline principles of effective intervention for children under the age of 2 with suspected/confirmed autism spectrum disorders. It is hoped that ongoing studies will provide an even stronger foundation for evidence-based diagnostic and intervention approaches for this critically important age group. PMID:19403506

Awareness and Knowledge of Ionizing Radiation Risks Between Prescribed and Self-Presenting Patients for Common Diagnostic Radiological Procedures in Bahrain

PubMed Central

Al-Mallah, Adel; Vaithinathan, Asokan G.; Al-Sehlawi, Mahdi; Al-Mannai, Mariam

2017-01-01

Objectives Between 20 to 50% of medical imaging examinations are considered inappropriate, and unnecessary ionizing radiation exposures may lead to cancer. We hypothesized that Bahraini patients who self-present for ionizing radiation procedures are not aware of, and lack the requisite knowledge of, the inherent risks associated with their use than patients prescribed for diagnostic purposes. We attempted to examine and compare the awareness and knowledge of the associated risks of ionizing radiation in common diagnostic radiological procedures between prescribed and self-presenting patients in Bahrain. Methods A cross-sectional survey was carried out among 416 Bahraini patients attending the radiology department of the Salmaniya Medical Complex (SMC), a secondary health care center, who had been referred by primary care physicians or self-presented to the center. Data was collected via face-to-face interviews. Results Prescribed patients (n = 358) had a better awareness than self-presenting (n = 58) patients on all ionizing radiation awareness statements (i.e., risks, permissible levels, willingness to undergo the procedure, and preference for a clinical examination over a radiological procedure) (p < 0.050). Of the 10 knowledge statements, the prescribed patients agreed on four statements than the self-presenting patients: preventing or minimizing exposure improves health, people can prevent or minimize exposure, a lifelong health concern, and radiological procedures offer best diagnoses compared to medical tests or procedures (p <  0.050). Conclusions Bahraini patients who reported to SMC lack awareness and knowledge on ionizing radiation. The proportion of appropriate responses to awareness and knowledge questions were paltry for self-presenting patients and deficient for the prescribed patients in the knowledge segment alone. PMID:29026468

Informatics in radiology: radiology gamuts ontology: differential diagnosis for the Semantic Web.

PubMed

Budovec, Joseph J; Lam, Cesar A; Kahn, Charles E

2014-01-01

The Semantic Web is an effort to add semantics, or "meaning," to empower automated searching and processing of Web-based information. The overarching goal of the Semantic Web is to enable users to more easily find, share, and combine information. Critical to this vision are knowledge models called ontologies, which define a set of concepts and formalize the relations between them. Ontologies have been developed to manage and exploit the large and rapidly growing volume of information in biomedical domains. In diagnostic radiology, lists of differential diagnoses of imaging observations, called gamuts, provide an important source of knowledge. The Radiology Gamuts Ontology (RGO) is a formal knowledge model of differential diagnoses in radiology that includes 1674 differential diagnoses, 19,017 terms, and 52,976 links between terms. Its knowledge is used to provide an interactive, freely available online reference of radiology gamuts ( www.gamuts.net ). A Web service allows its content to be discovered and consumed by other information systems. The RGO integrates radiologic knowledge with other biomedical ontologies as part of the Semantic Web. © RSNA, 2014.

A systematic evaluation of prevalence and diagnostic accuracy of sacroiliac joint interventions.

PubMed

Simopoulos, Thomas T; Manchikanti, Laxmaiah; Singh, Vijay; Gupta, Sanjeeva; Hameed, Haroon; Diwan, Sudhir; Cohen, Steven P

2012-01-01

The contributions of the sacroiliac joint to low back and lower extremity pain have been a subject of considerable debate and research. It is generally accepted that 10% to 25% of patients with persistent mechanical low back pain below L5 have pain secondary to sacroiliac joint pathology. However, no single historical, physical exam, or radiological feature can definitively establish a diagnosis of sacroiliac joint pain. Based on present knowledge, a proper diagnosis can only be made using controlled diagnostic blocks. The diagnosis and treatment of sacroiliac joint pain continue to be characterized by wide variability and a paucity of the literature. To evaluate the accuracy of diagnostic sacroiliac joint interventions. A systematic review of diagnostic sacroiliac joint interventions. Methodological quality assessment of included studies was performed using Quality Appraisal of Reliability Studies (QAREL). Only diagnostic accuracy studies meeting at least 50% of the designated inclusion criteria were utilized for analysis. Studies scoring less than 50% are presented descriptively and analyzed critically. The level of evidence was classified as good, fair, or poor based on the quality of evidence developed by the United States Preventive Services Task Force (USPSTF). Data sources included relevant literature identified through searches of PubMed and EMBASE from 1966 to December 2011, and manual searches of the bibliographies of known primary and review articles. In this evaluation we utilized controlled local anesthetic blocks using at least 50% pain relief as the reference standard. The evidence is good for the diagnosis of sacroiliac joint pain utilizing controlled comparative local anesthetic blocks. The prevalence of sacroiliac joint pain is estimated to range between 10% and 62% based on the setting; however, the majority of analyzed studies suggest a point prevalence of around 25%, with a false-positive rate for uncontrolled blocks of approximately 20%. The evidence for provocative testing to diagnose sacroiliac joint pain was fair. The evidence for the diagnostic accuracy of imaging is limited. The limitations of this systematic review include a paucity of literature, variations in technique, and variable criterion standards for the diagnosis of sacroiliac joint pain. Based on this systematic review, the evidence for the diagnostic accuracy of sacroiliac joint injections is good, the evidence for provocation maneuvers is fair, and evidence for imaging is limited.

PET/CT with 18F-choline: Physiological whole bio-distribution in male and female subjects and diagnostic pitfalls on 1000 prostate cancer patients: 18F-choline PET/CT bio-distribution and pitfalls. A southern Italian experience.

PubMed

Calabria, Ferdinando; Chiaravalloti, Agostino; Cicciò, Carmelo; Gangemi, Vincenzo; Gullà, Domenico; Rocca, Federico; Gallo, Gianpasquale; Cascini, Giuseppe Lucio; Schillaci, Orazio

2017-08-01

The 11 C/ 18 F-choline is a PET/CT radiopharmaceutical useful in detecting tumors with high lipogenesis. 11 C/ 18 F-choline uptake can occur in physiological conditions or tumors. The knowledge of its bio-distribution is essential to recognize physiologic variants or diagnostic pitfalls. Moreover, few information are available on the bio-distribution of this tracer in female patients. Our aim was to discuss some documented 18 F-choline PET/CT pitfalls in prostate cancer patients. Our secondary aim was to describe the 18 F-choline bio-distribution in the female body. We collected diagnostic pitfalls in three PET centers examining 1000 prostate cancer by 18 F-choline PET/CT. All pitfalls were ensured by follow-up, imaging and/or histology. We also performed whole body 18 F-choline PET/CT in 5 female patients. 169/1000 (16.9%) patients showed pitfalls not owing to prostate cancer. These findings were due to inflammation, benign tumors while, in 1% of examined patients, a concomitant neoplasm was found. In the female body, the breast showed low physiological uptake. The accurate knowledge of 18 F-choline PET/CT bio-distribution and diagnostic pitfalls is essential. Correlative imaging and histological exam are often necessary to depict pitfalls. In women, the uptake in the breast is due to the physiological gradient of 18 F-choline uptake in the exocrine glands. Our results confirm the possibility of 18 F-choline uptake in several diseases other than prostate cancer. However, our experience was acquired on a large population and shows that a conspicuous amount of 18 F-choline diagnostic pitfalls are easily recognizable and attributable to inflammation. A new advance in knowledge is the minimal difference in terms of physiological tracer bio-distribution between male and female patients. The knowledge of the physiological bio-distribution and of the potential pitfalls linked of a tracer could help physicians to choose the best diagnostic and therapeutic approaches for a better patient quality of life. Copyright © 2017 Elsevier Inc. All rights reserved.

[Evaluation of general practitioners' knowledge about diagnostic and therapeuthic management of erysipelas in the city of Marrakech].

PubMed

Ihbibane, Fatima; Arsène, Ntini Lebi; Adarmouch, Latifa; Amine, Mohamed; Tassi, Noura

2018-01-01

Erysipelas is the most common non necrotizing bacterial dermohypodermitis (NNBDH). This study aimed to evaluate the adequacy of general practitioners' knowledge about literature data on the diagnostic and therapeuthic management of erysipelas. We conducted a cross-sectional descriptive and analytical survey of 167 general practitioners in the public and private sectors in Marrakech over the period from 19 May to 20 October 2014. The 114 questionnaires which had been returned revealed that local and general risk factors were often reported for erysipelas. 92 (80.7%) physicians thought that positive diagnosis of common types was based on clinical examination. 97(85.1%) physicians thought that it required only out-patient service and that hospitalization and para-clinical examinations should only be performed in patients with severe, atypical or complicated erysipelas. 25 (21.9%) physicians thought that oral amoxicillin should be the gold standard therapy. 15(13.2%) physicians thought that bi-antibiotic therapy including antistreptococcique molecule should be the gold standard. 16 doctors (14%) advocated anti-inflammatory drugs. The primary and secondary prevention levels generated interest from physicians of whom 108 (94.7%) were favorable to the treatment of the portals of entry in the skin while 53 (46.5%) to the antibioprophylaxis after the second recurrence. Our study highlights that erysipelas is relatively frequent in city medical practice; clinical diagnosis guidelines should be shared between the specialists in order to improve the diagnostic and therapeutic approch of our physicians.

A Real-Time Knowledge Based Expert System For Diagnostic Problem Solving

NASA Astrophysics Data System (ADS)

Esteva, Juan C.; Reynolds, Robert G.

1986-03-01

This paper is a preliminary report of a real-time expert system which is concerned with the detection and diagnosis of electrical deviations in on-board vehicle-based electrical systems. The target systems are being tested at radio frequencies to evaluate their capability to be operated at designed levels of efficiency in an electromagnetic environment. The measurement of this capability is known as ElectroMagnetic Compatibility (EMC). The Intelligent Deviation Diagnosis (IDD) system consists of two basic modules the Automatic Data Acquisition Module (ADAM) and the Diagnosis System (DS). In this paper only the diagnosis system is described.

Diagnosis of helicopter gearboxes using structure-based networks

NASA Technical Reports Server (NTRS)

Jammu, Vinay B.; Danai, Kourosh; Lewicki, David G.

1995-01-01

A connectionist network is introduced for fault diagnosis of helicopter gearboxes that incorporates knowledge of the gearbox structure and characteristics of the vibration features as its fuzzy weights. Diagnosis is performed by propagating the abnormal features of vibration measurements through this Structure-Based Connectionist Network (SBCN), the outputs of which represent the fault possibility values for individual components of the gearbox. The performance of this network is evaluated by applying it to experimental vibration data from an OH-58A helicopter gearbox. The diagnostic results indicate that the network performance is comparable to those obtained from supervised pattern classification.

Concomitant idiopathic hypertrophic spinal pachymeningitis and Guillain-Barré syndrome in a patient: coincidence or a triggering mechanism?

PubMed

Olubajo, Farouk; Yermakova, Tatyana; Highley, J Robin; Arzoglou, Vasileios

2017-09-01

Idiopathic hypertrophic spinal pachymeningitis (IHSP), a rare diffuse inflammatory thickening of the dura mater, and Guillain-Barré syndrome (GBS) are known entities but they have never been reported as concomitant diagnoses. To their knowledge, the authors present the first reported case in the international literature with supportive evidence for both IHSP (based on MRI, intraoperative, and histological findings) and GBS (based on history, clinical examination, and electrophysiological findings). They review the literature on IHSP and the diagnostic criteria for GBS, with the view of identifying a possible causative connection.

Knowledge-base for interpretation of cerebrospinal fluid data patterns. Essentials in neurology and psychiatry.

PubMed

Reiber, Hansotto

2016-06-01

The physiological and biophysical knowledge base for interpretations of cerebrospinal fluid (CSF) data and reference ranges are essential for the clinical pathologist and neurochemist. With the popular description of the CSF flow dependent barrier function, the dynamics and concentration gradients of blood-derived, brain-derived and leptomeningeal proteins in CSF or the specificity-independent functions of B-lymphocytes in brain also the neurologist, psychiatrist, neurosurgeon as well as the neuropharmacologist may find essentials for diagnosis, research or development of therapies. This review may help to replace the outdated ideas like "leakage" models of the barriers, linear immunoglobulin Index Interpretations or CSF electrophoresis. Calculations, Interpretations and analytical pitfalls are described for albumin quotients, quantitation of immunoglobulin synthesis in Reibergrams, oligoclonal IgG, IgM analysis, the polyspecific ( MRZ- ) antibody reaction, the statistical treatment of CSF data and general quality assessment in the CSF laboratory. The diagnostic relevance is documented in an accompaning review.

Knowledge-based image processing for on-off type DNA microarray

NASA Astrophysics Data System (ADS)

Kim, Jong D.; Kim, Seo K.; Cho, Jeong S.; Kim, Jongwon

2002-06-01

This paper addresses the image processing technique for discriminating whether the probes are hybrized with target DNA in the Human Papilloma Virus (HPV) DNA Chip designed for genotyping HPV. In addition to the probes, the HPV DNA chip has markers that always react with the sample DNA. The positions of probe-dots in the final scanned image are fixed relative to the marker-dot locations with a small variation according to the accuracy of the dotter and the scanner. The probes are duplicated 4 times for the diagnostic stability. The prior knowledges such as the maker relative distance and the duplication information of probes is integrated into the template matching technique with the normalized correlation measure. Results show that the employment of both of the prior knowledges is to simply average the template matching measures over the positions of the markers and probes. The eventual proposed scheme yields stable marker locating and probe classification.

Toward detecting deception in intelligent systems

NASA Astrophysics Data System (ADS)

Santos, Eugene, Jr.; Johnson, Gregory, Jr.

2004-08-01

Contemporary decision makers often must choose a course of action using knowledge from several sources. Knowledge may be provided from many diverse sources including electronic sources such as knowledge-based diagnostic or decision support systems or through data mining techniques. As the decision maker becomes more dependent on these electronic information sources, detecting deceptive information from these sources becomes vital to making a correct, or at least more informed, decision. This applies to unintentional disinformation as well as intentional misinformation. Our ongoing research focuses on employing models of deception and deception detection from the fields of psychology and cognitive science to these systems as well as implementing deception detection algorithms for probabilistic intelligent systems. The deception detection algorithms are used to detect, classify and correct attempts at deception. Algorithms for detecting unexpected information rely upon a prediction algorithm from the collaborative filtering domain to predict agent responses in a multi-agent system.

Matrix Failure Modes and Effects Analysis as a Knowledge Base for a Real Time Automated Diagnosis Expert System

NASA Technical Reports Server (NTRS)

Herrin, Stephanie; Iverson, David; Spukovska, Lilly; Souza, Kenneth A. (Technical Monitor)

1994-01-01

Failure Modes and Effects Analysis contain a wealth of information that can be used to create the knowledge base required for building automated diagnostic Expert systems. A real time monitoring and diagnosis expert system based on an actual NASA project's matrix failure modes and effects analysis was developed. This Expert system Was developed at NASA Ames Research Center. This system was first used as a case study to monitor the Research Animal Holding Facility (RAHF), a Space Shuttle payload that is used to house and monitor animals in orbit so the effects of space flight and microgravity can be studied. The techniques developed for the RAHF monitoring and diagnosis Expert system are general enough to be used for monitoring and diagnosis of a variety of other systems that undergo a Matrix FMEA. This automated diagnosis system was successfully used on-line and validated on the Space Shuttle flight STS-58, mission SLS-2 in October 1993.

Basic physiological systems indicator's informative assessment for children and adolescents obesity diagnosis tasks

NASA Astrophysics Data System (ADS)

Marukhina, O. V.; Berestneva, O. G.; Emelyanova, Yu A.; Romanchukov, S. V.; Petrova, L.; Lombardo, C.; Kozlova, N. V.

2018-05-01

The healthcare computerization creates opportunities to the clinical decision support system development. In the course of diagnosis, doctor manipulates a considerable amount of data and makes a decision in the context of uncertainty basing upon the first-hand experience and knowledge. The situation is exacerbated by the fact that the knowledge scope in medicine is incrementally growing, but the decision-making time does not increase. The amount of medical malpractice is growing and it leads to various negative effects, even the mortality rate increase. IT-solution's development for clinical purposes is one of the most promising and efficient ways to prevent these effects. That is why the efforts of many IT specialists are directed to the doctor's heuristics simulating software or expert-based medical decision-making algorithms development. Thus, the objective of this study is to develop techniques and approaches for the body physiological system's informative value assessment index for the obesity degree evaluation based on the diagnostic findings.

Childhood cancer and factors related to prolonged diagnostic intervals: a Danish population-based study

PubMed Central

Ahrensberg, J M; Olesen, F; Hansen, R P; Schrøder, H; Vedsted, P

2013-01-01

Background: Early diagnosis of childhood cancer provides hope for better prognoses. Shorter diagnostic intervals (DI) in primary care require better knowledge of the association between presenting symptoms, interpretation of symptoms and the wording of the referral letter. Methods: A Danish nationwide population-based study. Data on 550 children aged <15 years with an incident cancer diagnosis (January 2007–December 2010) were collected through questionnaires to parents (response rate=69%) and general practitioners (GPs) (response rate=87%). The DI from the first presentation in general practice until diagnosis was categorised as short or long based on quartiles. Associations between variables and long DIs were assessed using logistic regression. Results: The GPs interpreted symptoms as ‘vague' in 25.4%, ‘serious' in 50.0% and ‘alarm' in 19.0% of cases. Symptom interpretation varied by cancer type (P<0.001) and was associated with the DI (P<0.001). Vomiting was associated with a shorter DI for central nervous system (CNS) tumours, and pain with a longer DI for leukaemia. Referral letter wording was associated with DI (P<0.001); the shortest DIs were observed when cancer suspicion was raised in the letter. Conclusion: The GPs play an important role in recognising early signs of childhood cancer as their symptom interpretation and referral wording have a profound impact on the diagnostic process. PMID:23449354

Preliminary investigation into application of problem-based learning in the practical teaching of diagnostics

PubMed Central

Rui, Zeng; Rong-Zheng, Yue; Hong-Yu, Qiu; Jing, Zeng; Xue-Hong, Wan; Chuan, Zuo

2015-01-01

Background Problem-based learning (PBL) is a pedagogical approach based on problems. Specifically, it is a student-centered, problem-oriented teaching method that is conducted through group discussions. The aim of our study is to explore the effects of PBL in diagnostic teaching for Chinese medical students. Methods A prospective, randomized controlled trial was conducted. Eighty junior clinical medical students were randomly divided into two groups. Forty students were allocated to a PBL group and another 40 students were allocated to a control group using the traditional teaching method. Their scores in the practice skills examination, ability to write and analyze medical records, and results on the stage test and behavior observation scale were compared. A questionnaire was administered in the PBL group after class. Results There were no significant differences in scores for writing medical records, content of interviewing, physical examination skills, and stage test between the two groups. However, compared with the control group, the PBL group had significantly higher scores on case analysis, interviewing skills, and behavioral observation scales. Conclusion The questionnaire survey revealed that PBL could improve interest in learning, cultivate an ability to study independently, improve communication and analytical skills, and good team cooperation spirit. However, there were some shortcomings in systematization of imparting knowledge. PBL has an obvious advantage in teaching with regard to diagnostic practice. PMID:25848334

Application of forwardchaining method to diagnosis of onion plant diseases

NASA Astrophysics Data System (ADS)

Sitanggang, Delima; Siregar, Saut D.; Situmeang, Suryani M. F.; Indra, Evta; Sagala, Ayu R.; Sihombing, Oloan; Nababan, Marlince; Pasaribu, Hendra; Damanik, Rudolf R.; Turnip, Mardi; Saragih, Rijois I. E.

2018-04-01

Red Onion is a tuber plant that is widely used by the people of Indonesia, both as herbs and herbal medicines. Onion farmers have limitations in identifying diseases that attack their crops.This disease can cause crop failure against the onion.This design begins with the creation of a knowledge base up to input-output design with forward chaining method. The results of this design can assist farmers in identifying their plant diseases. Based on diagnostic results of several methods that have been done testing can diagnose diseases contained in onion plants. With symptoms data that has been determined by the expert with the value of each symptom is different. As for the symptoms that have been determined that the leaves contain patches with a value of 0.3, White leaf spots value 0.4, Leaf spots form a purple zone if it is severe 0.5, Leaf tip of 0.2, Tubers rot 0.4. Based on the above diagnostic results then get the value of diagnosis 67% forward chaining with trotol disease type, Purple spotting.

XCOM intrinsic dimensionality for low-Z elements at diagnostic energies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bornefalk, Hans

2012-02-15

Purpose: To determine the intrinsic dimensionality of linear attenuation coefficients (LACs) from XCOM for elements with low atomic number (Z = 1-20) at diagnostic x-ray energies (25-120 keV). H{sub 0}{sup q}, the hypothesis that the space of LACs is spanned by q bases, is tested for various q-values. Methods: Principal component analysis is first applied and the LACs are projected onto the first q principal component bases. The residuals of the model values vs XCOM data are determined for all energies and atomic numbers. Heteroscedasticity invalidates the prerequisite of i.i.d. errors necessary for bootstrapping residuals. Instead wild bootstrap is applied,more » which, by not mixing residuals, allows the effect of the non-i.i.d residuals to be reflected in the result. Credible regions for the eigenvalues of the correlation matrix for the bootstrapped LAC data are determined. If subsequent credible regions for the eigenvalues overlap, the corresponding principal component is not considered to represent true data structure but noise. If this happens for eigenvalues l and l + 1, for any l{<=}q, H{sub 0}{sup q} is rejected. Results: The largest value of q for which H{sub 0}{sup q} is nonrejectable at the 5%-level is q = 4. This indicates that the statistically significant intrinsic dimensionality of low-Z XCOM data at diagnostic energies is four. Conclusions: The method presented allows determination of the statistically significant dimensionality of any noisy linear subspace. Knowledge of such significant dimensionality is of interest for any method making assumptions on intrinsic dimensionality and evaluating results on noisy reference data. For LACs, knowledge of the low-Z dimensionality might be relevant when parametrization schemes are tuned to XCOM data. For x-ray imaging techniques based on the basis decomposition method (Alvarez and Macovski, Phys. Med. Biol. 21, 733-744, 1976), an underlying dimensionality of two is commonly assigned to the LAC of human tissue at diagnostic energies. The finding of a higher statistically significant dimensionality thus raises the question whether a higher assumed model dimensionality (now feasible with the advent of multibin x-ray systems) might also be practically relevant, i.e., if better tissue characterization results can be obtained.« less

[Severity classification of chronic obstructive pulmonary disease based on deep learning].

PubMed

Ying, Jun; Yang, Ceyuan; Li, Quanzheng; Xue, Wanguo; Li, Tanshi; Cao, Wenzhe

2017-12-01

In this paper, a deep learning method has been raised to build an automatic classification algorithm of severity of chronic obstructive pulmonary disease. Large sample clinical data as input feature were analyzed for their weights in classification. Through feature selection, model training, parameter optimization and model testing, a classification prediction model based on deep belief network was built to predict severity classification criteria raised by the Global Initiative for Chronic Obstructive Lung Disease (GOLD). We get accuracy over 90% in prediction for two different standardized versions of severity criteria raised in 2007 and 2011 respectively. Moreover, we also got the contribution ranking of different input features through analyzing the model coefficient matrix and confirmed that there was a certain degree of agreement between the more contributive input features and the clinical diagnostic knowledge. The validity of the deep belief network model was proved by this result. This study provides an effective solution for the application of deep learning method in automatic diagnostic decision making.

[Serological diagnosis of congenital infections and algorithms to improve diagnostic efficacy].

PubMed

García-Bermejo, Isabel; de Ory-Manchón, Fernando

2015-07-01

Congenital infection is those transmitted by the mother to the fetus before delivery. It can occur transplacentally or by direct contact with the pathogen during birth or in the immediate postnatal period. Congenital infection can be due to viruses (rubella, cytomegalovirus, herpes simplex, varicella-zoster, hepatitis B and C virus, human inunodeficiencia, erythrovirus B19) as bacteria (Treponema pallidum) and parasites (Toxoplasma gondii and Trypanosoma cruzi). Serological diagnosis of congenital infection is based on both the knowledge of infectious serology in the mother, including the systematic serological screening and diagnostic aspects of the determination of IgM and confirmatory methods, IgG avidity tests, establishment of antibody profiles, and in the diagnosis the neonate. Serological diagnosis of congenital infection in the newborn is mainly based on the detection of specific IgM usually by immunoenzymatic assays or immunochemiluminescence techniques. In some instances it is important to perform the serological follow up of the newborn to confirm the congenital infection. Copyright © 2015 Elsevier España, S.L.U. All rights reserved.

Current use and future perspectives of diagnostic and therapeutic lasers in Oral Medicine.

PubMed

Maia, A M A; Barkokebas, A; Pires, A P; Barros, L F; Carvalho, A A T; Leão, J C

2008-10-01

Several diagnostic and therapeutic methods are based on the optical properties of lasers. In therapeutic applications, laser light is absorbed in a specific manner, whereas light is scattered, reflected, or transmitted from different structures. Improvements in laser technology allow new procedures and broaden the scope of applications for both diagnosis and therapy. The focus of laser application in Oral Medicine diagnosis should be early detection of oral squamous cell carcinoma. Novel modalities for the detection of oral malignancy are urgently needed, while others must be continuously improved. Optical coherence tomography and laser-induced fluorescence spectroscopy are currently being studied. In addition to diagnosis of non-malignant lesions, laser therapy has been used based upon the biological reactions and molecular wound healing mechanisms as an alternative for the treatment of a variety of oral soft tissue lesions. The aim of the present article is to review current knowledge and future perspectives of lasers in Oral Medicine.

Metabolic emergencies and the emergency physician.

PubMed

Fletcher, Janice Mary

2016-02-01

Fifty percent of inborn errors of metabolism are present in later childhood and adulthood, with crises commonly precipitated by minor viral illnesses or increased protein ingestion. Many physicians only consider IEM after more common conditions (such as sepsis) have been considered. In view of the large number of inborn errors, it might appear that their diagnosis requires precise knowledge of a large number of biochemical pathways and their interrelationship. As a matter of fact, an adequate diagnostic approach can be based on the proper use of only a few screening tests. A detailed history of antecedent events, together with these simple screening tests, can be diagnostic, leading to life-saving, targeted treatments for many disorders. Unrecognised, IEM can lead to significant mortality and morbidity. Advice is available 24/7 through the metabolic service based at the major paediatric hospital in each state and Starship Children's Health in New Zealand. © 2016 The Author. Journal of Paediatrics and Child Health © 2016 Paediatrics and Child Health Division (Royal Australasian College of Physicians).

Models based on value and probability in health improve shared decision making.

PubMed

Ortendahl, Monica

2008-10-01

Diagnostic reasoning and treatment decisions are a key competence of doctors. A model based on values and probability provides a conceptual framework for clinical judgments and decisions, and also facilitates the integration of clinical and biomedical knowledge into a diagnostic decision. Both value and probability are usually estimated values in clinical decision making. Therefore, model assumptions and parameter estimates should be continually assessed against data, and models should be revised accordingly. Introducing parameter estimates for both value and probability, which usually pertain in clinical work, gives the model labelled subjective expected utility. Estimated values and probabilities are involved sequentially for every step in the decision-making process. Introducing decision-analytic modelling gives a more complete picture of variables that influence the decisions carried out by the doctor and the patient. A model revised for perceived values and probabilities by both the doctor and the patient could be used as a tool for engaging in a mutual and shared decision-making process in clinical work.

A National Survey Exploring School Nurses Knowledge and Experience When Working with Children with Autism Spectrum Disorders

ERIC Educational Resources Information Center

McIntosh, Constance E.

2013-01-01

This study explored school nurses knowledge of the diagnostic criteria and secondary conditions related to Autism Spectrum Disorders (ASD), their involvement in the identification and treatment of ASD, their knowledge of medication used to treat ASD, and their overall medication management of children with ASD. Participants included 100 school…

Project Leader's Dual Socialization and Its Impact on Team Learning and Performance: A Diagnostic Study

ERIC Educational Resources Information Center

Gautam, Tanvi

2009-01-01

One of the important challenges for leadership in project teams is the ability to manage the knowledge, communication and coordination related activities of team. In cross-team collaboration, different boundaries contribute to the situated nature of knowledge and hamper the flow of knowledge and prevent shared understanding with those on the other…

Model Diagnostics for Bayesian Networks. Research Report. ETS RR-04-17

ERIC Educational Resources Information Center

Sinharay, Sandip

2004-01-01

Assessing fit of psychometric models has always been an issue of enormous interest, but there exists no unanimously agreed upon item fit diagnostic for the models. Bayesian networks, frequently used in educational assessments (see, for example, Mislevy, Almond, Yan, & Steinberg, 2001) primarily for learning about students' knowledge and…

An ontology-driven, diagnostic modeling system.

PubMed

Haug, Peter J; Ferraro, Jeffrey P; Holmen, John; Wu, Xinzi; Mynam, Kumar; Ebert, Matthew; Dean, Nathan; Jones, Jason

2013-06-01

To present a system that uses knowledge stored in a medical ontology to automate the development of diagnostic decision support systems. To illustrate its function through an example focused on the development of a tool for diagnosing pneumonia. We developed a system that automates the creation of diagnostic decision-support applications. It relies on a medical ontology to direct the acquisition of clinic data from a clinical data warehouse and uses an automated analytic system to apply a sequence of machine learning algorithms that create applications for diagnostic screening. We refer to this system as the ontology-driven diagnostic modeling system (ODMS). We tested this system using samples of patient data collected in Salt Lake City emergency rooms and stored in Intermountain Healthcare's enterprise data warehouse. The system was used in the preliminary development steps of a tool to identify patients with pneumonia in the emergency department. This tool was compared with a manually created diagnostic tool derived from a curated dataset. The manually created tool is currently in clinical use. The automatically created tool had an area under the receiver operating characteristic curve of 0.920 (95% CI 0.916 to 0.924), compared with 0.944 (95% CI 0.942 to 0.947) for the manually created tool. Initial testing of the ODMS demonstrates promising accuracy for the highly automated results and illustrates the route to model improvement. The use of medical knowledge, embedded in ontologies, to direct the initial development of diagnostic computing systems appears feasible.

[An XXX female with essential thrombocythemia].

PubMed

Ohta, Tadanobu; Hagiwara, Kioyuki; Makita, Kaori; Mugitani, Atuko; Ohta, Kensuke; Yamane, Takahisa; Takubo, Takayuki; Hino, Masayuki

2003-07-01

We describe an XXX female patient accompanied with essential thrombocythemia. To our knowledge this is the first case ever to have been reported. The patient was asymptomatic, but her platelet count had increased to 111.2 x 10(4)/microliter, and she was diagnosed as having essential thrombocythemia based on the diagnostic criteria of the Polycythemia Vera Study Group. At the same time, chromosome analysis of bone marrow cells revealed that she was an XXX female. The patient remained asymptomatic throughout the course of treatment.

Heboidophrenia and Pseudo-Psychopathic Schizophrenia: Current Knowledge and Critical Perspective.

PubMed

De Page, Louis; Englebert, Jérôme

2018-06-26

In this article, based on literature review, we present an integrated description of heboidophrenia and pseudo-psychopathic schizophrenia. Both diagnostic constructs describe latent psychotic processes inextricably bound with psychopathic features. Although both have been described in different eras and research threads, they are that similar that we could not find divergences. We formulated operational criteria for clinical and research purpose. The recognition of this syndrome improves risk management, treatment, and legal decisions. © 2018 S. Karger AG, Basel.

Managing the genomic revolution in cancer diagnostics.

PubMed

Nguyen, Doreen; Gocke, Christopher D

2017-08-01

Molecular tumor profiling is now a routine part of patient care, revealing targetable genomic alterations and molecularly distinct tumor subtypes with therapeutic and prognostic implications. The widespread adoption of next-generation sequencing technologies has greatly facilitated clinical implementation of genomic data and opened the door for high-throughput multigene-targeted sequencing. Herein, we discuss the variability of cancer genetic profiling currently offered by clinical laboratories, the challenges of applying rapidly evolving medical knowledge to individual patients, and the need for more standardized population-based molecular profiling.

Bayesian networks and statistical analysis application to analyze the diagnostic test accuracy

NASA Astrophysics Data System (ADS)

Orzechowski, P.; Makal, Jaroslaw; Onisko, A.

2005-02-01

The computer aided BPH diagnosis system based on Bayesian network is described in the paper. First result are compared to a given statistical method. Different statistical methods are used successfully in medicine for years. However, the undoubted advantages of probabilistic methods make them useful in application in newly created systems which are frequent in medicine, but do not have full and competent knowledge. The article presents advantages of the computer aided BPH diagnosis system in clinical practice for urologists.

Ultrasound and MRI of nerves for monitoring disease activity and treatment effects in chronic dysimmune neuropathies - Current concepts and future directions.

PubMed

Décard, Bernhard F; Pham, Mirko; Grimm, Alexander

2018-01-01

New imaging modalities like high-resolution-ultrasound (HRUS) and MR-Neurography (MRN) are increasingly used for the evaluation of the peripheral nervous system. The increasing knowledge on morphological changes observed in different neuropathies has led to a better understanding of underlying pathophysiological processes. The diagnosis of acquired chronic dysimmune neuropathies (CDN) like chronic inflammatory demyelinating polyneuropathy (CIDP), Lewis-Sumner Syndrome (LSS) or multifocal motor neuropathy (MMN) can be challenging. The current diagnostic criteria and outcome parameters are mainly based on clinical and electrophysiological parameters. Especially in CDN cases with atypical presentation or during early disease stages, the diagnostic accuracy is low and standardized protocols for the evaluation of disease activity and treatment response are lacking. The establishment of combined diagnostic criteria for CDN including imaging modalities could help to improve the diagnostic accuracy, allow a better differentiation of subtypes and facilitate the follow-up of disease course. The appropriate selection of eligible patients and sensitive monitoring of treatment response is mandatory future in treatment trials. In this article, we briefly summarize the clinical presentations and pathophysiological concepts of different CDN like CIDP, LSS and MMN. Furthermore, this review focuses on the diagnostic value of HRUS/MRN and its potential role for the monitoring of disease activity. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Diagnostic methods for mastitis in cows are not appropriate for use in humans: commentary.

PubMed

Kvist, Linda J

2016-01-01

Healthcare workers are now being targeted for marketing of diagnostic tools for mastitis that were developed for the dairy industry and which aim to provide information regarding choice of antibiotic treatment. Meanwhile, scientists are striving to understand how the human microbiome affects health and wellbeing and the importance of maintenance of bacterial balance in the human body. Breast milk supplies a multitude of bacteria to populate the baby's intestinal tract and kick-start the immune system. Researchers propose a paradigm shift in the understanding of bacterial content in breast milk and an alternative paradigm for the understanding of lactational mastitis: there is the beginning of evidence that many cases of lactational mastitis will resolve spontaneously. An international group of researchers is attempting to answer how dietary habits, birth mode, genetics and environmental factors may impact the bacterial content of breast milk. Until we have more comprehensive knowledge about the human milk microbiome, diagnostic aids for identification of women in need of antibiotic therapy for mastitis remain unreliable. Diagnostic aids could lead to the injudicious use of antibiotic therapy, which in turn may rob the infant of bacteria valuable for development of its immune system. The marketing of diagnostic aids for use in human medicine, that were originally developed for use in cows, is neither evidence-based nor good ethical practice.

Toward literature-based feature selection for diagnostic classification: a meta-analysis of resting-state fMRI in depression.

PubMed

Sundermann, Benedikt; Olde Lütke Beverborg, Mona; Pfleiderer, Bettina

2014-01-01

Information derived from functional magnetic resonance imaging (fMRI) during wakeful rest has been introduced as a candidate diagnostic biomarker in unipolar major depressive disorder (MDD). Multiple reports of resting state fMRI in MDD describe group effects. Such prior knowledge can be adopted to pre-select potentially discriminating features for diagnostic classification models with the aim to improve diagnostic accuracy. Purpose of this analysis was to consolidate spatial information about alterations of spontaneous brain activity in MDD, primarily to serve as feature selection for multivariate pattern analysis techniques (MVPA). Thirty two studies were included in final analyses. Coordinates extracted from the original reports were assigned to two categories based on directionality of findings. Meta-analyses were calculated using the non-additive activation likelihood estimation approach with coordinates organized by subject group to account for non-independent samples. Converging evidence revealed a distributed pattern of brain regions with increased or decreased spontaneous activity in MDD. The most distinct finding was hyperactivity/hyperconnectivity presumably reflecting the interaction of cortical midline structures (posterior default mode network components including the precuneus and neighboring posterior cingulate cortices associated with self-referential processing and the subgenual anterior cingulate and neighboring medial frontal cortices) with lateral prefrontal areas related to externally-directed cognition. Other areas of hyperactivity/hyperconnectivity include the left lateral parietal cortex, right hippocampus and right cerebellum whereas hypoactivity/hypoconnectivity was observed mainly in the left temporal cortex, the insula, precuneus, superior frontal gyrus, lentiform nucleus and thalamus. Results are made available in two different data formats to be used as spatial hypotheses in future studies, particularly for diagnostic classification by MVPA.

[Definition of the Diagnosis Osteomyelitis-Osteomyelitis Diagnosis Score (ODS)].

PubMed

Schmidt, H G K; Tiemann, A H; Braunschweig, R; Diefenbeck, M; Bühler, M; Abitzsch, D; Haustedt, N; Walter, G; Schoop, R; Heppert, V; Hofmann, G O; Glombitza, M; Grimme, C; Gerlach, U-J; Flesch, I

2011-08-01

The disease "osteomyelitis" is characterised by different symptoms and parameters. Decisive roles in the development of the disease are played by the causative bacteria, the route of infection and the individual defense mechanisms of the host. The diagnosis is based on different symptoms and findings from the clinical history, clinical symptoms, laboratory results, diagnostic imaging, microbiological and histopathological analyses. While different osteomyelitis classifications have been published, there is to the best of our knowledge no score that gives information how sure the diagnosis "osteomyelitis" is in general. For any scientific study of a disease a valid definition is essential. We have developed a special osteomyelitis diagnosis score for the reliable classification of clinical, laboratory and technical findings. The score is based on five diagnostic procedures: 1) clinical history and risk factors, 2) clinical examination and laboratory results, 3) diagnostic imaging (ultrasound, radiology, CT, MRI, nuclear medicine and hybrid methods), 4) microbiology, and 5) histopathology. Each diagnostic procedure is related to many individual findings, which are weighted by a score system, in order to achieve a relevant value for each assessment. If the sum of the five diagnostic criteria is 18 or more points, the diagnosis of osteomyelitis can be viewed as "safe" (diagnosis class A). Between 8-17 points the diagnosis is "probable" (diagnosis class B). Less than 8 points means that the diagnosis is "possible, but unlikely" (class C diagnosis). Since each parameter can score six points at a maximum, a reliable diagnosis can only be achieved if at least 3 parameters are scored with 6 points. The osteomyelitis diagnosis score should help to avoid the false description of a clinical presentation as "osteomyelitis". A safe diagnosis is essential for the aetiology, treatment and outcome studies of osteomyelitis. © Georg Thieme Verlag KG Stuttgart · New York.

Diagnostic Pathology and Laboratory Medicine in the Age of “Omics”

PubMed Central

Finn, William G.

2007-01-01

Functional genomics and proteomics involve the simultaneous analysis of hundreds or thousands of expressed genes or proteins and have spawned the modern discipline of computational biology. Novel informatic applications, including sophisticated dimensionality reduction strategies and cancer outlier profile analysis, can distill clinically exploitable biomarkers from enormous experimental datasets. Diagnostic pathologists are now charged with translating the knowledge generated by the “omics” revolution into clinical practice. Food and Drug Administration-approved proprietary testing platforms based on microarray technologies already exist and will expand greatly in the coming years. However, for diagnostic pathology, the greatest promise of the “omics” age resides in the explosion in information technology (IT). IT applications allow for the digitization of histological slides, transforming them into minable data and enabling content-based searching and archiving of histological materials. IT will also allow for the optimization of existing (and often underused) clinical laboratory technologies such as flow cytometry and high-throughput core laboratory functions. The state of pathology practice does not always keep up with the pace of technological advancement. However, to use fully the potential of these emerging technologies for the benefit of patients, pathologists and clinical scientists must embrace the changes and transformational advances that will characterize this new era. PMID:17652635

Stimuli-responsive nanotherapeutics for precision drug delivery and cancer therapy.

PubMed

Qiao, Yiting; Wan, Jianqin; Zhou, Liqian; Ma, Wen; Yang, Yuanyuan; Luo, Weixuan; Yu, Zhiqiang; Wang, Hangxiang

2018-05-04

Cancer remains one of the world's leading causes of death. However, most conventional chemotherapeutic drugs only show a narrow therapeutic window in patients because of their inability to discriminate cancer cells from healthy cells. Nanoparticle-based therapeutics (termed nanotherapeutics) have emerged as potential solutions to mitigate many obstacles posed by these free drugs. Deep insights into knowledge of the tumor microenvironment and materials science make it possible to construct nanotherapeutics that are able to release cargoes in response to a variety of internal stimuli and external triggers. Therefore, such highly sophisticated nanosystems could help impede the premature release of toxic drugs in the blood circulation or healthy tissues, thus enhancing the safety profiles of encapsulated drugs. In this context, this review offers a comprehensive overview of several specific stimuli, including internal stimuli (e.g., pH, temperature, enzyme, redox, and H 2 O 2 ) and external stimuli (e.g., magnetic, photo, and ultrasound). We envision that applications of these smart nanotherapeutics can benefit cancer patients and provide a good chance for clinical translation of many nanoparticle formulas. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease Diagnostic Tools > Diagnostic Nanodevices Diagnostic Tools > in vitro Nanoparticle-Based Sensing. © 2018 Wiley Periodicals, Inc.

Challenges to Laser-Based Imaging Techniques in Gas Turbine Combustor Systems for Aerospace Applications

NASA Technical Reports Server (NTRS)

Locke, Randy J.; Anderson, Robert C.; Zaller, Michelle M.; Hicks, Yolanda R.

1998-01-01

Increasingly severe constraints on emissions, noise and fuel efficiency must be met by the next generation of commercial aircraft powerplants. At NASA Lewis Research Center (LeRC) a cooperative research effort with industry is underway to design and test combustors that will meet these requirements. To accomplish these tasks, it is necessary to gain both a detailed understanding of the combustion processes and a precise knowledge of combustor and combustor sub-component performance at close to actual conditions. To that end, researchers at LeRC are engaged in a comprehensive diagnostic investigation of high pressure reacting flowfields that duplicate conditions expected within the actual engine combustors. Unique, optically accessible flame-tubes and sector rig combustors, designed especially for these tests. afford the opportunity to probe these flowfields with the most advanced, laser-based optical diagnostic techniques. However, these same techniques, tested and proven on comparatively simple bench-top gaseous flame burners, encounter numerous restrictions and challenges when applied in these facilities. These include high pressures and temperatures, large flow rates, liquid fuels, remote testing, and carbon or other material deposits on combustor windows. Results are shown that document the success and versatility of these nonintrusive optical diagnostics despite the challenges to their implementation in realistic systems.

Diagnostic value of FIB-4 for liver fibrosis in patients with hepatitis B: a meta-analysis of diagnostic test.

PubMed

Yin, Zhi; Zou, Jin; Li, Qiongxuan; Chen, Lizhang

2017-04-04

This study is aimed at evaluating the diagnostic value of FIB-4 for liver fibrosis in patients with hepatitis B through a meta-analysis of diagnostic test. We conducted a comprehensive search in the Pubmed, Embase, Web of Science, and Chinese National Knowledge Infrastructure before October 31, 2016. Stata 14.0 software was used for calculation and statistical analyses. We used the sensitivity, specificity, positive and negative likelihood ratio (PLR, NLR), diagnostic odds ratio (DOR) and 95% confidence intervals (CIs) to evaluate the diagnostic value of FIB-4 for liver fibrosis in patients with hepatitis B. Twenty-six studies were included in the final analyses, with a total of 8274 individuals. The pooled parameters are calculated from all studies: sensitivity of 0.69 (95%CI:0.63-0.75), specificity of 0.81 (95%CI: 0.73-0.87), PLR of 3.63 (95%CI:2.66-4.94), NLR of 0.38 (95%CI:0.32-0.44), DOR of 9.57 (95%CI: 6.67-13.74), and area under the curve (AUC) of 0.80 (95%CI: 0.76-0.83). We also conducted subgroup based on the range of cut-off values. Results from subgroup analysis showed that cut-off was the source of heterogeneity in the present study. The sensitivity and specificity of cut-off>2 were 0.69 and 0.95 with the AUC of 0.90 (95%CI: 0.87-0.92). The overall diagnostic value of FIB-4 is not very high for liver fibrosis in patients with hepatitis B. However, the diagnostic value is affected by the cut-off value. FIB-4 has relatively high diagnostic value for detecting liver fibrosis in patients with hepatitis B when the diagnostic threshold value is more than 2.0.

The implementation of liquid-based cytology for lung and pleural-based diseases.

PubMed

Michael, Claire W; Bedrossian, Carlos C W M

2014-01-01

First introduced for the processing of cervico-vaginal samples, liquid-based cytology (LBC) soon found application in nongynecological specimens, including bronchoscopic brushings, washings and transcutaneous and transbronchial aspiration biopsy of the lung as well as pleural effusions. This article reviews the existing literature related to these specimens along with the authors' own experience. A literature review was conducted through Ovid MEDLINE and PubMed search engines using several key words. Most of the literature is based on data collected through the use of split samples. The data confirms that the use of LBC is an acceptable, and sometimes superior, alternative to the conventional preparations (CP). LBC offers several advantages, including the ability to transport in a stable collecting media, elimination of obscuring elements, ease of screening, excellent preservation, random representative sample, and application of ancillary techniques on additional preparations. Some diagnostic pitfalls related to the introduced artifacts were reported. The utilization of LBC offers many advantages over CP and has a diagnostic accuracy that is equal to or surpasses that of CP. LBC affords a bridge to the future application of molecular and other ancillary techniques to cytology. Knowledge of the morphological artifacts is useful at the early stages of implementation.

A unified approach to the design of clinical reporting systems.

PubMed

Gouveia-Oliveira, A; Salgado, N C; Azevedo, A P; Lopes, L; Raposo, V D; Almeida, I; de Melo, F G

1994-12-01

Computer-based Clinical Reporting Systems (CRS) for diagnostic departments that use structured data entry have a number of functional and structural affinities suggesting that a common software architecture for CRS may be defined. Such an architecture should allow easy expandability and reusability of a CRS. We report the development methodology and the architecture of SISCOPE, a CRS originally designed for gastrointestinal endoscopy that is expandable and reusable. Its main components are a patient database, a knowledge base, a reports base, and screen and reporting engines. The knowledge base contains the description of the controlled vocabulary and all the information necessary to control the menu system, and is easily accessed and modified with a conventional text editor. The structure of the controlled vocabulary is formally presented as an entity-relationship diagram. The screen engine drives a dynamic user interface and the reporting engine automatically creates a medical report; both engines operate by following a set of rules and the information contained in the knowledge base. Clinical experience has shown this architecture to be highly flexible and to allow frequent modifications of both the vocabulary and the menu system. This structure provided increased collaboration among development teams, insulating the domain expert from the details of the database, and enabling him to modify the system as necessary and to test the changes immediately. The system has also been reused in several different domains.

Simulation based virtual learning environment in medical genetics counseling: an example of bridging the gap between theory and practice in medical education.

PubMed

Makransky, Guido; Bonde, Mads T; Wulff, Julie S G; Wandall, Jakob; Hood, Michelle; Creed, Peter A; Bache, Iben; Silahtaroglu, Asli; Nørremølle, Anne

2016-03-25

Simulation based learning environments are designed to improve the quality of medical education by allowing students to interact with patients, diagnostic laboratory procedures, and patient data in a virtual environment. However, few studies have evaluated whether simulation based learning environments increase students' knowledge, intrinsic motivation, and self-efficacy, and help them generalize from laboratory analyses to clinical practice and health decision-making. An entire class of 300 University of Copenhagen first-year undergraduate students, most with a major in medicine, received a 2-h training session in a simulation based learning environment. The main outcomes were pre- to post- changes in knowledge, intrinsic motivation, and self-efficacy, together with post-intervention evaluation of the effect of the simulation on student understanding of everyday clinical practice were demonstrated. Knowledge (Cohen's d = 0.73), intrinsic motivation (d = 0.24), and self-efficacy (d = 0.46) significantly increased from the pre- to post-test. Low knowledge students showed the greatest increases in knowledge (d = 3.35) and self-efficacy (d = 0.61), but a non-significant increase in intrinsic motivation (d = 0.22). The medium and high knowledge students showed significant increases in knowledge (d = 1.45 and 0.36, respectively), motivation (d = 0.22 and 0.31), and self-efficacy (d = 0.36 and 0.52, respectively). Additionally, 90 % of students reported a greater understanding of medical genetics, 82 % thought that medical genetics was more interesting, 93 % indicated that they were more interested and motivated, and had gained confidence by having experienced working on a case story that resembled the real working situation of a doctor, and 78 % indicated that they would feel more confident counseling a patient after the simulation. The simulation based learning environment increased students' learning, intrinsic motivation, and self-efficacy (although the strength of these effects differed depending on their pre-test knowledge), and increased the perceived relevance of medical educational activities. The results suggest that simulations can help future generations of doctors transfer new understanding of disease mechanisms gained in virtual laboratory settings into everyday clinical practice.

The adult literacy evaluator: An intelligent computer-aided training system for diagnosing adult illiterates

NASA Technical Reports Server (NTRS)

Yaden, David B., Jr.

1992-01-01

An important part of NASA's mission involves the secondary application of its technologies in the public and private sectors. One current application being developed is The Adult Literacy Evaluator, a simulation-based diagnostic tool designed to assess the operant literacy abilities of adults having difficulties in learning to read and write. Using ICAT system technology in addition to speech recognition, closed-captioned television (CCTV), live video and other state-of-the art graphics and storage capabilities, this project attempts to overcome the negative effects of adult literacy assessment by allowing the client to interact with an intelligent computer system which simulates real-life literacy activities and materials and which measures literacy performance in the actual context of its use. The specific objectives of the project are as follows: (1) To develop a simulation-based diagnostic tool to assess adults' prior knowledge about reading and writing processes in actual contexts of application; (2) to provide a profile of readers' strengths and weaknesses; and (3) to suggest instructional strategies and materials which can be used as a beginning point for remediation. In the first and developmental phase of the project, descriptions of literacy events and environments are being written and functional literacy documents analyzed for their components. Examples of literacy events and situations being considered included interactions with environmental print (e.g., billboards, street signs, commercial marquees, storefront logos, etc.), functional literacy materials (e.g., newspapers, magazines, telephone books, bills, receipts, etc.) and employment related communication (i.e., job descriptions, application forms, technical manuals, memorandums, newsletters, etc.). Each of these situations and materials is being analyzed for its literacy requirements in terms of written display (i.e., knowledge of printed forms and conventions), meaning demands (i.e., comprehension and word knowledge) and social situation. From these descriptions, scripts are being generated which define the interaction between the student, an on-screen guide and the simulated literacy environment. The proposed outcome of the Evaluator is a diagnostic profile which will present broad classifications of literacy behaviors across the major areas of metacognitive abilities, word recognition, vocabulary knowledge, comprehension and writing. From these classifications, suggestions for materials and strategies for instruction with which to begin corrective action will be made. The focus of the Literacy Evaluator will be essentially to provide an expert diagnosis and an interpretation of that assessment which then can be used by a human tutor to further design and individualize a remedial program as needed through the use of an authoring system.

The ACTTION-American Pain Society Pain Taxonomy (AAPT): an evidence-based and multidimensional approach to classifying chronic pain conditions.

PubMed

Fillingim, Roger B; Bruehl, Stephen; Dworkin, Robert H; Dworkin, Samuel F; Loeser, John D; Turk, Dennis C; Widerstrom-Noga, Eva; Arnold, Lesley; Bennett, Robert; Edwards, Robert R; Freeman, Roy; Gewandter, Jennifer; Hertz, Sharon; Hochberg, Marc; Krane, Elliot; Mantyh, Patrick W; Markman, John; Neogi, Tuhina; Ohrbach, Richard; Paice, Judith A; Porreca, Frank; Rappaport, Bob A; Smith, Shannon M; Smith, Thomas J; Sullivan, Mark D; Verne, G Nicholas; Wasan, Ajay D; Wesselmann, Ursula

2014-03-01

Current approaches to classification of chronic pain conditions suffer from the absence of a systematically implemented and evidence-based taxonomy. Moreover, existing diagnostic approaches typically fail to incorporate available knowledge regarding the biopsychosocial mechanisms contributing to pain conditions. To address these gaps, the Analgesic, Anesthetic, and Addiction Clinical Trial Translations Innovations Opportunities and Networks (ACTTION) public-private partnership with the U.S. Food and Drug Administration and the American Pain Society (APS) have joined together to develop an evidence-based chronic pain classification system called the ACTTION-APS Pain Taxonomy. This paper describes the outcome of an ACTTION-APS consensus meeting, at which experts agreed on a structure for this new taxonomy of chronic pain conditions. Several major issues around which discussion revolved are presented and summarized, and the structure of the taxonomy is presented. ACTTION-APS Pain Taxonomy will include the following dimensions: 1) core diagnostic criteria; 2) common features; 3) common medical comorbidities; 4) neurobiological, psychosocial, and functional consequences; and 5) putative neurobiological and psychosocial mechanisms, risk factors, and protective factors. In coming months, expert working groups will apply this taxonomy to clusters of chronic pain conditions, thereby developing a set of diagnostic criteria that have been consistently and systematically implemented across nearly all common chronic pain conditions. It is anticipated that the availability of this evidence-based and mechanistic approach to pain classification will be of substantial benefit to chronic pain research and treatment. The ACTTION-APS Pain Taxonomy is an evidence-based chronic pain classification system designed to classify chronic pain along the following dimensions: 1) core diagnostic criteria; 2) common features; 3) common medical comorbidities; 4) neurobiological, psychosocial, and functional consequences; and 5) putative neurobiological and psychosocial mechanisms, risk factors, and protective factors. Copyright © 2014 American Pain Society. Published by Elsevier Inc. All rights reserved.

Qualitative Discovery in Medical Databases

NASA Technical Reports Server (NTRS)

Maluf, David A.

2000-01-01

Implication rules have been used in uncertainty reasoning systems to confirm and draw hypotheses or conclusions. However a major bottleneck in developing such systems lies in the elicitation of these rules. This paper empirically examines the performance of evidential inferencing with implication networks generated using a rule induction tool called KAT. KAT utilizes an algorithm for the statistical analysis of empirical case data, and hence reduces the knowledge engineering efforts and biases in subjective implication certainty assignment. The paper describes several experiments in which real-world diagnostic problems were investigated; namely, medical diagnostics. In particular, it attempts to show that: (1) with a limited number of case samples, KAT is capable of inducing implication networks useful for making evidential inferences based on partial observations, and (2) observation driven by a network entropy optimization mechanism is effective in reducing the uncertainty of predicted events.

Dementia knowledge transfer project in a rural area.

PubMed

Stark, C; Innes, A; Szymczynska, P; Forrest, L; Proctor, K

2013-01-01

Rural Scotland has an ageing population. There has been an increase in the number of people with dementia and as the proportion of people aged over 75 years continues to rise, this will increase still further. The Scottish Government has produced a dementia strategy and implementing this will be a challenge for rural Scotland. Transferring academic knowledge into practice is challenging. A Knowledge Transfer Partnership was formed between NHS Highland and the University of Stirling. A literature review was undertaken of the rural dementia literature; local services were surveyed and described; and interviews were undertaken with people with dementia and carers. Work was conducted on training, diagnostic service provision and local policy. Throughout the project, a collaborative approach was used, which aimed at the joint production of knowledge. Involving University staff in local service development had a substantial impact. Reviewing existing research knowledge and setting it in the context of local services, and of experience of service use, allowed the relevant priorities to be identified. As well as identifying training needs and providing training, the work influenced local decisions on diagnostic service design and standards, and on policy. This embedded engagement model appeared to produce more rapid change than traditional models of use of academic knowledge.

Cognitive aspect of diagnostic errors.

PubMed

Phua, Dong Haur; Tan, Nigel C K

2013-01-01

Diagnostic errors can result in tangible harm to patients. Despite our advances in medicine, the mental processes required to make a diagnosis exhibits shortcomings, causing diagnostic errors. Cognitive factors are found to be an important cause of diagnostic errors. With new understanding from psychology and social sciences, clinical medicine is now beginning to appreciate that our clinical reasoning can take the form of analytical reasoning or heuristics. Different factors like cognitive biases and affective influences can also impel unwary clinicians to make diagnostic errors. Various strategies have been proposed to reduce the effect of cognitive biases and affective influences when clinicians make diagnoses; however evidence for the efficacy of these methods is still sparse. This paper aims to introduce the reader to the cognitive aspect of diagnostic errors, in the hope that clinicians can use this knowledge to improve diagnostic accuracy and patient outcomes.

The genome projects: implications for dental practice and education.

PubMed

Wright, J T; Hart, T C

2002-05-01

Information from the Human Genome Project (HGP) and the integration of information from related areas of study and technology will dramatically change health care for the craniofacial complex. Approaches to risk assessment and diagnosis, prevention, early intervention, and management of craniofacial conditions are and will continue to evolve through the application of this new knowledge. While this information will advance our health care abilities, it is clear that the dental profession will face challenges regarding the acquisition, application, transfer, and effective and efficient use of this knowledge with regards to dental research, dental education, and clinical practice. Unraveling the human genomic sequence now allows accurate diagnosis of numerous craniofacial conditions. However, the greatest oral disease burden results from dental caries and periodontal disease that are complex disorders having both hereditary and environmental factors determining disease risk, progression, and course. Disease risk assessment, prevention, and therapy, based on knowledge from the HGP, will likely vary markedly for the different complex conditions affecting the head and neck. Integration of Information from the human genome, comparative and microbial genomics, proteomics, bioinformatics, and related technologies will provide the basis for proactive prevention and intervention and novel and more efficient treatment approaches. Oral health care practitioners will increasingly require knowledge of human genetics and the application of new molecular-based diagnostic and therapeutic technologies.

The Mexican consensus on chronic constipation.

PubMed

Remes-Troche, J M; Coss-Adame, E; Lopéz-Colombo, A; Amieva-Balmori, M; Carmona Sánchez, R; Charúa Guindic, L; Flores Rendón, R; Gómez Escudero, O; González Martínez, M; Icaza Chávez, M E; Morales Arámbula, M; Schmulson, M; Tamayo de la Cuesta, J L; Valdovinos, M Á; Vázquez Elizondo, G

Significant advances have been made in the knowledge and understanding of the epidemiology, pathophysiology, diagnosis, and treatment of chronic constipation, since the publication of the 2011 guidelines on chronic constipation diagnosis and treatment in Mexico from the Asociación Mexicana de Gastroenterología. To present a consensus review of the current state of knowledge about chronic constipation, providing updated information and integrating the new scientific evidence. Three general coordinators reviewed the literature published within the time frame of January 2011 and January 2017. From that information, 62 initial statements were formulated and then sent to 12 national experts for their revision. The statements were voted upon, using the Delphi system in 3 voting rounds (2 electronic and one face-to-face). The statements were classified through the GRADE system and those that reached agreement >75% were included in the consensus. The present consensus is made up of 42 final statements that provide updated knowledge, supplementing the information that had not been included in the previous guidelines. The strength of recommendation and quality (level) of evidence were established for each statement. The current definitions of chronic constipation, functional constipation, and opioid-induced constipation are given, and diagnostic strategies based on the available diagnostic methods are described. The consensus treatment recommendations were established from evidence on the roles of diet and exercise, fiber, laxatives, new drugs (such as prucalopride, lubiprostone, linaclotide, plecanatide), biofeedback therapy, and surgery. Copyright © 2018. Publicado por Masson Doyma México S.A.

Patients' knowledge about the outcomes of thyroid biopsy: a patient survey.

PubMed

Singh Ospina, Naykky; Castaneda-Guarderas, Ana; Ward, Russell; Brito, Juan P; Maraka, Spyridoula; Zeballos Palacios, Claudia; Yost, Kathleen J; Dean, Diana S; Montori, Victor M

2018-06-16

Fine-needle aspiration biopsy of the thyroid is an increasingly common outpatient procedure. Patients are counseled about the indications and risks of this procedure and informed consent is obtained. We aimed to assess the extent to which patients acquired necessary knowledge during this process. Survey study conducted in a thyroid nodule clinic at a referral center. Adult patients who had just undergone a thyroid biopsy were asked to complete a survey, including eight questions regarding the indications and potential outcomes of thyroid biopsy. The main outcome of the study was to assess the patients' knowledge based on the response to each individual survey question. Two-hundred and ninety-seven patients were eligible, of which 196 (66%) completed the survey: most were women (76%), had adequate reading health literacy (95%) and a mean age of 58 years. Although 86% of patients correctly identified evaluation for thyroid cancer as the main indication for their biopsy, 56% were not aware of the likelihood of this diagnosis. Almost all (>90%) of respondents knew that results could be benign or malignant; fewer were aware of non-diagnostic (71%) or indeterminate (68%) outcomes, or of the need for additional diagnostic testing after the biopsy (33%). After undergoing thyroid biopsy, a high proportion of well-educated patients remained unaware of their risk for thyroid cancer, potential outcomes, and downstream consequences of their biopsy. This quality gap raises the possibility that informed consent procedures that meet legal standards may leave patients undergoing thyroid biopsy paradoxically uninformed.

Floating Numeral Quantifiers as an Unaccusative Diagnostic in Native, Heritage, and L2 Japanese Speakers

ERIC Educational Resources Information Center

Fukuda, Shin

2017-01-01

This study investigates the knowledge of unaccusativity in Japanese native, heritage, and second/foreign language speakers with respect to licensing of floating numeral quantifiers (FNQs) by unaccusative and unergative subjects (the "FNQ diagnostic"). Two acceptability judgment experiments were conducted to examine (i) whether and how…

Diagnosticity and Prototypicality in Category Learning: A Comparison of Inference Learning and Classification Learning

ERIC Educational Resources Information Center

Chin-Parker, Seth; Ross, Brian H.

2004-01-01

Category knowledge allows for both the determination of category membership and an understanding of what the members of a category are like. Diagnostic information is used to determine category membership; prototypical information reflects the most likely features given category membership. Two experiments examined 2 means of category learning,…

Sterile folliculitis as an important diagnostic clue to Crohn's disease.

PubMed

Kempeneers, Céline; Paquot, Isabelle; Philippet, Pierre; Goossens, Annieta; Bernier, Vincent

2013-01-01

Sterile folliculitis is known to be one of the rare cutaneous manifestations of Crohn's disease (CD). To our knowledge it has never been emphasized as a marker of significant diagnostic value, perhaps maybe even more significant than more common cutaneous manifestations such as erythema nodosum (EN). © 2012 Wiley Periodicals, Inc.

A Diagnostic Approach to Corrective Reading in the Classroom.

ERIC Educational Resources Information Center

Dietrich, Dorothy M.

To meet the needs of students reading below their potentials, teachers must learn more about the reading process, become more diagnostic in determining pupils' strengths and weaknesses, and couple their knowledge of reading with an understanding of pupil deficiencies to plan a program to improve the child's ability to read. Diagnosis, though…

Pediatric providers and radiology examinations: knowledge and comfort levels regarding ionizing radiation and potential complications of imaging.

PubMed

Wildman-Tobriner, Benjamin; Parente, Victoria M; Maxfield, Charles M

2017-12-01

Pediatric providers should understand the basic risks of the diagnostic imaging tests they order and comfortably discuss those risks with parents. Appreciating providers' level of understanding is important to guide discussions and enhance relationships between radiologists and pediatric referrers. To assess pediatric provider knowledge of diagnostic imaging modalities that use ionizing radiation and to understand provider concerns about risks of imaging. A 6-question survey was sent via email to 390 pediatric providers (faculty, trainees and midlevel providers) from a single academic institution. A knowledge-based question asked providers to identify which radiology modalities use ionizing radiation. Subjective questions asked providers about discussions with parents, consultations with radiologists, and complications of imaging studies. One hundred sixty-nine pediatric providers (43.3% response rate) completed the survey. Greater than 90% of responding providers correctly identified computed tomography (CT), fluoroscopy and radiography as modalities that use ionizing radiation, and ultrasound and magnetic resonance imaging (MRI) as modalities that do not. Fewer (66.9% correct, P<0.001) knew that nuclear medicine utilizes ionizing radiation. A majority of providers (82.2%) believed that discussions with radiologists regarding ionizing radiation were helpful, but 39.6% said they rarely had time to do so. Providers were more concerned with complications of sedation and cost than they were with radiation-induced cancer, renal failure or anaphylaxis. Providers at our academic referral center have a high level of basic knowledge regarding modalities that use ionizing radiation, but they are less aware of ionizing radiation use in nuclear medicine studies. They find discussions with radiologists helpful and are concerned about complications of sedation and cost.

A virtual university Web system for a medical school.

PubMed

Séka, L P; Duvauferrier, R; Fresnel, A; Le Beux, P

1998-01-01

This paper describes a Virtual Medical University Web Server. This project started in 1994 by the development of the French Radiology Server. The main objective of our Medical Virtual University is to offer not only an initial training (for students) but also the Continuing Professional Education (for practitioners). Our system is based on electronic textbooks, clinical cases (around 4000) and a medical knowledge base called A.D.M. ("Aide au Diagnostic Medical"). We have indexed all electronic textbooks and clinical cases according to the ADM base in order to facilitate the navigation on the system. This system base is supported by a relational database management system. The Virtual Medical University, available on the Web Internet, is presently in the process of external evaluations.

Evaluating the impact of an integrated multidisciplinary head & neck competency-based anatomy & radiology teaching approach in radiation oncology: a prospective cohort study

PubMed Central

2014-01-01

Background Modern radiation oncology demands a thorough understanding of gross and cross-sectional anatomy for diagnostic and therapeutic applications. Complex anatomic sites present challenges for learners and are not well-addressed in traditional postgraduate curricula. A multidisciplinary team (MDT) based head-and-neck gross and radiologic anatomy program for radiation oncology trainees was developed, piloted, and empirically assessed for efficacy and learning outcomes. Methods Four site-specific MDT head-and-neck seminars were implemented, each involving a MDT delivering didactic and case-based instruction, supplemented by cadaveric presentations. There was no dedicated contouring instruction. Pre- and post-testing were performed to assess knowledge, and ability to apply knowledge to the clinical setting as defined by accuracy of contouring. Paired analyses of knowledge pretests and posttests were performed by Wilcoxon matched-pair signed-rank test. Results Fifteen post-graduate trainees participated. A statistically significant (p < 0.001) mean absolute improvement of 4.6 points (17.03%) was observed between knowledge pretest and posttest scores. Contouring accuracy was analyzed quantitatively by comparing spatial overlap of participants’ pretest and posttest contours with a gold standard through the dice similarity coefficient. A statistically significant improvement in contouring accuracy was observed for 3 out of 20 anatomical structures. Qualitative and quantitative feedback revealed that participants were more confident at contouring and were enthusiastic towards the seminars. Conclusions MDT seminars were associated with improved knowledge scores and resident satisfaction; however, increased gross and cross-sectional anatomic knowledge did not translate into improvements in contouring accuracy. Further research should evaluate the impact of hands-on contouring sessions in addition to dedicated instructional sessions to develop competencies. PMID:24969509

Evaluating the impact of an integrated multidisciplinary head & neck competency-based anatomy & radiology teaching approach in radiation oncology: a prospective cohort study.

PubMed

D'Souza, Leah; Jaswal, Jasbir; Chan, Francis; Johnson, Marjorie; Tay, Keng Yeow; Fung, Kevin; Palma, David

2014-06-26

Modern radiation oncology demands a thorough understanding of gross and cross-sectional anatomy for diagnostic and therapeutic applications. Complex anatomic sites present challenges for learners and are not well-addressed in traditional postgraduate curricula. A multidisciplinary team (MDT) based head-and-neck gross and radiologic anatomy program for radiation oncology trainees was developed, piloted, and empirically assessed for efficacy and learning outcomes. Four site-specific MDT head-and-neck seminars were implemented, each involving a MDT delivering didactic and case-based instruction, supplemented by cadaveric presentations. There was no dedicated contouring instruction. Pre- and post-testing were performed to assess knowledge, and ability to apply knowledge to the clinical setting as defined by accuracy of contouring. Paired analyses of knowledge pretests and posttests were performed by Wilcoxon matched-pair signed-rank test. Fifteen post-graduate trainees participated. A statistically significant (p < 0.001) mean absolute improvement of 4.6 points (17.03%) was observed between knowledge pretest and posttest scores. Contouring accuracy was analyzed quantitatively by comparing spatial overlap of participants' pretest and posttest contours with a gold standard through the dice similarity coefficient. A statistically significant improvement in contouring accuracy was observed for 3 out of 20 anatomical structures. Qualitative and quantitative feedback revealed that participants were more confident at contouring and were enthusiastic towards the seminars. MDT seminars were associated with improved knowledge scores and resident satisfaction; however, increased gross and cross-sectional anatomic knowledge did not translate into improvements in contouring accuracy. Further research should evaluate the impact of hands-on contouring sessions in addition to dedicated instructional sessions to develop competencies.

Advantages of the Dental Practice-Based Research Network Initiative and Its Role in Dental Education

PubMed Central

Curro, Frederick A.; Grill, Ashley C.; Thompson, Van P.; Craig, Ronald G.; Vena, Don; Keenan, Analia V.; Naftolin, Frederick

2012-01-01

Practice-based research networks (PBRNs) provide a novel venue in which providers can increase their knowledge base and improve delivery of care through participation in clinical studies. This article describes some aspects of our experience with a National Institute of Dental and Craniofacial Research-supported PBRN and discusses the role it can play in dental education. PBRNs create a structured pathway for providers to advance their professional development by participating in the process of collecting data through clinical research. This process allows practitioners to contribute to the goals of evidence-based dentistry by helping to provide a foundation of evidence on which to base clinical decisions as opposed to relying on anecdotal evidence. PBRNs strengthen the professional knowledge base by applying the principles of good clinical practice, creating a resource for future dental faculty, training practitioners on best practices, and increasing the responsibility, accountability, and scope of care. PBRNs can be the future pivotal instruments of change in dental education, the use of electronic health record systems, diagnostic codes, and the role of comparative effectiveness research, which can create an unprecedented opportunity for the dental profession to advance and be integrated into the health care system. PMID:21828299

Advantages of the dental practice-based research network initiative and its role in dental education.

PubMed

Curro, Frederick A; Grill, Ashley C; Thompson, Van P; Craig, Ronald G; Vena, Don; Keenan, Analia V; Naftolin, Frederick

2011-08-01

Practice-based research networks (PBRNs) provide a novel venue in which providers can increase their knowledge base and improve delivery of care through participation in clinical studies. This article describes some aspects of our experience with a National Institute of Dental and Craniofacial Research-supported PBRN and discusses the role it can play in dental education. PBRNs create a structured pathway for providers to advance their professional development by participating in the process of collecting data through clinical research. This process allows practitioners to contribute to the goals of evidence-based dentistry by helping to provide a foundation of evidence on which to base clinical decisions as opposed to relying on anecdotal evidence. PBRNs strengthen the professional knowledge base by applying the principles of good clinical practice, creating a resource for future dental faculty, training practitioners on best practices, and increasing the responsibility, accountability, and scope of care. PBRNs can be the future pivotal instruments of change in dental education, the use of electronic health record systems, diagnostic codes, and the role of comparative effectiveness research, which can create an unprecedented opportunity for the dental profession to advance and be integrated into the health care system.

Towards intelligent diagnostic system employing integration of mathematical and engineering model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Isa, Nor Ashidi Mat

The development of medical diagnostic system has been one of the main research fields during years. The goal of the medical diagnostic system is to place a nosological system that could ease the diagnostic evaluation normally performed by scientists and doctors. Efficient diagnostic evaluation is essentials and requires broad knowledge in order to improve conventional diagnostic system. Several approaches on developing the medical diagnostic system have been designed and tested since the earliest 60s. Attempts on improving their performance have been made which utilizes the fields of artificial intelligence, statistical analyses, mathematical model and engineering theories. With the availability ofmore » the microcomputer and software development as well as the promising aforementioned fields, medical diagnostic prototypes could be developed. In general, the medical diagnostic system consists of several stages, namely the 1) data acquisition, 2) feature extraction, 3) feature selection, and 4) classifications stages. Data acquisition stage plays an important role in converting the inputs measured from the real world physical conditions to the digital numeric values that can be manipulated by the computer system. One of the common medical inputs could be medical microscopic images, radiographic images, magnetic resonance image (MRI) as well as medical signals such as electrocardiogram (ECG) and electroencephalogram (EEG). Normally, the scientist or doctors have to deal with myriad of data and redundant to be processed. In order to reduce the complexity of the diagnosis process, only the significant features of the raw data such as peak value of the ECG signal or size of lesion in the mammogram images will be extracted and considered in the subsequent stages. Mathematical models and statistical analyses will be performed to select the most significant features to be classified. The statistical analyses such as principal component analysis and discriminant analysis as well as mathematical model of clustering technique have been widely used in developing the medical diagnostic systems. The selected features will be classified using mathematical models that embedded engineering theory such as artificial intelligence, support vector machine, neural network and fuzzy-neuro system. These classifiers will provide the diagnostic results without human intervention. Among many publishable researches, several prototypes have been developed namely NeuralPap, Neural Mammo, and Cervix Kit. The former system (NeuralPap) is an automatic intelligent diagnostic system for classifying and distinguishing between the normal and cervical cancerous cells. Meanwhile, the Cervix Kit is a portable Field-programmable gate array (FPGA)-based cervical diagnostic kit that could automatically diagnose the cancerous cell based on the images obtained during sampling test. Besides the cervical diagnostic system, the Neural Mammo system is developed to specifically aid the diagnosis of breast cancer using a fine needle aspiration image.« less

Towards intelligent diagnostic system employing integration of mathematical and engineering model

NASA Astrophysics Data System (ADS)

Isa, Nor Ashidi Mat

2015-05-01

The development of medical diagnostic system has been one of the main research fields during years. The goal of the medical diagnostic system is to place a nosological system that could ease the diagnostic evaluation normally performed by scientists and doctors. Efficient diagnostic evaluation is essentials and requires broad knowledge in order to improve conventional diagnostic system. Several approaches on developing the medical diagnostic system have been designed and tested since the earliest 60s. Attempts on improving their performance have been made which utilizes the fields of artificial intelligence, statistical analyses, mathematical model and engineering theories. With the availability of the microcomputer and software development as well as the promising aforementioned fields, medical diagnostic prototypes could be developed. In general, the medical diagnostic system consists of several stages, namely the 1) data acquisition, 2) feature extraction, 3) feature selection, and 4) classifications stages. Data acquisition stage plays an important role in converting the inputs measured from the real world physical conditions to the digital numeric values that can be manipulated by the computer system. One of the common medical inputs could be medical microscopic images, radiographic images, magnetic resonance image (MRI) as well as medical signals such as electrocardiogram (ECG) and electroencephalogram (EEG). Normally, the scientist or doctors have to deal with myriad of data and redundant to be processed. In order to reduce the complexity of the diagnosis process, only the significant features of the raw data such as peak value of the ECG signal or size of lesion in the mammogram images will be extracted and considered in the subsequent stages. Mathematical models and statistical analyses will be performed to select the most significant features to be classified. The statistical analyses such as principal component analysis and discriminant analysis as well as mathematical model of clustering technique have been widely used in developing the medical diagnostic systems. The selected features will be classified using mathematical models that embedded engineering theory such as artificial intelligence, support vector machine, neural network and fuzzy-neuro system. These classifiers will provide the diagnostic results without human intervention. Among many publishable researches, several prototypes have been developed namely NeuralPap, Neural Mammo, and Cervix Kit. The former system (NeuralPap) is an automatic intelligent diagnostic system for classifying and distinguishing between the normal and cervical cancerous cells. Meanwhile, the Cervix Kit is a portable Field-programmable gate array (FPGA)-based cervical diagnostic kit that could automatically diagnose the cancerous cell based on the images obtained during sampling test. Besides the cervical diagnostic system, the Neural Mammo system is developed to specifically aid the diagnosis of breast cancer using a fine needle aspiration image.

Use of diagnostics in wound management.

PubMed

Romanelli, Marco; Miteva, Maria; Romanelli, Paolo; Barbanera, Sabrina; Dini, Valentina

2013-03-01

Wound healing research has progressed impressively over the past years. New insights into the pathogenesis of different chronic wounds and the study of novel treatment have made wound healing a model disorder and have revealed basic cellular and molecular mechanisms underlying chronic wounds. Although the observation is so obvious and simple, the interpretations by different observers can be quite variable. The interpretations of severity and change in severity by treatment may differ considerably between patient and practitioners. In this review we provide comprehensive view on different aspects of wound diagnostic, including clinical measurement, new biomarkers in wound pathology, proteases evaluation, and future noninvasive sensor-based devices. Wound caregivers are in the unique position of being able to observe the wound changes and describe these with knowledge and strict methodology, but also with the wide range of available wound diagnostic devices. The complexity of severity assessment in wound healing is reflected by the multiple clinical scores available. The best objective methods used to evaluate cutaneous tissue repair should have a high specificity and sensitivity and a low inter and intraobserver variation.

Diagnostic imaging for chronic orofacial pain, maxillofacial osseous and soft tissue pathology and temporomandibular disorders.

PubMed

Shintaku, Werner; Enciso, Reyes; Broussard, Jack; Clark, Glenn T

2006-08-01

Since dentists can be faced by unusual cases during their professional life, this article reviews the common orofacial disorders that are of concern to a dentist trying to diagnose the source of pain or dysfunction symptoms, providing an overview of the essential knowledge and usage of nowadays available advanced diagnostic imaging modalities. In addition to symptom-driven diagnostic dilemmas, where such imaging is utilized, occasionally there are asymptomatic anomalies discovered by routine clinical care and/or on dental or panoramic images that need more discussion. The correct selection criteria of an image exam should be based on the individual characteristics of the patient, and the type of imaging technique should be selected depending on the specific clinical problem, the kind of tissue to be visualized, the information obtained from the imaging modality, radiation exposure, and the cost of the examination. The usage of more specialized imaging modalities such as magnetic resonance imaging, computed tomography, ultrasound, as well as single photon computed tomography, positron electron tomography, and their hybrid machines, SPECT/ CT and PET/CT, are discussed.

Biopharmaceutical industry perspectives on the business prospects for personalized medicine.

PubMed

Milne, Christopher-Paul; Zuckerman, Rachael

2011-09-01

Personalized medicine is entering its second decade, yet the role it will play in addressing the biopharmaceutical industry's productivity gap and the rising cost of healthcare is still a matter of speculation. So what does the biopharmaceutical industry itself say about the business prospects for personalized medicine? The authors conducted interviews with 20 science and business experts from 13 companies to find out. In this article, particular attention is paid to drug-diagnostic codevelopment, so-called companion diagnostics. The results of the interviews are discussed in light of perspectives from various stakeholders available from the literature in the public domain. In brief, biopharmaceutical acknowledges the many difficulties that plague this path to product development with particular concern for knowledge gaps in the scientific base, the timing of studies during development, as well as the regulatory, reimbursement and commercial hurdles that can thwart approval, launch and market uptake. Nonetheless, personalized medicine in general and companion diagnostics in particular are believed to be an increasingly sustainable business proposition with expectations for rapid market growth in the near term.

Authoritative knowledge, the technological imperative and women's responses to prenatal diagnostic technologies.

PubMed

McCoyd, Judith L M

2010-12-01

Theories about authoritative knowledge (AK) and the technological imperative have received varying levels of interest in anthropological, feminist and science and technology studies. Although the anthropological literature abounds with empirical considerations of authoritative knowledge, few have considered both theories through an empirical, inductive lens. Data extracted from an earlier study of 30 women's responses to termination for fetal anomaly are reanalyzed to consider the women's views of, and responses to, prenatal diagnostic technologies (PNDTs). Findings indicate that a small minority embrace the societal portrayal of technology as univalently positive, while the majority have nuanced and ambivalent responses to the use of PNDTs. Further, the interface of authoritative knowledge and the technological imperative suggests that AK derives not only from medical provider status and technology use, but also from the adequacy and trustworthiness of the information. The issue of timing and uncertainty of the information also are interrogated for their impact on women's lives and what that can illuminate about the theories of AK and the technological imperative.

The translation research in a dental setting (TRiaDS) programme protocol

PubMed Central

2010-01-01

Background It is well documented that the translation of knowledge into clinical practice is a slow and haphazard process. This is no less true for dental healthcare than other types of healthcare. One common policy strategy to help promote knowledge translation is the production of clinical guidance, but it has been demonstrated that the simple publication of guidance is unlikely to optimise practice. Additional knowledge translation interventions have been shown to be effective, but effectiveness varies and much of this variation is unexplained. The need for researchers to move beyond single studies to develop a generalisable, theory based, knowledge translation framework has been identified. For dentistry in Scotland, the production of clinical guidance is the responsibility of the Scottish Dental Clinical Effectiveness Programme (SDCEP). TRiaDS (Translation Research in a Dental Setting) is a multidisciplinary research collaboration, embedded within the SDCEP guidance development process, which aims to establish a practical evaluative framework for the translation of guidance and to conduct and evaluate a programme of integrated, multi-disciplinary research to enhance the science of knowledge translation. Methods Set in General Dental Practice the TRiaDS programmatic evaluation employs a standardised process using optimal methods and theory. For each SDCEP guidance document a diagnostic analysis is undertaken alongside the guidance development process. Information is gathered about current dental care activities. Key recommendations and their required behaviours are identified and prioritised. Stakeholder questionnaires and interviews are used to identify and elicit salient beliefs regarding potential barriers and enablers towards the key recommendations and behaviours. Where possible routinely collected data are used to measure compliance with the guidance and to inform decisions about whether a knowledge translation intervention is required. Interventions are theory based and informed by evidence gathered during the diagnostic phase and by prior published evidence. They are evaluated using a range of experimental and quasi-experimental study designs, and data collection continues beyond the end of the intervention to investigate the sustainability of an intervention effect. Discussion The TRiaDS programmatic approach is a significant step forward towards the development of a practical, generalisable framework for knowledge translation research. The multidisciplinary composition of the TRiaDS team enables consideration of the individual, organisational and system determinants of professional behaviour change. In addition the embedding of TRiaDS within a national programme of guidance development offers a unique opportunity to inform and influence the guidance development process, and enables TRiaDS to inform dental services practitioners, policy makers and patients on how best to translate national recommendations into routine clinical activities. PMID:20646275

Assessment of Durability of Online and Multisensory Learning Using an Ophthalmology Model.

PubMed

Lippa, Linda Mottow; Anderson, Craig L

2015-10-01

To explore the impact of online learning and multisensory small-group teaching on acquisition and retention of specialty knowledge and diagnostic skills during a third-year family medicine rotation. Exploratory, observational, longitudinal, and multiple-skill measures. Two medical school classes (n = 199) at a public medical school in California. Students engaged in online self-study, small-group interactive diagnostic sessions, picture identification of critical pathologic features, and funduscopic simulator examinations. The authors compared performance on testing immediately after online learning with testing at end-rotation, as well as picture identification versus simulator diagnostic ability in students with (n = 94) and without (n = 105) practice tracing contours on whiteboard projections of those same slides depicting fundus pathologic features of common systemic diseases. Picture identification, accuracy of funduscopic descriptions, online module post-tests, and end-rotation tests. Proprioceptive reinforcement of fundus pattern recognition significantly reduced the need for remediation for misdiagnosing optic disc edema during end-rotation funduscopic simulator testing, but it had no effect on fundus pattern recognition or diagnostic ability overall. Near-perfect immediate online post-test scores contrasted sharply with poor end-rotation scores on an in-house test (average, 59.4%). Rotation timing was not a factor because the patterns remained consistent throughout the academic school year. Neither multisensory teaching nor online self-study significantly improved retention of ophthalmic knowledge and diagnostic skills by the end of a month-long third-year rotation. Timing such training closer to internship when application is imminent may enhance students' appreciation for its value and perhaps may improve retention. Pulsed quizzes over time also may be necessary to motivate students to retain the knowledge gained. Copyright © 2015 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

How Expert Clinicians Intuitively Recognize a Medical Diagnosis.

PubMed

Brush, John E; Sherbino, Jonathan; Norman, Geoffrey R

2017-06-01

Research has shown that expert clinicians make a medical diagnosis through a process of hypothesis generation and verification. Experts begin the diagnostic process by generating a list of diagnostic hypotheses using intuitive, nonanalytic reasoning. Analytic reasoning then allows the clinician to test and verify or reject each hypothesis, leading to a diagnostic conclusion. In this article, we focus on the initial step of hypothesis generation and review how expert clinicians use experiential knowledge to intuitively recognize a medical diagnosis. Copyright © 2017 Elsevier Inc. All rights reserved.

Dutch evidence statement for pelvic physical therapy in patients with anal incontinence.

PubMed

Berghmans, L C M; Groot, J A M; van Heeswijk-Faase, I C; Bols, E M J

2015-04-01

To promote agreement among and support the quality of pelvic physiotherapists' skills and clinical reasoning in The Netherlands, an Evidence Statement Anal Incontinence (AI) was developed based on the practice-driven problem definitions outlined. We present a summary of the current state of knowledge and formulate recommendations for a methodical assessment and treatment for patients with AI, and place the evidence in a broader perspective of current developments. Electronic literature searches were conducted in relevant databases with regard to prevalence, incidence, costs, etiological and prognostic factors, predictors of response to therapy, prevention, assessment, and treatment. The recommendations have been formulated on the basis of scientific evidence and where no evidence was available, recommendations were consensus-based. The evidence statement incorporates a practice statement with corresponding notes that clarify the recommendations, and accompanying flowcharts, describing the steps and recommendations with regard to the diagnostic and therapeutic process. The diagnostic process consists of history-taking and physical examination supported by measurement instruments. For each problem category for patients with AI, a certain treatment plan can be distinguished dependent on the presence of pelvic floor dysfunction, awareness of loss of stools, comorbidity, neurological problems, adequate anorectal sensation, and (in)voluntary control. Available evidence and expert opinion support the use of education, pelvic floor muscle training, biofeedback, and electrostimulation in selected patients. The evidence statement reflects the current state of knowledge for a methodical and systematic physical therapeutic assessment and treatment for patients with AI.

A design and implementation methodology for diagnostic systems

NASA Technical Reports Server (NTRS)

Williams, Linda J. F.

1988-01-01

A methodology for design and implementation of diagnostic systems is presented. Also discussed are the advantages of embedding a diagnostic system in a host system environment. The methodology utilizes an architecture for diagnostic system development that is hierarchical and makes use of object-oriented representation techniques. Additionally, qualitative models are used to describe the host system components and their behavior. The methodology architecture includes a diagnostic engine that utilizes a combination of heuristic knowledge to control the sequence of diagnostic reasoning. The methodology provides an integrated approach to development of diagnostic system requirements that is more rigorous than standard systems engineering techniques. The advantages of using this methodology during various life cycle phases of the host systems (e.g., National Aerospace Plane (NASP)) include: the capability to analyze diagnostic instrumentation requirements during the host system design phase, a ready software architecture for implementation of diagnostics in the host system, and the opportunity to analyze instrumentation for failure coverage in safety critical host system operations.

The impact of patents on the development of genome-based clinical diagnostics: an analysis of case studies

PubMed Central

Pierce, Brandon L.; Carlson, Christopher S.; Kuszler, Patricia C.; Stanford, Janet L.; Austin, Melissa A.

2010-01-01

Purpose Fragmented ownership of diagnostic gene patents has the potential to create an ‘anticommons’ in the area of genomic diagnostics, making it difficult and expensive to assemble the patent rights necessary to develop a panel of genetic tests. The objectives of this study were to identify U.S. patents that protect existing panels of genetic tests, describe how (or if) test providers acquired rights to these patents, and determine if fragmented patent ownership has inhibited the commercialization of these panels. Methods As case studies, we selected four clinical applications of genetic testing (cystic fibrosis, maturity-onset diabetes of the young, long QT syndrome, and hereditary breast cancer) that utilize tests protected by ≥3 U.S. patents. We summarized publically available information on relevant patents, test providers, licenses, and litigation. Results For each case study, all tests of major genes/mutations were patented, and at least one party held the collective rights to conduct all relevant tests, often as a result of licensing agreements. Conclusions We did not find evidence that fragmentation of patent rights has inhibited commercialization of genetic testing services. However, as knowledge of genetic susceptibility increases, it will be important to consider the potential consequences of fragmented ownership of diagnostic gene patents. PMID:19367193

Diagnostic reasoning strategies and diagnostic success.

PubMed

Coderre, S; Mandin, H; Harasym, P H; Fick, G H

2003-08-01

Cognitive psychology research supports the notion that experts use mental frameworks or "schemes", both to organize knowledge in memory and to solve clinical problems. The central purpose of this study was to determine the relationship between problem-solving strategies and the likelihood of diagnostic success. Think-aloud protocols were collected to determine the diagnostic reasoning used by experts and non-experts when attempting to diagnose clinical presentations in gastroenterology. Using logistic regression analysis, the study found that there is a relationship between diagnostic reasoning strategy and the likelihood of diagnostic success. Compared to hypothetico-deductive reasoning, the odds of diagnostic success were significantly greater when subjects used the diagnostic strategies of pattern recognition and scheme-inductive reasoning. Two other factors emerged as independent determinants of diagnostic success: expertise and clinical presentation. Not surprisingly, experts outperformed novices, while the content area of the clinical cases in each of the four clinical presentations demonstrated varying degrees of difficulty and thus diagnostic success. These findings have significant implications for medical educators. It supports the introduction of "schemes" as a means of enhancing memory organization and improving diagnostic success.

Radiological interpretation of images displayed on tablet computers: a systematic review

PubMed Central

Armfield, N R; Smith, A C

2015-01-01

Objective: To review the published evidence and to determine if radiological diagnostic accuracy is compromised when images are displayed on a tablet computer and thereby inform practice on using tablet computers for radiological interpretation by on-call radiologists. Methods: We searched the PubMed and EMBASE databases for studies on the diagnostic accuracy or diagnostic reliability of images interpreted on tablet computers. Studies were screened for inclusion based on pre-determined inclusion and exclusion criteria. Studies were assessed for quality and risk of bias using Quality Appraisal of Diagnostic Reliability Studies or the revised Quality Assessment of Diagnostic Accuracy Studies tool. Treatment of studies was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Results: 11 studies met the inclusion criteria. 10 of these studies tested the Apple iPad® (Apple, Cupertino, CA). The included studies reported high sensitivity (84–98%), specificity (74–100%) and accuracy rates (98–100%) for radiological diagnosis. There was no statistically significant difference in accuracy between a tablet computer and a digital imaging and communication in medicine-calibrated control display. There was a near complete consensus from authors on the non-inferiority of diagnostic accuracy of images displayed on a tablet computer. All of the included studies were judged to be at risk of bias. Conclusion: Our findings suggest that the diagnostic accuracy of radiological interpretation is not compromised by using a tablet computer. This result is only relevant to the Apple iPad and to the modalities of CT, MRI and plain radiography. Advances in knowledge: The iPad may be appropriate for an on-call radiologist to use for radiological interpretation. PMID:25882691

Improvement of diagnostic agreement among pathologists in resolving an "atypical glands suspicious for cancer" diagnosis in prostate biopsies using a novel "Disease-Focused Diagnostic Review" quality improvement process.

PubMed

Shah, Rajal B; Leandro, Gioacchino; Romerocaces, Gloria; Bentley, James; Yoon, Jiyoon; Mendrinos, Savvas; Tadros, Yousef; Tian, Wei; Lash, Richard

2016-10-01

One of the major goals of an anatomic pathology laboratory quality program is to minimize unwarranted diagnostic variability and equivocal reporting. This study evaluated the utility of Miraca Life Sciences' "Disease-Focused Diagnostic Review" (DFDR) quality program in improving interobserver diagnostic reproducibility associated with classification of "atypical glands suspicious for adenocarcinoma" (ATYP) in prostate biopsies. Seventy-one selected prostate biopsies with a focus of ATYP were reviewed by 8 pathologists. Participants were blinded to the original diagnosis and were first asked to classify the ATYP as benign, atypical, or limited adenocarcinoma. DFDR comprised a "theoretical consensus" (in which pathologists first reached consensus on the morphological features they considered relevant for the diagnosis of limited prostatic adenocarcinoma), a didactic review including relevant literature, and "practical consensus" (pathologists performed joint microscopic sessions, reconciling each other's observations and positions evaluating a separate unique slide set). Participants were finally asked to reclassify the original 71 ATYP cases based on knowledge gleaned from DFDR. Pre- and post-DFDR interobserver reproducibility of overall diagnostic agreement was assessed. Interobserver reproducibility measured by Fleiss κ values of pre- and post-DFDR was 0.36 and 0.59, respectively (P=.006). Post-DFDR, there were significant improvement for "100% concordance" (P=.011) and reduction for "no consensus" (P=.0004) categories. Despite a lower pre-DFDR reproducibility for non-uropathology fellowship-trained (n=3, κ=0.38) versus uropathology fellowship-trained (n=5, κ=0.43) pathologists, both groups achieved similarly high post-DFDR κ levels (κ=0.58 and 0.56, respectively). DFDR represents an effective tool to formally achieve diagnostic consensus and reduce variability associated with critical diagnoses in an anatomic pathology practice. Copyright © 2016 Elsevier Inc. All rights reserved.

An Analysis of Knowledge Structure, Diversity and Diagnostic Abilities among Pre-Service Science Teachers within the Domain of Oxidation and Reduction Chemistry

ERIC Educational Resources Information Center

Bischoff, Paul J.; Avery, Leanne; Golden, Constance Feldt; French, Paul

2010-01-01

The purpose of this study was to investigate the development of preservice science teachers' knowledge structures in the domain of oxidation and reduction chemistry. Knowledge structures were elicited through video-recorded semi-structured interviews before and after the unit of instruction, and analyzed using a visual flow map representation.…

[Personalized urooncology based on molecular uropathology: what is the future?].

PubMed

Dahl, E; Haller, F

2013-07-01

Targeted therapies and biomarker validation are key drivers in the advancement of personalized oncology which is a growing topic in all clinical areas. Compared with other professions, such as pulmonology and gynecology, development in urology has so far been retarded but has recently gained increasing momentum. A basis for this is the currently growing and in future accelerated application of new knowledge derived from molecular biology in the field of uropathology. The rapid gain of knowledge is driven by a whole new class of analytical methods, such as massively parallel sequencing (deep sequencing or next generation sequencing), which enables analysis of virtually a new universe of potential biomarkers. This article describes the emerging paradigm shift in molecular pathological diagnostics of urological tumors using the example of prostate cancer.

Proteome analysis of snake venom toxins: pharmacological insights.

PubMed

Georgieva, Dessislava; Arni, Raghuvir K; Betzel, Christian

2008-12-01

Snake venoms are an extremely rich source of pharmacologically active proteins with a considerable clinical and medical potential. To date, this potential has not been fully explored, mainly because of our incomplete knowledge of the venom proteome and the pharmacological properties of its components, in particular those devoid of enzymatic activity. This review summarizes the latest achievements in the determination of snake venom proteome, based primarily on the development of new strategies and techniques. Detailed knowledge of the venom toxin composition and biological properties of the protein constituents should provide the scaffold for the design of new more effective drugs for the treatment of the hemostatic system and heart disorders, inflammation, cancer and consequences of snake bites, as well as new tools for clinical diagnostic and assays of hemostatic parameters.

Innovative applications of artificial intelligence

NASA Astrophysics Data System (ADS)

Schorr, Herbert; Rappaport, Alain

Papers concerning applications of artificial intelligence are presented, covering applications in aerospace technology, banking and finance, biotechnology, emergency services, law, media planning, music, the military, operations management, personnel management, retail packaging, and manufacturing assembly and design. Specific topics include Space Shuttle telemetry monitoring, an intelligent training system for Space Shuttle flight controllers, an expert system for the diagnostics of manufacturing equipment, a logistics management system, a cooling systems design assistant, and a knowledge-based integrated circuit design critic. Additional topics include a hydraulic circuit design assistant, the use of a connector assembly specification expert system to harness detailed assembly process knowledge, a mixed initiative approach to airlift planning, naval battle management decision aids, an inventory simulation tool, a peptide synthesis expert system, and a system for planning the discharging and loading of container ships.

Factors associated with patient, and diagnostic delays in Chinese TB patients: a systematic review and meta-analysis.

PubMed

Li, Ying; Ehiri, John; Tang, Shenglan; Li, Daikun; Bian, Yongqiao; Lin, Hui; Marshall, Caitlin; Cao, Jia

2013-07-02

Delay in seeking care is a major impediment to effective management of tuberculosis (TB) in China. To elucidate factors that underpin patient and diagnostic delays in TB management, we conducted a systematic review and meta-analysis of factors that are associated with delays in TB care-seeking and diagnosis in the country. This review was prepared following standard procedures of the Cochrane Collaboration and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement and checklist. Relevant studies published up to November 2012 were identified from three major international and Chinese literature databases: Medline/PubMed, EMBASE and CNKI (China National Knowledge Infrastructure). We included 29 studies involving 38,947 patients from 17 provinces in China. Qualitative analysis showed that key individual level determinants of delays included socio-demographic and economic factors, mostly poverty, rural residence, lack of health insurance, lower educational attainment, stigma and poor knowledge of TB. Health facility determinants included limited availability of resources to perform prompt diagnosis, lack of qualified health workers and geographical barriers.Quantitative meta-analysis indicated that living in rural areas was a risk factor for patient delays (pooled odds ratio (OR) (95% confidence interval (CI)): 1.79 (1.62, 1.98)) and diagnostic delays (pooled OR (95% CI): 1.40 (1.23, 1.59)). Female patients had higher risk of patient delay (pooled OR (95% CI): 1.94 (1.13, 3.33)). Low educational attainment (primary school and below) was also a risk factor for patient delay (pooled OR (95% CI): 2.14 (1.03, 4.47)). The practice of seeking care first from Traditional Chinese Medicine (TMC) providers was also identified as a risk factor for diagnostic delay (pooled OR (95% CI): 5.75 (3.03, 10.94)). Patient and diagnostic delays in TB care are mediated by individual and health facility factors. Population-based interventions that seek to reduce TB stigma and raise awareness about the benefits of early diagnosis and prompt treatment are needed. Policies that remove patients' financial barriers in access to TB care, and integration of the informal care sector into TB control in urban and rural settings are central factors in TB control.

Evaluation of Computer-aided Strategies for Teaching Medical Students Prenatal Ultrasound Diagnostic Skills.

PubMed

Amesse, Lawrence S; Callendar, Ealena; Pfaff-Amesse, Teresa; Duke, Janice; Herbert, William N P

2008-09-24

To evaluate whether computer-based learning (CBL) improves newly acquired knowledge and is an effective strategy for teaching prenatal ultrasound diagnostic skills to third-year medical students when compared with instruction by traditional paper-based methods (PBM). We conducted a randomized, prospective study involving volunteer junior (3(rd) year) medical students consecutively rotating through the Obstetrics and Gynecology clerkship during six months of the 2005-2006 academic year. The students were randomly assigned to permuted blocks and divided into two groups. Half of the participants received instruction in prenatal ultrasound diagnostics using an interactive CBL program; the other half received instruction using equivalent material by the traditional PBM. Outcomes were evaluated by comparing changes in pre-tutorial and post instruction examination scores. All 36 potential participants (100%) completed the study curriculum. Students were divided equally between the CBL (n = 18) and PBM (n = 18) groups. Pre-tutorial exam scores (mean+/-s.d.) were 44%+/-11.1% for the CBL group and 44%+/-10.8% for the PBL cohort, indicating no statistically significant differences (p>0.05) between the two groups. After instruction, post-tutorial exam scores (mean+/-s.d.) were increased from the pre-tutorial scores, 74%+/-11% and 67%+/-12%, for students in the CBL and the PBM groups, respectively. The improvement in post-tutorial exam scores from the pre-test scores was considered significant (p<0.05). When post-test scores for the tutorial groups were compared, the CBL subjects achieved a score that was, on average, 7 percentage points higher than their PBM counterparts, a statistically significant difference (p < 0.05). Instruction by either CBL or PBM strategies is associated with improvements in newly acquired knowledge as reflected by increased post-tutorial examination scores. Students that received CBL had significantlyhigher post-tutorial exam scores than those in the PBM group, indicating that CBL is an effective instruction strategy in this setting.

Diagnostic criteria as dysfunction indicators: bridging the chasm between the definition of mental disorder and diagnostic criteria for specific disorders.

PubMed

First, Michael B; Wakefield, Jerome C

2013-12-01

According to the introduction to the Diagnostic and Statistical Manual of Mental Disorders (DSM), Fifth Edition, each disorder must satisfy the definition of mental disorder, which requires the presence of both harm and dysfunction. Constructing criteria sets to require harm is relatively straightforward. However, establishing the presence of dysfunction is necessarily inferential because of the lack of knowledge of internal psychological and biological processes and their functions and dysfunctions. Given that virtually every psychiatric symptom characteristic of a DSM disorder can occur under some circumstances in a normally functioning person, diagnostic criteria based on symptoms must be constructed so that the symptoms indicate an internal dysfunction, and are thus inherently pathosuggestive. In this paper, we review strategies used in DSM criteria sets for increasing the pathosuggestiveness of symptoms to ensure that the disorder meets the requirements of the definition of mental disorder. Strategies include the following: requiring a minimum duration and persistence; requiring that the frequency or intensity of a symptom exceed that seen in normal people; requiring disproportionality of symptoms, given the context; requiring pervasiveness of symptom expression across contexts; adding specific exclusions for contextual scenarios in which symptoms are best understood as normal reactions; combining symptoms to increase cumulative pathosuggestiveness; and requiring enough symptoms from an overall syndrome to meet a minimum threshold of pathosuggestiveness. We propose that future revisions of the DSM consider systematic implementation of these strategies in the construction and revision of criteria sets, with the goal of maximizing the pathosuggestiveness of diagnostic criteria to reduce the potential for diagnostic false positives.

Mechanisms for Induction of Pulmonary Capillary Hemorrhage by Diagnostic Ultrasound: Review and Consideration of Acoustical Radiation Surface Pressure

PubMed Central

Miller, Douglas L.

2016-01-01

Diagnostic ultrasound can induce pulmonary capillary hemorrhage (PCH) in rats and other mammals. This phenomenon represents the only clearly demonstrated biological effect of (non-contrast enhanced) diagnostic ultrasound and thus presents a uniquely important safety issue. However, the physical mechanism responsible for PCH remains uncertain more than 25 y after its discovery. Experimental research has indicated that neither heating nor acoustic cavitation, the predominant mechanisms for bioeffects of ultrasound, is responsible for PCH. Furthermore, proposed theoretical mechanisms based on gas body activation, on alveolar resonance and on impulsive generation of liquid droplets all appear unlikely to be responsible for PCH, owing to unrealistic model assumptions. Here, a simple model based on the acoustic radiation surface pressure (ARSP) at a tissue-air interface is hypothesized as the mechanism for PCH. The ARSP model seems to explain some features of PCH, including the approximate frequency independence of PCH thresholds, and the dependence of thresholds on biological factors. However, ARSP evaluated for experimental threshold conditions appear to be too weak to fully account for stress failure of pulmonary capillaries, gauging by known stresses for injurious physiological conditions. Furthermore, consideration of bulk properties of lung tissue suggests substantial transmission of ultrasound through the pleura, with reduced ARSP and potential involvement of additional mechanisms within the pulmonary interior. Although these recent findings advance our knowledge, only a full understanding of PCH mechanisms will allow development of science-based safety assurance for pulmonary ultrasound. PMID:27649878

Advanced Diagnostics for Reacting Flows

DTIC Science & Technology

2006-06-01

TECHNICAL DISCUSSION: 1. Infrared-PLIF Imaging Diagnostics using Vibrational Transitions IR-PLIF allows for imaging a group of molecular species important...excitation of IR-active vibrational modes with imaging of the subsequent vibrational fluorescence. Quantitative interpretation requires knowledge of...the vibrational energy transfer processes, and hence in recent years we have been developing models for infrared fluorescence. During the past year

Are Clinical Diagnoses of Alzheimer's Disease and Other Dementias Affected by Education and Self-Reported Race?

ERIC Educational Resources Information Center

Teresi, Jeanne A.; Grober, Ellen; Eimicke, Joseph P.; Ehrlich, Amy R.

2012-01-01

A randomized controlled trial examined whether the diagnostic process for Alzheimer's disease and other dementias may be influenced by knowledge of the patient's education and/or self-reported race. Four conditions were implemented: diagnostic team knows (a) race and education, (b) education only, (c) race only, or (d) neither. Diagnosis and…

Development and Validation of a Diagnostic Grammar Test for Japanese Learners of English

ERIC Educational Resources Information Center

Koizumi, Rie; Sakai, Hideki; Ido, Takahiro; Ota, Hiroshi; Hayama, Megumi; Sato, Masatoshi; Nemoto, Akiko

2011-01-01

This article reports on the development and validation of the English Diagnostic Test of Grammar (EDiT Grammar) for Japanese learners of English. From among the many aspects of grammar, this test focuses on the knowledge of basic English noun phrases (NPs), especially their internal structures, because previous research has indicated the…

Negotiating Knowledge: Parents' Experience of the Neuropsychiatric Diagnostic Process for Children with Autism

ERIC Educational Resources Information Center

Carlsson, Emilia; Miniscalco, Carmela; Kadesjö, Björn; Laakso, Katja

2016-01-01

Background: Parents often recognize problems in their child's development earlier than health professionals do and there is new emphasis on the importance of involving parents in the diagnostic process. In Gothenburg, Sweden, over 100 children were identified as having an autism spectrum disorder (ASD) in 2009-11 through a general population…

Comparing Eighth-Grade Diagnostic Test Results for Korean, Czech, and American Students.

ERIC Educational Resources Information Center

Um, Eunkyoung; Dogan, Enis; Im, Seongah; Tatsuoka, Kimumi; Corter, James E.

Diagnostic analyses were conducted on data from the Third International Mathematics and Science Study second population (TIMSS-R; 1999) from the United States, Korea, and the Czech Republic in terms of test item attributes (i.e., content, processing skills, and item format) and inferred students' knowledge. The Rule Space model (K. Tatsuoka, 1998)…

CDP

Cancer.gov

The Cancer Diagnosis Program strives to improve the diagnosis and assessment of cancer by effectively moving new scientific knowledge into clinical practice. This national program stimulates, coordinates and funds resources and research for the development of innovative in vitro diagnostics, novel diagnostic technologies and appropriate human specimens in order to better characterize cancers and allow improved medical decision making and evaluation of response to treatment.

Resources | CDP

Cancer.gov

The Cancer Diagnosis Program strives to improve the diagnosis and assessment of cancer by effectively moving new scientific knowledge into clinical practice. This national program stimulates, coordinates and funds resources and research for the development of innovative in vitro diagnostics, novel diagnostic technologies and appropriate human specimens in order to better characterize cancers and allow improved medical decision making and evaluation of response to treatment.

Development of a Diagnostic System for Information Ethics Education

ERIC Educational Resources Information Center

Shiota, Shingo; Sakai, Kyohei; Kobayashi, Keita

2016-01-01

This paper presents a new diagnostic system for information ethics education. In order to educate children about information ethics, it is necessary to know the stage at which they currently are in terms of their knowledge of the same. Some actual condition surveys have been conducted by the Cabinet Office and the National Police Agency to gauge…

Accuracy of dementia diagnosis: a direct comparison between radiologists and a computerized method.

PubMed

Klöppel, Stefan; Stonnington, Cynthia M; Barnes, Josephine; Chen, Frederick; Chu, Carlton; Good, Catriona D; Mader, Irina; Mitchell, L Anne; Patel, Ameet C; Roberts, Catherine C; Fox, Nick C; Jack, Clifford R; Ashburner, John; Frackowiak, Richard S J

2008-11-01

There has been recent interest in the application of machine learning techniques to neuroimaging-based diagnosis. These methods promise fully automated, standard PC-based clinical decisions, unbiased by variable radiological expertise. We recently used support vector machines (SVMs) to separate sporadic Alzheimer's disease from normal ageing and from fronto-temporal lobar degeneration (FTLD). In this study, we compare the results to those obtained by radiologists. A binary diagnostic classification was made by six radiologists with different levels of experience on the same scans and information that had been previously analysed with SVM. SVMs correctly classified 95% (sensitivity/specificity: 95/95) of sporadic Alzheimer's disease and controls into their respective groups. Radiologists correctly classified 65-95% (median 89%; sensitivity/specificity: 88/90) of scans. SVM correctly classified another set of sporadic Alzheimer's disease in 93% (sensitivity/specificity: 100/86) of cases, whereas radiologists ranged between 80% and 90% (median 83%; sensitivity/specificity: 80/85). SVMs were better at separating patients with sporadic Alzheimer's disease from those with FTLD (SVM 89%; sensitivity/specificity: 83/95; compared to radiological range from 63% to 83%; median 71%; sensitivity/specificity: 64/76). Radiologists were always accurate when they reported a high degree of diagnostic confidence. The results show that well-trained neuroradiologists classify typical Alzheimer's disease-associated scans comparable to SVMs. However, SVMs require no expert knowledge and trained SVMs can readily be exchanged between centres for use in diagnostic classification. These results are encouraging and indicate a role for computerized diagnostic methods in clinical practice.

Accuracy of dementia diagnosis—a direct comparison between radiologists and a computerized method

PubMed Central

Stonnington, Cynthia M.; Barnes, Josephine; Chen, Frederick; Chu, Carlton; Good, Catriona D.; Mader, Irina; Mitchell, L. Anne; Patel, Ameet C.; Roberts, Catherine C.; Fox, Nick C.; Jack, Clifford R.; Ashburner, John; Frackowiak, Richard S. J.

2008-01-01

There has been recent interest in the application of machine learning techniques to neuroimaging-based diagnosis. These methods promise fully automated, standard PC-based clinical decisions, unbiased by variable radiological expertise. We recently used support vector machines (SVMs) to separate sporadic Alzheimer's disease from normal ageing and from fronto-temporal lobar degeneration (FTLD). In this study, we compare the results to those obtained by radiologists. A binary diagnostic classification was made by six radiologists with different levels of experience on the same scans and information that had been previously analysed with SVM. SVMs correctly classified 95% (sensitivity/specificity: 95/95) of sporadic Alzheimer's disease and controls into their respective groups. Radiologists correctly classified 65–95% (median 89%; sensitivity/specificity: 88/90) of scans. SVM correctly classified another set of sporadic Alzheimer's disease in 93% (sensitivity/specificity: 100/86) of cases, whereas radiologists ranged between 80% and 90% (median 83%; sensitivity/specificity: 80/85). SVMs were better at separating patients with sporadic Alzheimer's disease from those with FTLD (SVM 89%; sensitivity/specificity: 83/95; compared to radiological range from 63% to 83%; median 71%; sensitivity/specificity: 64/76). Radiologists were always accurate when they reported a high degree of diagnostic confidence. The results show that well-trained neuroradiologists classify typical Alzheimer's disease-associated scans comparable to SVMs. However, SVMs require no expert knowledge and trained SVMs can readily be exchanged between centres for use in diagnostic classification. These results are encouraging and indicate a role for computerized diagnostic methods in clinical practice. PMID:18835868

[Implementation of cytology images classification--the Bethesda 2001 System--in a group of screened women from Podlaskie region--effect evaluation].

PubMed

Zbroch, Tomasz; Knapp, Paweł Grzegorz; Knapp, Piotr Andrzej

2007-09-01

Increasing knowledge concerning carcinogenesis within cervical epithelium has forced us to make continues modifications of cytology classification of the cervical smears. Eventually, new descriptions of the submicroscopic cytomorphological abnormalities have enabled the implementation of Bethesda System which was meant to take place of the former Papanicolaou classification although temporarily both are sometimes used simultaneously. The aim of this study was to compare results of these two classification systems in the aspect of diagnostic accuracy verified by further tests of the diagnostic algorithm for the cervical lesion evaluation. The study was conducted in the group of women selected from general population, the criteria being the place of living and cervical cancer age risk group, in the consecutive periods of mass screening in Podlaski region. The performed diagnostic tests have been based on the commonly used algorithm, as well as identical laboratory and methodological conditions. Performed assessment revealed comparable diagnostic accuracy of both analyzing classifications, verified by histological examination, although with marked higher specificity for dysplastic lesions with decreased number of HSIL results and increased diagnosis of LSILs. Higher number of performed colposcopies and biopsies were an additional consequence of TBS classification. Results based on Bethesda System made it possible to find the sources and reasons of abnormalities with much greater precision, which enabled causing agent treatment. Two evaluated cytology classification systems, although not much different, depicted higher potential of TBS and better, more effective communication between cytology laboratory and gynecologist, making reasonable implementation of The Bethesda System in the daily cytology screening work.

Knowledge translation from continuing education to physiotherapy practice in classifying patients with low back pain.

PubMed

Karvonen, Eira; Paatelma, Markku; Kesonen, Jukka-Pekka; Heinonen, Ari O

2015-05-01

Physical therapists have used continuing education as a method of improving their skills in conducting clinical examination of patients with low back pain (LBP). The purpose of this study was to evaluate how well the pathoanatomical classification of patients in acute or subacute LBP can be learned and applied through a continuing education format. The patients were seen in a direct access setting. The study was carried out in a large health-care center in Finland. The analysis included a total of 57 patient evaluations generated by six physical therapists on patients with LBP. We analyzed the consistency and level of agreement of the six physiotherapists' (PTs) diagnostic decisions, who participated in a 5-day, intensive continuing education session and also compared those with the diagnostic opinions of two expert physical therapists, who were blind to the original diagnostic decisions. Evaluation of the physical therapists' clinical examination of the patients was conducted by the two experts, in order to determine the accuracy and percentage agreement of the pathoanatomical diagnoses. The percentage of agreement between the experts and PTs was 72-77%. The overall inter-examiner reliability (kappa coefficient) for the subgroup classification between the six PTs and two experts was 0.63 [95% confidence interval (CI): 0.47-0.77], indicating good agreement between the PTs and the two experts. The overall inter-examiner reliability between the two experts was 0.63 (0.49-0.77) indicating good level of agreement. Our results indicate that PTs' were able to apply their continuing education training to clinical reasoning and make consistently accurate pathoanatomic based diagnostic decisions for patients with LBP. This would suggest that continuing education short-courses provide a reasonable format for knowledge translation (KT) by which physical therapists can learn and apply new information related to the examination and differential diagnosis of patients in acute or subacute LBP.

Chagas disease diagnostic applications: present knowledge and future steps

PubMed Central

Balouz, Virginia; Agüero, Fernán; Buscaglia, Carlos A.

2017-01-01

Chagas disease, caused by the protozoan Trypanosoma cruzi, is a life-long and debilitating illness of major significance throughout Latin America, and an emergent threat to global public health. Being a neglected disease, the vast majority of Chagasic patients have limited access to proper diagnosis and treatment, and there is only a marginal investment into R&D for drug and vaccine development. In this context, identification of novel biomarkers able to transcend the current limits of diagnostic methods surfaces as a main priority in Chagas disease applied research. The expectation is that these novel biomarkers will provide reliable, reproducible and accurate results irrespective of the genetic background, infecting parasite strain, stage of disease, and clinical-associated features of Chagasic populations. In addition, they should be able to address other still unmet diagnostic needs, including early detection of congenital T. cruzi transmission, rapid assessment of treatment efficiency or failure, indication/prediction of disease progression and direct parasite typification in clinical samples. The lack of access of poor and neglected populations to essential diagnostics also stress the necessity of developing new methods operational in Point-of-Care (PoC) settings. In summary, emergent diagnostic tests integrating these novel and tailored tools should provide a significant impact on the effectiveness of current intervention schemes and on the clinical management of Chagasic patients. In this chapter, we discuss the present knowledge and possible future steps in Chagas disease diagnostic applications, as well as the opportunity provided by recent advances in high-throughput methods for biomarker discovery. PMID:28325368

Theorizing about Practice: Story Telling and Practical Knowledge in Cancer Diagnoses

ERIC Educational Resources Information Center

Zucchermaglio, Cristina; Alby, Francesca

2016-01-01

Purpose: This paper aims to analyze the organization of storytelling and its role in creating and sharing practical knowledge for cancer diagnosis in a medical community in Italy. Design/methodology/approach: The qualitative analysis draws upon different interactional data sets--naturally occurring diagnostic conversations among physicians in the…

Awareness of Diagnostic Error among Japanese Residents: a Nationwide Study.

PubMed

Nishizaki, Yuji; Shinozaki, Tomohiro; Kinoshita, Kensuke; Shimizu, Taro; Tokuda, Yasuharu

2018-04-01

Residents' understanding of diagnostic error may differ between countries. We sought to explore the relationship between diagnostic error knowledge and self-study, clinical knowledge, and experience. Our nationwide study involved postgraduate year 1 and 2 (PGY-1 and -2) Japanese residents. The Diagnostic Error Knowledge Assessment Test (D-KAT) and General Medicine In-Training Examination (GM-ITE) were administered at the end of the 2014 academic year. D-KAT scores were compared with the benchmark scores of US residents. Associations between D-KAT score and gender, PGY, emergency department (ED) rotations per month, mean number of inpatients handled at any given time, and mean daily minutes of self-study were also analyzed, both with and without adjusting for GM-ITE scores. Student's t test was used for comparisons with linear mixed models and structural equation models (SEM) to explore associations with D-KAT or GM-ITE scores. The mean D-KAT score among Japanese PGY-2 residents was significantly lower than that of their US PGY-2 counterparts (6.2 vs. 8.3, p < 0.001). GM-ITE scores correlated with ED rotations (≥6 rotations: 2.14; 0.16-4.13; p = 0.03), inpatient caseloads (5-9 patients: 1.79; 0.82-2.76; p < 0.001), and average daily minutes of self-study (≥91 min: 2.05; 0.56-3.53; p = 0.01). SEM revealed that D-KAT scores were directly associated with GM-ITE scores (ß = 0.37, 95% CI: 0.34-0.41) and indirectly associated with ED rotations (ß = 0.06, 95% CI: 0.02-0.10), inpatient caseload (ß = 0.04, 95% CI: 0.003-0.08), and average daily minutes of study (ß = 0.13, 95% CI: 0.09-0.17). Knowledge regarding diagnostic error among Japanese residents was poor compared with that among US residents. D-KAT scores correlated strongly with GM-ITE scores, and the latter scores were positively associated with a greater number of ED rotations, larger caseload (though only up to 15 patients), and more time spent studying.

Knowledge From Pictures (KFP)

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Paterra, Frank; Bailin, Sidney

1993-01-01

The old maxim goes: 'A picture is worth a thousand words'. The objective of the research reported in this paper is to demonstrate this idea as it relates to the knowledge acquisition process and the automated development of an expert system's rule base. A prototype tool, the Knowledge From Pictures (KFP) tool, has been developed which configures an expert system's rule base by an automated analysis of and reasoning about a 'picture', i.e., a graphical representation of some target system to be supported by the diagnostic capabilities of the expert system under development. This rule base, when refined, could then be used by the expert system for target system monitoring and fault analysis in an operational setting. Most people, when faced with the problem of understanding the behavior of a complicated system, resort to the use of some picture or graphical representation of the system as an aid in thinking about it. This depiction provides a means of helping the individual to visualize the bahavior and dynamics of the system under study. An analysis of the picture augmented with the individual's background information, allows the problem solver to codify knowledge about the system. This knowledge can, in turn, be used to develop computer programs to automatically monitor the system's performance. The approach taken is this research was to mimic this knowledge acquisition paradigm. A prototype tool was developed which provides the user: (1) a mechanism for graphically representing sample system-configurations appropriate for the domain, and (2) a linguistic device for annotating the graphical representation with the behaviors and mutual influences of the components depicted in the graphic. The KFP tool, reasoning from the graphical depiction along with user-supplied annotations of component behaviors and inter-component influences, generates a rule base that could be used in automating the fault detection, isolation, and repair of the system.

In utero diagnosis of PHACE syndrome by fetal magnetic resonance imaging (MRI).

PubMed

Fernández-Mayoralas, Daniel Martín; Recio-Rodríguez, Manuel; Fernández-Perrone, Ana Laura; Jiménez-de-la-Peña, Mar; Muñoz-Jareño, Nuria; Fernández-Jaén, Alberto

2014-01-01

The acronym PHACE describes the association of facial hemangioma with anomalies of the posterior fossa, cerebral arteries, and cardiovascular and ocular alterations. This study presents a case of diagnostic suspicion based on fetal MRI. We report the case of a pregnant woman whose 26-week MRI revealed a female fetus with hypoplasia of the right cerebellar hemisphere and right microphthalmia, leading to the suspicion of PHACE syndrome. The diagnosis was confirmed at birth, together with other criteria: facial hemangioma, absent posterior inferior cerebellar artery, and dysplasia of the right internal carotid artery. To our knowledge, this is the first live case described prenatally with both ocular and cerebellar findings on fetal MRI that suggest PHACE syndrome. The prenatal presence of 2 PHACE criteria led to the suspicion of this syndrome, and prenatal diagnostic criteria might be developed to improve information regarding the prognosis of cerebellar malformations.

[Quality of diagnosis and prophylaxis of HIV-infection in military clinical institutions and related problems in training medical personnel].

PubMed

Volzhanin, V M; Bulan'kov, Iu I; Bolekhan, V N; Vasil'ev, V V; Orlova, E S

2009-06-01

The analysis of results of laboratorial diagnostics of HIV-infection in multiprofile treatment institute of the Ministry of Defense of RF, questioning of medical staff on the questions of diagnostics and treatment of HIV-infection discovered several disadvantages in the system of training of the physicians in this sphere. Insufficient level of knowledge of practical aspects of HIV-infection causes baseless quantity of screening laboratorial tests (up to 70%). It leads to grand material inputs of the Ministry of Defense of RF. The authors propose an elaborated guidance manual for teachers, attending physicians and students of academies on studying questions of HIV-infection, based on the principle of "transparent study", on broad engaging of different departments to the process of teaching, on consideration of profiles of cycles of studying, of levels of adoption, types of lessons, volume of study time.

Hepatocellular carcinoma: Advances in diagnostic imaging.

PubMed

Sun, Haoran; Song, Tianqiang

2015-10-01

Thanks to the growing knowledge on biological behaviors of hepatocellular carcinomas (HCC), as well as continuous improvement in imaging techniques and experienced interpretation of imaging features of the nodules in cirrhotic liver, the detection and characterization of HCC has improved in the past decade. A number of practice guidelines for imaging diagnosis have been developed to reduce interpretation variability and standardize management of HCC, and they are constantly updated with advances in imaging techniques and evidence based data from clinical series. In this article, we strive to review the imaging techniques and the characteristic features of hepatocellular carcinoma associated with cirrhotic liver, with emphasis on the diagnostic value of advanced magnetic resonance imaging (MRI) techniques and utilization of hepatocyte-specific MRI contrast agents. We also briefly describe the concept of liver imaging reporting and data systems and discuss the consensus and controversy of major practice guidelines.

ViDI: Virtual Diagnostics Interface. Volume 1; The Future of Wind Tunnel Testing

NASA Technical Reports Server (NTRS)

Fleming, Gary A. (Technical Monitor); Schwartz, Richard J.

2004-01-01

The quality of data acquired in a given test facility ultimately resides within the fidelity and implementation of the instrumentation systems. Over the last decade, the emergence of robust optical techniques has vastly expanded the envelope of measurement possibilities. At the same time the capabilities for data processing, data archiving and data visualization required to extract the highest level of knowledge from these global, on and off body measurement techniques have equally expanded. Yet today, while the instrumentation has matured to the production stage, an optimized solution for gaining knowledge from the gigabytes of data acquired per test (or even per test point) is lacking. A technological void has to be filled in order to possess a mechanism for near-real time knowledge extraction during wind tunnel experiments. Under these auspices, the Virtual Diagnostics Interface, or ViDI, was developed.

Robotic and artificial intelligence for keyhole neurosurgery: the ROBOCAST project, a multi-modal autonomous path planner.

PubMed

De Momi, E; Ferrigno, G

2010-01-01

The robot and sensors integration for computer-assisted surgery and therapy (ROBOCAST) project (FP7-ICT-2007-215190) is co-funded by the European Union within the Seventh Framework Programme in the field of information and communication technologies. The ROBOCAST project focuses on robot- and artificial-intelligence-assisted keyhole neurosurgery (tumour biopsy and local drug delivery along straight or turning paths). The goal of this project is to assist surgeons with a robotic system controlled by an intelligent high-level controller (HLC) able to gather and integrate information from the surgeon, from diagnostic images, and from an array of on-field sensors. The HLC integrates pre-operative and intra-operative diagnostics data and measurements, intelligence augmentation, multiple-robot dexterity, and multiple sensory inputs in a closed-loop cooperating scheme including a smart interface for improved haptic immersion and integration. This paper, after the overall architecture description, focuses on the intelligent trajectory planner based on risk estimation and human criticism. The current status of development is reported, and first tests on the planner are shown by using a real image stack and risk descriptor phantom. The advantages of using a fuzzy risk description are given by the possibility of upgrading the knowledge on-field without the intervention of a knowledge engineer.

Integrating exhaled breath diagnostics by disease-sniffing dogs with instrumental laboratory analysis.

PubMed

Pleil, Joachim; Giese, Roger

2017-09-07

Dogs have been studied for many years as a medical diagnostic tool to detect a pre-clinical disease state by sniffing emissions directly from a human or an in vitro biological sample. Some of the studies report high sensitivity and specificity in blinded case-control studies. However, in these studies it is completely unknown as to which suites of chemicals the dogs detect and how they ultimately interpret this information amidst confounding background odors. Herein, we consider the advantages and challenges of canine olfaction for early (meaningful) detection of cancer, and propose an experimental concept to narrow the molecular signals used by the dog for sample classification to laboratory-based instrumental analysis. This serves two purposes; first, in contrast to dogs, analytical methods could be quickly up-scaled for high throughput sampling. Second, the knowledge gained from identifying probative chemicals could be helpful in learning more about biochemical pathways and disease progression. We focus on exhaled breath aerosol, arguing that the semi-volatile fraction should be given more attention. Ultimately, we conclude that the interaction between dog-based and instrument-based research will be mutually beneficial and accelerate progress towards early detection of cancer by breath analysis.

Direct, Label-Free, and Rapid Transistor-Based Immunodetection in Whole Serum.

PubMed

Gutiérrez-Sanz, Óscar; Andoy, Nesha M; Filipiak, Marcin S; Haustein, Natalie; Tarasov, Alexey

2017-09-22

Transistor-based biosensors fulfill many requirements posed upon transducers for future point-of-care diagnostic devices such as scalable fabrication and label-free and real-time quantification of chemical and biological species with high sensitivity. However, the short Debye screening length in physiological samples (<1 nm) has been a major drawback so far, preventing direct measurements in serum. In this work, we demonstrate how tailoring the sensing surface with short specific biological receptors and a polymer polyethylene glycol (PEG) can strongly enhance the sensor response. In addition, the sensor performance can be dramatically improved if the measurements are performed at elevated temperatures (37 °C instead of 21 °C). With this novel approach, highly sensitive and selective detection of a representative immunosensing parameter-human thyroid-stimulating hormone-is shown over a wide measuring range with subpicomolar detection limits in whole serum. To the best of our knowledge, this is the first demonstration of direct immunodetection in whole serum using transistor-based biosensors, without the need for sample pretreatment, labeling, or washing steps. The presented sensor is low-cost, can be easily integrated into portable diagnostics devices, and offers a competitive performance compared to state-of-the-art central laboratory analyzers.

Drug Induced Liver Injury: Can Biomarkers Assist RUCAM in Causality Assessment?

PubMed Central

Teschke, Rolf; Schulze, Johannes; Eickhoff, Axel; Danan, Gaby

2017-01-01

Drug induced liver injury (DILI) is a potentially serious adverse reaction in a few susceptible individuals under therapy by various drugs. Health care professionals facing DILI are confronted with a wealth of drug-unrelated liver diseases with high incidence and prevalence rates, which can confound the DILI diagnosis. Searching for alternative causes is a key element of RUCAM (Roussel Uclaf Causality Assessment Method) to assess rigorously causality in suspected DILI cases. Diagnostic biomarkers as blood tests would be a great help to clinicians, regulators, and pharmaceutical industry would be more comfortable if, in addition to RUCAM, causality of DILI can be confirmed. High specificity and sensitivity are required for any diagnostic biomarker. Although some risk factors are available to evaluate liver safety of drugs in patients, no valid diagnostic or prognostic biomarker exists currently for idiosyncratic DILI when a liver injury occurred. Identifying a biomarker in idiosyncratic DILI requires detailed knowledge of cellular and biochemical disturbances leading to apoptosis or cell necrosis and causing leakage of specific products in blood. As idiosyncratic DILI is typically a human disease and hardly reproducible in animals, pathogenetic events and resulting possible biomarkers remain largely undisclosed. Potential new diagnostic biomarkers should be evaluated in patients with DILI and RUCAM-based established causality. In conclusion, causality assessment in cases of suspected idiosyncratic DILI is still best achieved using RUCAM since specific biomarkers as diagnostic blood tests that could enhance RUCAM results are not yet available. PMID:28398242

Comparison of dermatoscopic diagnostic algorithms based on calculation: The ABCD rule of dermatoscopy, the seven-point checklist, the three-point checklist and the CASH algorithm in dermatoscopic evaluation of melanocytic lesions.

PubMed

Unlu, Ezgi; Akay, Bengu N; Erdem, Cengizhan

2014-07-01

Dermatoscopic analysis of melanocytic lesions using the CASH algorithm has rarely been described in the literature. The purpose of this study was to compare the sensitivity, specificity, and diagnostic accuracy rates of the ABCD rule of dermatoscopy, the seven-point checklist, the three-point checklist, and the CASH algorithm in the diagnosis and dermatoscopic evaluation of melanocytic lesions on the hairy skin. One hundred and fifteen melanocytic lesions of 115 patients were examined retrospectively using dermatoscopic images and compared with the histopathologic diagnosis. Four dermatoscopic algorithms were carried out for all lesions. The ABCD rule of dermatoscopy showed sensitivity of 91.6%, specificity of 60.4%, and diagnostic accuracy of 66.9%. The seven-point checklist showed sensitivity, specificity, and diagnostic accuracy of 87.5, 65.9, and 70.4%, respectively; the three-point checklist 79.1, 62.6, 66%; and the CASH algorithm 91.6, 64.8, and 70.4%, respectively. To our knowledge, this is the first study that compares the sensitivity, specificity and diagnostic accuracy of the ABCD rule of dermatoscopy, the three-point checklist, the seven-point checklist, and the CASH algorithm for the diagnosis of melanocytic lesions on the hairy skin. In our study, the ABCD rule of dermatoscopy and the CASH algorithm showed the highest sensitivity for the diagnosis of melanoma. © 2014 Japanese Dermatological Association.

Isomorphic pressures, institutional strategies, and knowledge creation in the health care sector.

PubMed

Yang, Chen-Wei; Fang, Shih-Chieh; Huang, Wei-Min

2007-01-01

Health care organizations are facing surprisingly complex challenges, including new treatment and diagnostic technologies, ongoing pressures for health care institutional reform, the emergence of new organizational governance structures, and knowledge creation for the health care system. To maintain legitimacy in demanding environments, organizations tend to copy practices of similar organizations, which lead to isomorphism, and to use internal strategies to accommodate changes. A concern is that a poor fit between isomorphic pressures and internal strategies can interfere with developmental processes, such as knowledge creation. The purposes of this article are to, first, develop a set of propositions, based on institutional theory, as a theoretical framework that might explain the influence of isomorphic pressures on institutional processes through which knowledge is created within the health care sector and, second, propose that a good fit between isomorphic pressures factors and health care organizations' institutional strategic choices will enhance the health care organizations' ability to create knowledge. To develop a theoretical framework, we developed a set of propositions based on literature pertaining to the institutional theory perspective of isomorphic pressures and the response of health care organizations to isomorphic pressures. Institutional theory perspectives of isomorphic pressures and institutional strategies may provide a new understanding for health care organizations seeking effective knowledge creation strategies within institutional environment of health care sector. First, the ability to identify three forces for isomorphic change is critical for managers. Second, the importance of a contingency approach by health care managers can lead to strategies tailoring to cope with uncertainties facing their organizations.

Intentional retrieval suppression can conceal guilty knowledge in ERP memory detection tests☆

PubMed Central

Bergström, Zara M.; Anderson, Michael C.; Buda, Marie; Simons, Jon S.; Richardson-Klavehn, Alan

2013-01-01

Brain-activity markers of guilty knowledge have been promoted as accurate and reliable measures for establishing criminal culpability. Tests based on these markers interpret the presence or absence of memory-related neural activity as diagnostic of whether or not incriminating information is stored in a suspect's brain. This conclusion critically relies on the untested assumption that reminders of a crime uncontrollably elicit memory-related brain activity. However, recent research indicates that, in some circumstances, humans can control whether they remember a previous experience by intentionally suppressing retrieval. We examined whether people could use retrieval suppression to conceal neural evidence of incriminating memories as indexed by Event-Related Potentials (ERPs). When people were motivated to suppress crime retrieval, their memory-related ERP effects were significantly decreased, allowing guilty individuals to evade detection. Our findings indicate that brain measures of guilty knowledge may be under criminals’ intentional control and place limits on their use in legal settings. PMID:23664804

The psychodynamics of borderline psychopathology.

PubMed

Corradi, Richard B

2015-01-01

The concept of borderline personality disorder (BPD) remains problematic despite psychiatrists' general familiarity with its DSM diagnostic criteria. The diagnosis of BPD is frequently based simply on the DSM checklist of traits and symptoms without knowledge of their origins or significance. Misdiagnosis is common, as is lack of recognition of the full complexity of this severe personality disorder and the nature of the vulnerabilities that underlie its myriad forms of pathology. The stresses of ordinary life are often too much for people with BPD. Knowledge of the nature and origins of their stress points, such as their great fear of loss or rejection, is necessary for adequate diagnosis and treatment. The author addresses how signature features of the disorder relate to psychosocial development, how they correlate with failed developmental milestones, and how they can be understood psychodynamically. This is essential knowledge for psychotherapists because the pathological interpersonal relationships of the borderline patient will be repeated and acted out in the transference, whatever the modality or intensity of treatment.

Predicate calculus, artificial intelligence, and workers' compensation.

PubMed

Harber, P; McCoy, J M

1989-05-01

Application of principles of predicate calculus (PC) and artificial intelligence (AI) search methods to occupational medicine can meet several goals. First, they can improve understanding of the diagnostic process and recognition of the sources of uncertainty in knowledge and in case specific information. Second, PC provides a rational means of resolving differences in conclusion based upon the same premises. Third, understanding of these principles allows separation of knowledge (facts) from the process by which they are used and therefore facilitates development of AI-based expert systems. Application of PC to recognizing causation of pulmonary fibrosis is demonstrated in this paper, providing a method that can be generalized to other problems in occupational medicine. Application of PC and understanding of AI search routines may be particularly applicable to workers' compensation where explicit statement of rational and inferential process is necessary. This approach is useful in the diagnosis of occupational lung disease and may be particularly valuable in workers' compensation considerations, wherein explicit statement of rationale is needed.

Data acquisition for a real time fault monitoring and diagnosis knowledge-based system for space power system

NASA Technical Reports Server (NTRS)

Wilhite, Larry D.; Lee, S. C.; Lollar, Louis F.

1989-01-01

The design and implementation of the real-time data acquisition and processing system employed in the AMPERES project is described, including effective data structures for efficient storage and flexible manipulation of the data by the knowledge-based system (KBS), the interprocess communication mechanism required between the data acquisition system and the KBS, and the appropriate data acquisition protocols for collecting data from the sensors. Sensor data are categorized as critical or noncritical data on the basis of the inherent frequencies of the signals and the diagnostic requirements reflected in their values. The critical data set contains 30 analog values and 42 digital values and is collected every 10 ms. The noncritical data set contains 240 analog values and is collected every second. The collected critical and noncritical data are stored in separate circular buffers. Buffers are created in shared memory to enable other processes, i.e., the fault monitoring and diagnosis process and the user interface process, to freely access the data sets.

Separating Business Logic from Medical Knowledge in Digital Clinical Workflows Using Business Process Model and Notation and Arden Syntax.

PubMed

de Bruin, Jeroen S; Adlassnig, Klaus-Peter; Leitich, Harald; Rappelsberger, Andrea

2018-01-01

Evidence-based clinical guidelines have a major positive effect on the physician's decision-making process. Computer-executable clinical guidelines allow for automated guideline marshalling during a clinical diagnostic process, thus improving the decision-making process. Implementation of a digital clinical guideline for the prevention of mother-to-child transmission of hepatitis B as a computerized workflow, thereby separating business logic from medical knowledge and decision-making. We used the Business Process Model and Notation language system Activiti for business logic and workflow modeling. Medical decision-making was performed by an Arden-Syntax-based medical rule engine, which is part of the ARDENSUITE software. We succeeded in creating an electronic clinical workflow for the prevention of mother-to-child transmission of hepatitis B, where institution-specific medical decision-making processes could be adapted without modifying the workflow business logic. Separation of business logic and medical decision-making results in more easily reusable electronic clinical workflows.

Applying artificial intelligence technology to support decision-making in nursing: A case study in Taiwan.

PubMed

Liao, Pei-Hung; Hsu, Pei-Ti; Chu, William; Chu, Woei-Chyn

2015-06-01

This study applied artificial intelligence to help nurses address problems and receive instructions through information technology. Nurses make diagnoses according to professional knowledge, clinical experience, and even instinct. Without comprehensive knowledge and thinking, diagnostic accuracy can be compromised and decisions may be delayed. We used a back-propagation neural network and other tools for data mining and statistical analysis. We further compared the prediction accuracy of the previous methods with an adaptive-network-based fuzzy inference system and the back-propagation neural network, identifying differences in the questions and in nurse satisfaction levels before and after using the nursing information system. This study investigated the use of artificial intelligence to generate nursing diagnoses. The percentage of agreement between diagnoses suggested by the information system and those made by nurses was as much as 87 percent. When patients are hospitalized, we can calculate the probability of various nursing diagnoses based on certain characteristics. © The Author(s) 2013.

Systematic reviews and knowledge translation.

PubMed Central

Tugwell, Peter; Robinson, Vivian; Grimshaw, Jeremy; Santesso, Nancy

2006-01-01

Proven effective interventions exist that would enable all countries to meet the Millennium Development Goals. However, uptake and use of these interventions in the poorest populations is at least 50% less than in the richest populations within each country. Also, we have recently shown that community effectiveness of interventions is lower for the poorest populations due to a "staircase" effect of lower coverage/access, worse diagnostic accuracy, less provider compliance and less consumer adherence. We propose an evidence-based framework for equity-oriented knowledge translation to enhance community effectiveness and health equity. This framework is represented as a cascade of steps to assess and prioritize barriers and thus choose effective knowledge translation interventions that are tailored for relevant audiences (public, patient, practitioner, policy-maker, press and private sector), as well as the evaluation, monitoring and sharing of these strategies. We have used two examples of effective interventions (insecticide-treated bednets to prevent malaria and childhood immunization) to illustrate how this framework can provide a systematic method for decision-makers to ensure the application of evidence-based knowledge in disadvantaged populations. Future work to empirically validate and evaluate the usefulness of this framework is needed. We invite researchers and implementers to use the cascade for equity-oriented knowledge translation as a guide when planning implementation strategies for proven effective interventions. We also encourage policy-makers and health-care managers to use this framework when deciding how effective interventions can be implemented in their own settings. PMID:16917652

Systematic reviews and knowledge translation.

PubMed

Tugwell, Peter; Robinson, Vivian; Grimshaw, Jeremy; Santesso, Nancy

2006-08-01

Proven effective interventions exist that would enable all countries to meet the Millennium Development Goals. However, uptake and use of these interventions in the poorest populations is at least 50% less than in the richest populations within each country. Also, we have recently shown that community effectiveness of interventions is lower for the poorest populations due to a "staircase" effect of lower coverage/access, worse diagnostic accuracy, less provider compliance and less consumer adherence. We propose an evidence-based framework for equity-oriented knowledge translation to enhance community effectiveness and health equity. This framework is represented as a cascade of steps to assess and prioritize barriers and thus choose effective knowledge translation interventions that are tailored for relevant audiences (public, patient, practitioner, policy-maker, press and private sector), as well as the evaluation, monitoring and sharing of these strategies. We have used two examples of effective interventions (insecticide-treated bednets to prevent malaria and childhood immunization) to illustrate how this framework can provide a systematic method for decision-makers to ensure the application of evidence-based knowledge in disadvantaged populations. Future work to empirically validate and evaluate the usefulness of this framework is needed. We invite researchers and implementers to use the cascade for equity-oriented knowledge translation as a guide when planning implementation strategies for proven effective interventions. We also encourage policy-makers and health-care managers to use this framework when deciding how effective interventions can be implemented in their own settings.

Overview of MDX-A System for Medical Diagnosis

PubMed Central

Mittal, S.; Chandrasekaran, B.; Smith, J.

1979-01-01

We describe the design and performance of MDX, an experimental medical diagnosis system, which currently diagnoses in the syndrome called Cholestasis. The needed medical knowledge is represented in a scheme called conceptual structures, which can be viewed as a collection of conceptual experts interacting according to certain well-defined principles. MDX has three components: the diagnostic system, a patient data base and a radiology consultant. We describe these components, the inter-expert communication system and the query language used by these components. The system is illustrated by means of its performance on a real case.

Identification of Patients at Risk for Hereditary Colorectal Cancer

PubMed Central

Mishra, Nitin; Hall, Jason

2012-01-01

Diagnosis of hereditary colorectal cancer syndromes requires clinical suspicion and knowledge of such syndromes. Lynch syndrome is the most common cause of hereditary colorectal cancer. Other less common causes include familial adenomatous polyposis (FAP), Peutz-Jeghers syndrome (PJS), juvenile polyposis syndrome, and others. There have been a growing number of clinical and molecular tools used to screen and test at risk individuals. Screening tools include diagnostic clinical criteria, family history, genetic prediction models, and tumor testing. Patients who are high risk based on screening should be referred for genetic testing. PMID:23730221

DISCONTOOLS: a database to identify research gaps on vaccines, pharmaceuticals and diagnostics for the control of infectious diseases of animals.

PubMed

O'Brien, Declan; Scudamore, Jim; Charlier, Johannes; Delavergne, Morgane

2017-01-03

The public and private sector in the EU spend around €800 million per year on animal health and welfare related research. An objective process to identify critical gaps in knowledge and available control tools should aid the prioritisation of research in order to speed up the development of new or improved diagnostics, vaccines and pharmaceuticals and reduce the burden of animal diseases. Here, we describe the construction of a database based on expert consultation for 52 infectious diseases of animals. For each disease, an expert group produced a disease and product analysis document that formed the basis for gap analysis and prioritisation. The prioritisation model was based on a closed scoring system, employing identical weights for six evaluation criteria (disease knowledge; impact on animal health and welfare; impact on public health; impact on wider society; impact on trade; control tools). The diseases were classified into three groups: epizootic diseases, food-producing animal complexes or zoonotic diseases. The highly ranked diseases in the prioritisation model comprised mostly zoonotic and epizootic diseases with important gaps identified in vaccine development and pharmaceuticals, respectively. The most important outcome is the identification of key research needs by disease. The rankings and research needs by disease are provided on a public website ( www.discontools.eu ) which is currently being updated based on new expert consultations. As such, it can become a reference point for funders of research including the European Commission, member states, foundations, trusts along with private industry to prioritise research. This will deliver benefits in terms of animal health and welfare but also public health, societal benefits and a safe and secure food supply.

Parent Refusal of Topical Fluoride for Their Children: Clinical Strategies and Future Research Priorities to Improve Evidence-Based Pediatric Dental Practice.

PubMed

Chi, Donald L

2017-07-01

A growing number of parents are refusing topical fluoride for their children during preventive dental and medical visits. This nascent clinical and public health problem warrants attention from dental professionals and the scientific community. Clinical and community-based strategies are available to improve fluoride-related communications with parents and the public. In terms of future research priorities, there is a need to develop screening tools to identify parents who are likely to refuse topical fluoride and diagnostic instruments to uncover the reasons for topical fluoride refusal. This knowledge will lead to evidence-based strategies that can be widely disseminated into clinical practice. Copyright © 2017 Elsevier Inc. All rights reserved.

A Memory Based Model of Posttraumatic Stress Disorder: Evaluating Basic Assumptions Underlying the PTSD Diagnosis

PubMed Central

Rubin, David C.; Berntsen, Dorthe; Johansen, Malene Klindt

2009-01-01

In the mnemonic model of PTSD, the current memory of a negative event, not the event itself determines symptoms. The model is an alternative to the current event-based etiology of PTSD represented in the DSM. The model accounts for important and reliable findings that are often inconsistent with the current diagnostic view and that have been neglected by theoretical accounts of the disorder, including the following observations. The diagnosis needs objective information about the trauma and peritraumatic emotions, but uses retrospective memory reports that can have substantial biases. Negative events and emotions that do not satisfy the current diagnostic criteria for a trauma can be followed by symptoms that would otherwise qualify for PTSD. Predisposing factors that affect the current memory have large effects on symptoms. The inability-to-recall-an-important-aspect-of-the-trauma symptom does not correlate with other symptoms. Loss or enhancement of the trauma memory affects PTSD symptoms in predictable ways. Special mechanisms that apply only to traumatic memories are not needed, increasing parsimony and the knowledge that can be applied to understanding PTSD. PMID:18954211

Neuroimaging-based biomarkers in psychiatry: clinical opportunities of a paradigm shift.

PubMed

Fu, Cynthia H Y; Costafreda, Sergi G

2013-09-01

Neuroimaging research has substantiated the functional and structural abnormalities underlying psychiatric disorders but has, thus far, failed to have a significant impact on clinical practice. Recently, neuroimaging-based diagnoses and clinical predictions derived from machine learning analysis have shown significant potential for clinical translation. This review introduces the key concepts of this approach, including how the multivariate integration of patterns of brain abnormalities is a crucial component. We survey recent findings that have potential application for diagnosis, in particular early and differential diagnoses in Alzheimer disease and schizophrenia, and the prediction of clinical response to treatment in depression. We discuss the specific clinical opportunities and the challenges for developing biomarkers for psychiatry in the absence of a diagnostic gold standard. We propose that longitudinal outcomes, such as early diagnosis and prediction of treatment response, offer definite opportunities for progress. We propose that efforts should be directed toward clinically challenging predictions in which neuroimaging may have added value, compared with the existing standard assessment. We conclude that diagnostic and prognostic biomarkers will be developed through the joint application of expert psychiatric knowledge in addition to advanced methods of analysis.

Component-Level Electronic-Assembly Repair (CLEAR) System Architecture

NASA Technical Reports Server (NTRS)

Oeftering, Richard C.; Bradish, Martin A.; Juergens, Jeffrey R.; Lewis, Michael J.; Vrnak, Daniel R.

2011-01-01

This document captures the system architecture for a Component-Level Electronic-Assembly Repair (CLEAR) capability needed for electronics maintenance and repair of the Constellation Program (CxP). CLEAR is intended to improve flight system supportability and reduce the mass of spares required to maintain the electronics of human rated spacecraft on long duration missions. By necessity it allows the crew to make repairs that would otherwise be performed by Earth based repair depots. Because of practical knowledge and skill limitations of small spaceflight crews they must be augmented by Earth based support crews and automated repair equipment. This system architecture covers the complete system from ground-user to flight hardware and flight crew and defines an Earth segment and a Space segment. The Earth Segment involves database management, operational planning, and remote equipment programming and validation processes. The Space Segment involves the automated diagnostic, test and repair equipment required for a complete repair process. This document defines three major subsystems including, tele-operations that links the flight hardware to ground support, highly reconfigurable diagnostics and test instruments, and a CLEAR Repair Apparatus that automates the physical repair process.

Commentary: Objective aids for the assessment of ADHD - further clarification of what FDA approval for marketing means and why NEBA might help clinicians. A response to Arns et al. (2016).

PubMed

Stein, Mark A; Snyder, Steven M; Rugino, Thomas A; Hornig, Mady

2016-06-01

Neuropsychiatric EEG-Based ADHD Assessment Aid (NEBA) is an EEG-based device designed to aid in the diagnostic process for ADHD by identifying individuals less likely to have ADHD by virtue of a lower theta/beta ratio. In using NEBA as an example, the Arns et al. commentary misstates the purpose of NEBA, which is to widen the differential rather than to make the diagnosis. Arns et al. caution about missing an ADHD diagnosis, but fail to mention the impact of overdiagnosis. If we are to advance our knowledge of the etiology and pathophysiology of ADHD, as well as develop tailored treatments and ultimately improve outcomes for ADHD, then biomarkers and objective assessment aids such as NEBA are needed to improve and refine diagnostic accuracy beyond symptom description and clinical history. © 2016 The Authors. Journal of Child Psychology and Psychiatry published by John Wiley & Sons Ltd on behalf of Association for Child and Adolescent Mental Health.

Strategies for Characterization of Low-Abundant Intact or Truncated Low-Molecular-Weight Proteins From Human Plasma.

PubMed

Cai, Tanxi; Yang, Fuquan

2017-01-01

Low-molecular-weight region (LMW, MW≤30kDa) of human serum/plasma proteins, including small intact proteins, truncated fragments of larger proteins, along with some other small components, has been associated with the ongoing physiological and pathological events, and thereby represent a treasure trove of diagnostic molecules. Great progress in the mining of novel biomarkers from this diagnostic treasure trove for disease diagnosis and health monitoring has been achieved based on serum samples from healthy individuals and patients and powerful new approaches in biochemistry and systems biology. However, cumulative evidence indicates that many potential LMW protein biomarkers might still have escaped from detection due to their low abundance, the dynamic complexity of serum/plasma, and the limited efficiency of characterization approaches. Here, we provide an overview of the current state of knowledge with respect to strategies for the characterization of low-abundant LMW proteins (small intact or truncated proteins) from human serum/plasma, involving prefractionation or enrichment methods to reduce dynamic range and mass spectrometry-based characterization of low-abundant LMW proteins. © 2017 Elsevier Inc. All rights reserved.

An image based vibration sensor for soft tissue modal analysis in a Digital Image Elasto Tomography (DIET) system.

PubMed

Feng, Sheng; Lotz, Thomas; Chase, J Geoffrey; Hann, Christopher E

2010-01-01

Digital Image Elasto Tomography (DIET) is a non-invasive elastographic breast cancer screening technology, based on image-based measurement of surface vibrations induced on a breast by mechanical actuation. Knowledge of frequency response characteristics of a breast prior to imaging is critical to maximize the imaging signal and diagnostic capability of the system. A feasibility analysis for a non-invasive image based modal analysis system is presented that is able to robustly and rapidly identify resonant frequencies in soft tissue. Three images per oscillation cycle are enough to capture the behavior at a given frequency. Thus, a sweep over critical frequency ranges can be performed prior to imaging to determine critical imaging settings of the DIET system to optimize its tumor detection performance.

Socio-demographic and academic correlates of clinical reasoning in a dental school in South Africa.

PubMed

Postma, T C; White, J G

2017-02-01

There are no empirical studies that describe factors that may influence the development of integrated clinical reasoning skills in dental education. Hence, this study examines the association between outcomes of clinical reasoning in relation with differences in instructional design and student factors. Progress test scores, including diagnostic and treatment planning scores, of fourth and fifth year dental students (2009-2011) at the University of Pretoria, South Africa served as the outcome measures in stepwise linear regression analyses. These scores were correlated with the instructional design (lecture-based teaching and learning (LBTL = 0) or case-based teaching and learning (CBTL = 1), students' grades in Oral Biology, indicators of socio-economic status (SES) and gender. CBTL showed an independent association with progress test scores. Oral Biology scores correlated with diagnostic component scores. Diagnostic component scores correlated with treatment planning scores in the fourth year of study but not in the fifth year of study. 'SES' correlated with progress test scores in year five only, while gender showed no correlation. The empirical evidence gathered in this study provides support for scaffolded inductive teaching and learning methods to develop clinical reasoning skills. Knowledge in Oral Biology and reading skills may be important attributes to develop to ensure that students are able to reason accurately in a clinical setting. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Characterization of Serum Cytokine Profile in Predominantly Colonic Inflammatory Bowel Disease to Delineate Ulcerative and Crohn’s Colitides

PubMed Central

Korolkova, Olga Y; Myers, Jeremy N; Pellom, Samuel T; Wang, Li; M’Koma, Amosy E

2015-01-01

BACKGROUND As accessible diagnostic approaches fail to differentiate between ulcerative colitis (UC) and Crohn’s colitis (CC) in one-third of patients with predominantly colonic inflammatory bowel disease (IBD), leading to inappropriate therapy, we aim to investigate the serum cytokine levels in these patients in search of molecular biometric markers delineating UC from CC. METHODS We measured 38 cytokines, chemokines, and growth factors using magnetic-bead-based multiplex immunoassay in 25 UC patients, 28 CC patients, and 30 controls. Our results are compared with those from a review of current literature regarding advances in serum cytokine profiles and associated challenges preventing their use for diagnostic/prognostic purposes. RESULTS Univariate analysis showed statistically significant increases of eotaxin, GRO, and TNF-α in UC patients compared to controls (Ctrl); interferon γ, interleukin (IL)-6, and IL-7 in CC group compared to Ctrl; and IL-8 in both UC and CC versus Ctrl. No cytokines were found to be different between UC and CC. A generalized linear model identified combinations of cytokines, allowing the identification of UC and CC patients, with area under the curve (AUC) = 0.936, as determined with receiver operating characteristic (ROC) analysis. CONCLUSIONS The current knowledge available about circulating cytokines in IBD is often contradictory. The development of an evidence-based tool using cytokines for diagnostic accuracy is still preliminary. PMID:26078592

Pathways to diagnosis for Black men and White men found to have prostate cancer: the PROCESS cohort study

PubMed Central

Metcalfe, C; Evans, S; Ibrahim, F; Patel, B; Anson, K; Chinegwundoh, F; Corbishley, C; Gillatt, D; Kirby, R; Muir, G; Nargund, V; Popert, R; Persad, R; Ben-Shlomo, Y

2008-01-01

Black men in England have three times the age-adjusted incidence of diagnosed prostate cancer as compared with their White counterparts. This population-based retrospective cohort study is the first UK-based investigation of whether access to diagnostic services underlies the association between race and prostate cancer. Prostate cancer was ascertained using multiple sources including hospital records. Race and factors that may influence prostate cancer diagnosis were assessed by questionnaire and hospital records review. We found that Black men were diagnosed an average of 5.1 years younger as compared with White men (P<0.001). Men of both races were comparable in their knowledge of prostate cancer, in the delays reported before presentation, and in their experience of co-morbidity and symptoms. Black men were more likely to be referred for diagnostic investigation by a hospital department (P=0.013), although general practitioners referred the large majority of men. Prostate-specific antigen levels were comparable at diagnosis, although Black men had higher levels when compared with same-age White men (P<0.001). In conclusion, we found no evidence of Black men having poorer access to diagnostic services. Differences in the run-up to diagnosis are modest and seem insufficient to explain the higher rate of prostate cancer diagnosis in Black men. PMID:18797456

Technology Development Resources | Resources | CDP

Cancer.gov

The Cancer Diagnosis Program strives to improve the diagnosis and assessment of cancer by effectively moving new scientific knowledge into clinical practice. This national program stimulates, coordinates and funds resources and research for the development of innovative in vitro diagnostics, novel diagnostic technologies and appropriate human specimens in order to better characterize cancers and allow improved medical decision making and evaluation of response to treatment.

Recommendations, Publications and Multimedia | Resources | CDP

Cancer.gov

The Cancer Diagnosis Program strives to improve the diagnosis and assessment of cancer by effectively moving new scientific knowledge into clinical practice. This national program stimulates, coordinates and funds resources and research for the development of innovative in vitro diagnostics, novel diagnostic technologies and appropriate human specimens in order to better characterize cancers and allow improved medical decision making and evaluation of response to treatment.

SPECS | Scientific Programs | CDP

Cancer.gov

The Cancer Diagnosis Program strives to improve the diagnosis and assessment of cancer by effectively moving new scientific knowledge into clinical practice. This national program stimulates, coordinates and funds resources and research for the development of innovative in vitro diagnostics, novel diagnostic technologies and appropriate human specimens in order to better characterize cancers and allow improved medical decision making and evaluation of response to treatment.

PACCT | Scientific Programs | CDP

Cancer.gov

The Cancer Diagnosis Program strives to improve the diagnosis and assessment of cancer by effectively moving new scientific knowledge into clinical practice. This national program stimulates, coordinates and funds resources and research for the development of innovative in vitro diagnostics, novel diagnostic technologies and appropriate human specimens in order to better characterize cancers and allow improved medical decision making and evaluation of response to treatment.

News and Events | Resources | CDP

Cancer.gov

The Cancer Diagnosis Program strives to improve the diagnosis and assessment of cancer by effectively moving new scientific knowledge into clinical practice. This national program stimulates, coordinates and funds resources and research for the development of innovative in vitro diagnostics, novel diagnostic technologies and appropriate human specimens in order to better characterize cancers and allow improved medical decision making and evaluation of response to treatment.

Human Specimen Resources | Resources | CDP

Cancer.gov

The Cancer Diagnosis Program strives to improve the diagnosis and assessment of cancer by effectively moving new scientific knowledge into clinical practice. This national program stimulates, coordinates and funds resources and research for the development of innovative in vitro diagnostics, novel diagnostic technologies and appropriate human specimens in order to better characterize cancers and allow improved medical decision making and evaluation of response to treatment.

Funding Opportunities | CDP

Cancer.gov

The Cancer Diagnosis Program strives to improve the diagnosis and assessment of cancer by effectively moving new scientific knowledge into clinical practice. This national program stimulates, coordinates and funds resources and research for the development of innovative in vitro diagnostics, novel diagnostic technologies and appropriate human specimens in order to better characterize cancers and allow improved medical decision making and evaluation of response to treatment.

Scientific Programs | CDP

Cancer.gov

The Cancer Diagnosis Program strives to improve the diagnosis and assessment of cancer by effectively moving new scientific knowledge into clinical practice. This national program stimulates, coordinates and funds resources and research for the development of innovative in vitro diagnostics, novel diagnostic technologies and appropriate human specimens in order to better characterize cancers and allow improved medical decision making and evaluation of response to treatment.

About CDP | CDP

Cancer.gov

The Cancer Diagnosis Program strives to improve the diagnosis and assessment of cancer by effectively moving new scientific knowledge into clinical practice. This national program stimulates, coordinates and funds resources and research for the development of innovative in vitro diagnostics, novel diagnostic technologies and appropriate human specimens in order to better characterize cancers and allow improved medical decision making and evaluation of response to treatment.

Factors Influencing Early Detection of Oral Cancer by Primary Health-Care Professionals.

PubMed

Hassona, Y; Scully, C; Shahin, A; Maayta, W; Sawair, F

2016-06-01

The purposes of this study are to determine early detection practices performed by primary healthcare professionals, to compare medical and dental sub-groups, and to identify factors that influence the ability of medical and dental practitioners to recognize precancerous changes and clinical signs of oral cancer. A 28-item survey instrument was used to interview a total of 330 Jordanian primary health-care professionals (165 dental and 165 medical). An oral cancer knowledge scale (0 to 31) was generated from correct responses on oral cancer general knowledge. An early detection practice scale (0 to 24) was generated from the reported usage and frequency of procedures in oral cancer examination. Also, a diagnostic ability scale (0 to 100) was generated from correct selections of suspicious oral lesions. Only 17.8 % of the participants reported that they routinely performed oral cancer screening in practices. Their oral cancer knowledge scores ranged from 3 to 31 with a mean of 15.6. The early detection practice scores ranged from 2 to 21 with a mean of 11.6. A significant positive correlation was found between knowledge scores and early detection practice scores (r = 0.22; p < 0.001). The diagnostic ability scores ranged from 11.5 to 96 with a mean of 43.6. The diagnostic ability score was significantly correlated with knowledge scores (r = 0.39; p < 0.001), but not with early detection practice scores (r = 0.01; p = 0.92). Few significant differences were found between medical and dental primary care professionals. Continuous education courses on early diagnosis of oral cancer and oral mucosal lesions are needed for primary health-care professionals.

The rare and undiagnosed diseases diagnostic service - application of massively parallel sequencing in a state-wide clinical service.

PubMed

Baynam, Gareth; Pachter, Nicholas; McKenzie, Fiona; Townshend, Sharon; Slee, Jennie; Kiraly-Borri, Cathy; Vasudevan, Anand; Hawkins, Anne; Broley, Stephanie; Schofield, Lyn; Verhoef, Hedwig; Walker, Caroline E; Molster, Caron; Blackwell, Jenefer M; Jamieson, Sarra; Tang, Dave; Lassmann, Timo; Mina, Kym; Beilby, John; Davis, Mark; Laing, Nigel; Murphy, Lesley; Weeramanthri, Tarun; Dawkins, Hugh; Goldblatt, Jack

2016-06-11

The Rare and Undiagnosed Diseases Diagnostic Service (RUDDS) refers to a genomic diagnostic platform operating within the Western Australian Government clinical services delivered through Genetic Services of Western Australia (GSWA). GSWA has provided a state-wide service for clinical genetic care for 28 years and it serves a population of 2.5 million people across a geographical area of 2.5milion Km(2). Within this context, GSWA has established a clinically integrated genomic diagnostic platform in partnership with other public health system managers and service providers, including but not limited to the Office of Population Health Genomics, Diagnostic Genomics (PathWest Laboratories) and with executive level support from the Department of Health. Herein we describe report presents the components of this service that are most relevant to the heterogeneity of paediatric clinical genetic care. Briefly the platform : i) offers multiple options including non-genetic testing; monogenic and genomic (targeted in silico filtered and whole exome) analysis; and matchmaking; ii) is delivered in a patient-centric manner that is resonant with the patient journey, it has multiple points for entry, exit and re-entry to allow people access to information they can use, when they want to receive it; iii) is synchronous with precision phenotyping methods; iv) captures new knowledge, including multiple expert review; v) is integrated with current translational genomic research activities and best practice; and vi) is designed for flexibility for interactive generation of, and integration with, clinical research for diagnostics, community engagement, policy and models of care. The RUDDS has been established as part of routine clinical genetic services and is thus sustainable, equitably managed and seeks to translate new knowledge into efficient diagnostics and improved health for the whole community.

Assessing the educational needs of Canadian gastroenterologists and gastroenterology nurses: challenges to optimal care in Crohn's Disease.

PubMed

Dupuis, Martin; Marshall, John K; Hayes, Sean M; Cytryn, Kayla; Murray, Suzanne

2009-12-01

A national needs assessment of Canadian gastroenterologists and gastroenterology nurses was undertaken to determine the perceived and unperceived educational and performance barriers to caring for patients with Crohn's disease (CD). A triangulated, mixed-method approach (qualitative and quantitative) was used to determine the nature and extent of knowledge gaps and barriers in the care of patients with CD. Qualitative interviews were conducted with nine gastroenterologists, four gastroenterology nurses and nine patients with CD. Based on this exploratory research, a survey was designed and launched nationally (37 gastroenterologists, 36 gastroenterology nurses). Findings indicated that Canadian gastroenterologists and gastroenterology nurses lacked clarity regarding their roles and responsibilities across the continuum of CD care, and face communication gaps within the health care team, undermining their effectiveness. Gastroenterologists identified challenges in optimal diagnosis due to unclear testing and diagnostic criteria. They recognized knowledge gaps when treating patient subgroups and in prescribing biological therapies. Furthermore, gastroenterologists self-identified gaps in skill, knowledge, and confidence in monitoring disease progression and effectively assessing response to therapy. When managing patients with CD, gastroenterologists expressed challenges with patient issues outside their domain of medical expertise, particularly with the skills needed to facilitate effective patient communication and education that would enhance adherence to recommended treatments. Educational initiatives should address diagnostic and treatment guidelines, as well as enhancement of clinical performance gaps in health care team processes and the patient-professional therapeutic relationship. To impact care and patient outcomes, these initiatives must be relevant to clinical practice settings and applicable to the practice context.

Assessing the educational needs of Canadian gastroenterologists and gastroenterology nurses: Challenges to optimal care in Crohn’s disease

PubMed Central

Dupuis, Martin; Marshall, John K; Hayes, Sean M; Cytryn, Kayla; Murray, Suzanne

2009-01-01

OBJECTIVE: A national needs assessment of Canadian gastroenterologists and gastroenterology nurses was undertaken to determine the perceived and unperceived educational and performance barriers to caring for patients with Crohn’s disease (CD). METHODS: A triangulated, mixed-method approach (qualitative and quantitative) was used to determine the nature and extent of knowledge gaps and barriers in the care of patients with CD. RESULTS: Qualitative interviews were conducted with nine gastroenterologists, four gastroenterology nurses and nine patients with CD. Based on this exploratory research, a survey was designed and launched nationally (37 gastroenterologists, 36 gastroenterology nurses). Findings indicated that Canadian gastroenterologists and gastroenterology nurses lacked clarity regarding their roles and responsibilities across the continuum of CD care, and face communication gaps within the health care team, undermining their effectiveness. Gastroenterologists identified challenges in optimal diagnosis due to unclear testing and diagnostic criteria. They recognized knowledge gaps when treating patient subgroups and in prescribing biological therapies. Furthermore, gastroenterologists self-identified gaps in skill, knowledge, and confidence in monitoring disease progression and effectively assessing response to therapy. When managing patients with CD, gastroenterologists expressed challenges with patient issues outside their domain of medical expertise, particularly with the skills needed to facilitate effective patient communication and education that would enhance adherence to recommended treatments. CONCLUSIONS: Educational initiatives should address diagnostic and treatment guidelines, as well as enhancement of clinical performance gaps in health care team processes and the patient-professional therapeutic relationship. To impact care and patient outcomes, these initiatives must be relevant to clinical practice settings and applicable to the practice context. PMID:20011732

Tuberculosis knowledge among injecting drug users visiting syringe exchange programme in Tallinn, Estonia.

PubMed

Rüütel, Kristi; Parker, R David; Sobolev, Igor; Loit, Helle-Mai

2012-12-01

The purpose of the current study was to describe tuberculosis (TB) knowledge, beliefs, and experience with TB services among injecting drug users. Participants for this anonymous, cross-sectional study were recruited from a community based syringe exchange programme in Tallinn, Estonia. A structured questionnaire was completed and included information on socio-demographics, health history, drug use, and knowledge about TB and HIV. The study included 407 people (79% male, mean age 27.9 years, mean injection drug use 9.4 years). 32.9% of participants reported HIV infection and 1.7% lifetime history of TB. 26.4% participants (n=106) reported symptoms suggestive of TB. 93% of participants recognized correctly that TB is air-borne infection and 91% that HIV is a risk factor for TB. Only 40% of the participants knew that TB diagnostics and treatment in Estonia are free of charge for everybody and 58% reported they knew where to get health care services in case they suspected that they had TB. TB transmission and treatment adherence knowledge was better among those in contact with either health care or harm reduction services, e.g the community based syringe exchange programme. Similar to HIV services, TB prevention and education should be integrated into harm reduction and drug treatment programmes to facilitate early diagnosis and treatment of TB among injecting drug users.

Teaching science vs. the apprentice model--do we really have the choice?

PubMed

Marckmann, G

2001-01-01

The debate about the appropriate methodology of medical education has been (and still is) dominated by the opposing poles of teaching science versus teaching practical skills. I will argue that this conflict between scientific education and practical training has its roots in the underlying, more systematic question about the conceptual foundation of medicine: how far or in what respects can medicine be considered to be a science? By analyzing the epistemological status of medicine I will show that the internal aim of medicine ("promoting health through the prevention and treatment of disease") differs from the internal aim of science ("the methodological and systematic acquisition of knowledge"). Therefore, medicine as a whole discipline should not be considered as a science. However, medicine can be conceptually and methodologically scientific in so much as it is based on scientific knowledge. There is evidence from cognitive science research that diagnostic reasoning not only relies on the application of scientific knowledge but also--especially in routine cases--on a process of pattern recognition, a reasoning strategy based on the memory of previously encountered patients. Hence, medical education must contain both: the imparting of scientific knowledge and the rich exposure to concrete cases during practical training. Hence, the question of teaching science vs. the apprentice model will not be "either-or" but rather "both--but in which proportion?"

Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction

PubMed Central

Kim, Dokyoon; Joung, Je-Gun; Sohn, Kyung-Ah; Shin, Hyunjung; Park, Yu Rang; Ritchie, Marylyn D; Kim, Ju Han

2015-01-01

Objective Cancer can involve gene dysregulation via multiple mechanisms, so no single level of genomic data fully elucidates tumor behavior due to the presence of numerous genomic variations within or between levels in a biological system. We have previously proposed a graph-based integration approach that combines multi-omics data including copy number alteration, methylation, miRNA, and gene expression data for predicting clinical outcome in cancer. However, genomic features likely interact with other genomic features in complex signaling or regulatory networks, since cancer is caused by alterations in pathways or complete processes. Methods Here we propose a new graph-based framework for integrating multi-omics data and genomic knowledge to improve power in predicting clinical outcomes and elucidate interplay between different levels. To highlight the validity of our proposed framework, we used an ovarian cancer dataset from The Cancer Genome Atlas for predicting stage, grade, and survival outcomes. Results Integrating multi-omics data with genomic knowledge to construct pre-defined features resulted in higher performance in clinical outcome prediction and higher stability. For the grade outcome, the model with gene expression data produced an area under the receiver operating characteristic curve (AUC) of 0.7866. However, models of the integration with pathway, Gene Ontology, chromosomal gene set, and motif gene set consistently outperformed the model with genomic data only, attaining AUCs of 0.7873, 0.8433, 0.8254, and 0.8179, respectively. Conclusions Integrating multi-omics data and genomic knowledge to improve understanding of molecular pathogenesis and underlying biology in cancer should improve diagnostic and prognostic indicators and the effectiveness of therapies. PMID:25002459

Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction.

PubMed

Kim, Dokyoon; Joung, Je-Gun; Sohn, Kyung-Ah; Shin, Hyunjung; Park, Yu Rang; Ritchie, Marylyn D; Kim, Ju Han

2015-01-01

Cancer can involve gene dysregulation via multiple mechanisms, so no single level of genomic data fully elucidates tumor behavior due to the presence of numerous genomic variations within or between levels in a biological system. We have previously proposed a graph-based integration approach that combines multi-omics data including copy number alteration, methylation, miRNA, and gene expression data for predicting clinical outcome in cancer. However, genomic features likely interact with other genomic features in complex signaling or regulatory networks, since cancer is caused by alterations in pathways or complete processes. Here we propose a new graph-based framework for integrating multi-omics data and genomic knowledge to improve power in predicting clinical outcomes and elucidate interplay between different levels. To highlight the validity of our proposed framework, we used an ovarian cancer dataset from The Cancer Genome Atlas for predicting stage, grade, and survival outcomes. Integrating multi-omics data with genomic knowledge to construct pre-defined features resulted in higher performance in clinical outcome prediction and higher stability. For the grade outcome, the model with gene expression data produced an area under the receiver operating characteristic curve (AUC) of 0.7866. However, models of the integration with pathway, Gene Ontology, chromosomal gene set, and motif gene set consistently outperformed the model with genomic data only, attaining AUCs of 0.7873, 0.8433, 0.8254, and 0.8179, respectively. Integrating multi-omics data and genomic knowledge to improve understanding of molecular pathogenesis and underlying biology in cancer should improve diagnostic and prognostic indicators and the effectiveness of therapies. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association.

Italian Teachers' Knowledge and Perception of Attention Deficit Hyperactivity Disorder (ADHD)

ERIC Educational Resources Information Center

Frigerio, Alessandra; Montali, Lorenzo; Marzocchi, Gian Marco

2014-01-01

Teachers' perceptions of attention deficit hyperactivity disorder (ADHD) can influence the diagnostic rates of the disorder and the management of children in schools. This study investigated the knowledge and perceptions of ADHD in a sample of 589 Italian primary school teachers using a self-report questionnaire that included the ADHD perceptions…

DSM-V from the perspective of the DSM-IV experience.

PubMed

Walsh, B Timothy

2007-11-01

This article provides a brief overview of the development of the diagnostic criteria for eating disorders in DSM-IV. The process by which DSM-IV was developed is reviewed, including perspectives on what constitutes diagnostic validity and clinical utility, and their importance in assessing proposed changes in diagnostic criteria. The question of whether alterations in diagnostic criteria would clearly improve clinical utility was a major consideration in the DSM-IV process. Because of concerns that changes in diagnostic criteria would be disruptive and might entail loss of established knowledge, the DSM-IV Task Force assumed a generally conservative stance vis-à-vis change. The process of developing DSM-V is just beginning, and it is far from clear what alterations in diagnostic criteria for eating disorders will occur. However, the evolution of DSM-IV may provide a useful perspective on the development of DSM-V. (c) 2007 by Wiley Periodicals, Inc.

Gendered uncertainty and variation in physicians' decisions for coronary heart disease: the double-edged sword of "atypical symptoms".

PubMed

Welch, Lisa C; Lutfey, Karen E; Gerstenberger, Eric; Grace, Matthew

2012-09-01

Nonmedical factors and diagnostic certainty contribute to variation in clinical decision making, but the process by which this occurs remains unclear. We examine how physicians' interpretations of patient sex-gender affect diagnostic certainty and, in turn, decision making for coronary heart disease. Data are from a factorial experiment of 256 physicians who viewed 1 of 16 video vignettes with different patient-actors presenting the same symptoms of coronary heart disease. Physician participants completed a structured interview and provided a narrative about their decision-making processes. Quantitative analysis showed that diagnostic uncertainty reduces the likelihood that physicians will order tests and medications appropriate for an urgent cardiac condition in particular. Qualitative analysis revealed that a subset of physicians applied knowledge that women have "atypical symptoms" as a generalization, which engendered uncertainty for some. Findings are discussed in relation to social-psychological processes that underlie clinical decision making and the social framing of medical knowledge.

Gendered Uncertainty and Variation in Physicians’ Decisions for Coronary Heart Disease: The Double-Edged Sword of “Atypical Symptoms”*

PubMed Central

Welch, Lisa C.; Lutfey, Karen E.; Gerstenberger, Eric; Grace, Matthew

2013-01-01

Nonmedical factors and diagnostic certainty contribute to variation in clinical decision making, but the process by which this occurs remains unclear. We examine how physicians’ interpretations of patient sex/gender affect diagnostic certainty and, in turn, decision making for coronary heart disease (CHD). Data are from a factorial experiment of 256 physicians who viewed one of 16 video vignettes with different patient-actors presenting the same CHD symptoms. Physician participants completed a structured interview and provided a narrative about their decision-making processes. Quantitative analysis showed that diagnostic uncertainty reduces the likelihood that physicians will order tests and medications appropriate for an urgent cardiac condition in particular. Qualitative analysis revealed that a subset of physicians applied knowledge that women have “atypical symptoms” as a generalization, which engendered uncertainty for some. Findings are discussed in relation to social-psychological processes that underlie clinical decision making and the social framing of medical knowledge. PMID:22933590

Synopsis of Guidelines for the Clinical Management of Cerebral Cavernous Malformations: Consensus Recommendations Based on Systematic Literature Review by the Angioma Alliance Scientific Advisory Board Clinical Experts Panel

PubMed Central

Al-Shahi Salman, Rustam; A. Awad, Issam; Dahlem, Kristen; Flemming, Kelly; Hart, Blaine; Kim, Helen; Jusue-Torres, Ignacio; Kondziolka, Douglas; Lee, Cornelia; Morrison, Leslie; Rigamonti, Daniele; Rebeiz, Tania; Tournier-Lasserve, Elisabeth; Waggoner, Darrel; Whitehead, Kevin

2017-01-01

Abstract BACKGROUND: Despite many publications about cerebral cavernous malformations (CCMs), controversy remains regarding diagnostic and management strategies. OBJECTIVE: To develop guidelines for CCM management. METHODS: The Angioma Alliance (www.angioma.org), the patient support group in the United States advocating on behalf of patients and research in CCM, convened a multidisciplinary writing group comprising expert CCM clinicians to help summarize the existing literature related to the clinical care of CCM, focusing on 5 topics: (1) epidemiology and natural history, (2) genetic testing and counseling, (3) diagnostic criteria and radiology standards, (4) neurosurgical considerations, and (5) neurological considerations. The group reviewed literature, rated evidence, developed recommendations, and established consensus, controversies, and knowledge gaps according to a prespecified protocol. RESULTS: Of 1270 publications published between January 1, 1983 and September 31, 2014, we selected 98 based on methodological criteria, and identified 38 additional recent or relevant publications. Topic authors used these publications to summarize current knowledge and arrive at 23 consensus management recommendations, which we rated by class (size of effect) and level (estimate of certainty) according to the American Heart Association/American Stroke Association criteria. No recommendation was level A (because of the absence of randomized controlled trials), 11 (48%) were level B, and 12 (52%) were level C. Recommendations were class I in 8 (35%), class II in 10 (43%), and class III in 5 (22%). CONCLUSION: Current evidence supports recommendations for the management of CCM, but their generally low levels and classes mandate further research to better inform clinical practice and update these recommendations. The complete recommendations document, including the criteria for selecting reference citations, a more detailed justification of the respective recommendations, and a summary of controversies and knowledge gaps, was similarly peer reviewed and is available on line www.angioma.org/CCMGuidelines. PMID:28387823

Object-based modeling, identification, and labeling of medical images for content-based retrieval by querying on intervals of attribute values

NASA Astrophysics Data System (ADS)

Thies, Christian; Ostwald, Tamara; Fischer, Benedikt; Lehmann, Thomas M.

2005-04-01

The classification and measuring of objects in medical images is important in radiological diagnostics and education, especially when using large databases as knowledge resources, for instance a picture archiving and communication system (PACS). The main challenge is the modeling of medical knowledge and the diagnostic context to label the sought objects. This task is referred to as closing the semantic gap between low-level pixel information and high level application knowledge. This work describes an approach which allows labeling of a-priori unknown objects in an intuitive way. Our approach consists of four main components. At first an image is completely decomposed into all visually relevant partitions on different scales. This provides a hierarchical organized set of regions. Afterwards, for each of the obtained regions a set of descriptive features is computed. In this data structure objects are represented by regions with characteristic attributes. The actual object identification is the formulation of a query. It consists of attributes on which intervals are defined describing those regions that correspond to the sought objects. Since the objects are a-priori unknown, they are described by a medical expert by means of an intuitive graphical user interface (GUI). This GUI is the fourth component. It enables complex object definitions by browsing the data structure and examinating the attributes to formulate the query. The query is executed and if the sought objects have not been identified its parameterization is refined. By using this heuristic approach, object models for hand radiographs have been developed to extract bones from a single hand in different anatomical contexts. This demonstrates the applicability of the labeling concept. By using a rule for metacarpal bones on a series of 105 images, this type of bone could be retrieved with a precision of 0.53 % and a recall of 0.6%.

A False Positive Dengue Fever Rapid Diagnostic Test Result in a Case of Acute Parvovirus B19 Infection.

PubMed

Izumida, Toshihide; Sakata, Hidenao; Nakamura, Masahiko; Hayashibara, Yumiko; Inasaki, Noriko; Inahata, Ryo; Hasegawa, Sumiyo; Takizawa, Takenori; Kaya, Hiroyasu

2016-01-01

An outbreak of dengue fever occurred in Japan in August 2014. We herein report the case of a 63-year-old man who presented with a persistent fever in September 2014. Acute parvovirus B19 infection led to a false positive finding of dengue fever on a rapid diagnostic test (Panbio Dengue Duo Cassette(TM)). To the best of our knowledge, there are no previous reports of a false positive result for dengue IgM with the dengue rapid diagnostic test. We believe that epidemiological information on the prevalence of parvovirus B19 is useful for guiding the interpretation of a positive result with the dengue rapid diagnostic test.

A development framework for distributed artificial intelligence

NASA Technical Reports Server (NTRS)

Adler, Richard M.; Cottman, Bruce H.

1989-01-01

The authors describe distributed artificial intelligence (DAI) applications in which multiple organizations of agents solve multiple domain problems. They then describe work in progress on a DAI system development environment, called SOCIAL, which consists of three primary language-based components. The Knowledge Object Language defines models of knowledge representation and reasoning. The metaCourier language supplies the underlying functionality for interprocess communication and control access across heterogeneous computing environments. The metaAgents language defines models for agent organization coordination, control, and resource management. Application agents and agent organizations will be constructed by combining metaAgents and metaCourier building blocks with task-specific functionality such as diagnostic or planning reasoning. This architecture hides implementation details of communications, control, and integration in distributed processing environments, enabling application developers to concentrate on the design and functionality of the intelligent agents and agent networks themselves.

Plasma density characterization at SPARC_LAB through Stark broadening of Hydrogen spectral lines

NASA Astrophysics Data System (ADS)

Filippi, F.; Anania, M. P.; Bellaveglia, M.; Biagioni, A.; Chiadroni, E.; Cianchi, A.; Di Giovenale, D.; Di Pirro, G.; Ferrario, M.; Mostacci, A.; Palumbo, L.; Pompili, R.; Shpakov, V.; Vaccarezza, C.; Villa, F.; Zigler, A.

2016-09-01

Plasma-based acceleration techniques are of great interest for future, compact accelerators due to their high accelerating gradient. Both particle-driven and laser-driven Plasma Wakefield Acceleration experiments are foreseen at the SPARC_LAB Test Facility (INFN National Laboratories of Frascati, Italy), with the aim to accelerate high-brightness electron beams. In order to optimize the efficiency of the acceleration in the plasma and preserve the quality of the accelerated beam, the knowledge of the plasma electron density is mandatory. The Stark broadening of the Hydrogen spectral lines is one of the candidates used to characterize plasma density. The implementation of this diagnostic for plasma-based experiments at SPARC_LAB is presented.

Planetary Nebula Candidates Uncovered with the HASH Research Platform

NASA Astrophysics Data System (ADS)

Fragkou, Vasiliki; Bojičić, Ivan; Frew, David; Parker, Quentin

2017-10-01

A detailed examination of new high quality radio catalogues (e.g. Cornish) in combination with available mid-infrared (MIR) satellite imagery (e.g. Glimpse) has allowed us to find 70 new planetary nebula (PN) candidates based on existing knowledge of their typical colors and fluxes. To further examine the nature of these sources, multiple diagnostic tools have been applied to these candidates based on published data and on available imagery in the HASH (Hong Kong/ AAO/ Strasbourg Hα planetary nebula) research platform. Some candidates have previously-missed optical counterparts allowing for spectroscopic follow-up. Indeed, the single object spectroscopically observed so far has turned out to be a bona fide PN.

Do knowledge, knowledge sources and reasoning skills affect the accuracy of nursing diagnoses? a randomised study.

PubMed

Paans, Wolter; Sermeus, Walter; Nieweg, Roos Mb; Krijnen, Wim P; van der Schans, Cees P

2012-08-01

This paper reports a study about the effect of knowledge sources, such as handbooks, an assessment format and a predefined record structure for diagnostic documentation, as well as the influence of knowledge, disposition toward critical thinking and reasoning skills, on the accuracy of nursing diagnoses.Knowledge sources can support nurses in deriving diagnoses. A nurse's disposition toward critical thinking and reasoning skills is also thought to influence the accuracy of his or her nursing diagnoses. A randomised factorial design was used in 2008-2009 to determine the effect of knowledge sources. We used the following instruments to assess the influence of ready knowledge, disposition, and reasoning skills on the accuracy of diagnoses: (1) a knowledge inventory, (2) the California Critical Thinking Disposition Inventory, and (3) the Health Science Reasoning Test. Nurses (n = 249) were randomly assigned to one of four factorial groups, and were instructed to derive diagnoses based on an assessment interview with a simulated patient/actor. The use of a predefined record structure resulted in a significantly higher accuracy of nursing diagnoses. A regression analysis reveals that almost half of the variance in the accuracy of diagnoses is explained by the use of a predefined record structure, a nurse's age and the reasoning skills of `deduction' and `analysis'. Improving nurses' dispositions toward critical thinking and reasoning skills, and the use of a predefined record structure, improves accuracy of nursing diagnoses.

Medicine is not science: guessing the future, predicting the past.

PubMed

Miller, Clifford

2014-12-01

Irregularity limits human ability to know, understand and predict. A better understanding of irregularity may improve the reliability of knowledge. Irregularity and its consequences for knowledge are considered. Reliable predictive empirical knowledge of the physical world has always been obtained by observation of regularities, without needing science or theory. Prediction from observational knowledge can remain reliable despite some theories based on it proving false. A naïve theory of irregularity is outlined. Reducing irregularity and/or increasing regularity can increase the reliability of knowledge. Beyond long experience and specialization, improvements include implementing supporting knowledge systems of libraries of appropriately classified prior cases and clinical histories and education about expertise, intuition and professional judgement. A consequence of irregularity and complexity is that classical reductionist science cannot provide reliable predictions of the behaviour of complex systems found in nature, including of the human body. Expertise, expert judgement and their exercise appear overarching. Diagnosis involves predicting the past will recur in the current patient applying expertise and intuition from knowledge and experience of previous cases and probabilistic medical theory. Treatment decisions are an educated guess about the future (prognosis). Benefits of the improvements suggested here are likely in fields where paucity of feedback for practitioners limits development of reliable expert diagnostic intuition. Further analysis, definition and classification of irregularity is appropriate. Observing and recording irregularities are initial steps in developing irregularity theory to improve the reliability and extent of knowledge, albeit some forms of irregularity present inherent difficulties. © 2014 John Wiley & Sons, Ltd.

Do knowledge, knowledge sources and reasoning skills affect the accuracy of nursing diagnoses? a randomised study

PubMed Central

2012-01-01

Background This paper reports a study about the effect of knowledge sources, such as handbooks, an assessment format and a predefined record structure for diagnostic documentation, as well as the influence of knowledge, disposition toward critical thinking and reasoning skills, on the accuracy of nursing diagnoses. Knowledge sources can support nurses in deriving diagnoses. A nurse’s disposition toward critical thinking and reasoning skills is also thought to influence the accuracy of his or her nursing diagnoses. Method A randomised factorial design was used in 2008–2009 to determine the effect of knowledge sources. We used the following instruments to assess the influence of ready knowledge, disposition, and reasoning skills on the accuracy of diagnoses: (1) a knowledge inventory, (2) the California Critical Thinking Disposition Inventory, and (3) the Health Science Reasoning Test. Nurses (n = 249) were randomly assigned to one of four factorial groups, and were instructed to derive diagnoses based on an assessment interview with a simulated patient/actor. Results The use of a predefined record structure resulted in a significantly higher accuracy of nursing diagnoses. A regression analysis reveals that almost half of the variance in the accuracy of diagnoses is explained by the use of a predefined record structure, a nurse’s age and the reasoning skills of `deduction’ and `analysis’. Conclusions Improving nurses’ dispositions toward critical thinking and reasoning skills, and the use of a predefined record structure, improves accuracy of nursing diagnoses. PMID:22852577

Diagnostic accuracy of PCR for detecting ALK gene rearrangement in NSCLC patients: A systematic review and meta-analysis

PubMed Central

Zhang, Xia; Zhou, Jian-Guo; Wu, Hua-Lian; Ma, Hu; Jiang, Zhi-Xia

2017-01-01

Background Anaplastic lymphoma kinase (ALK) gene fusion has been reported in 3∼5% non-small cell lung carcinoma (NSCLC) patients, and polymerase chain reaction (PCR) is commonly used to detecting the gene status, but the diagnostic capacity of it is still controversial. A systematic review and meta-analysis was conducted to clarify the diagnostic accuracy of PCR for detecting ALK gene rearrangement in NSCLC patients. Results 18 articles were enrolled, which included 21 studies, involving 2800 samples from NSCLC patients. The overall pooled parameters were calculated: sensitivity was 92.4% [95% confidence interval (CI): 82.2%–97.0%], specificity was 97.8% [95% CI: 95.1%–99.0%], PLR was 41.51 [95% CI: 18.10–95.22], NLR was 0.08 [95% CI: 0.03–0.19], DOR was 535.72 [95% CI: 128.48–2233.79], AUROC was 0.99 [95% CI: 0.98–1.00]. Materials and Methods Relevant articles were searched from PubMed, EMBASE, Web of Science, Cochrane library, American Society of Clinical Oncology (ASCO), European Society for Medical Oncology (ESMO), China National Knowledge Infrastructure (CNKI), China Wan Fang databases and Chinese biomedical literature database (CBM). Diagnostic capacity of PCR test was assessed by the pooled sensitivity and specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), area under the summary receiver operating characteristic (AUROC). Conclusions Based on the results from this review, PCR has good diagnostic performance for detecting the ALK gene fusion in NSCLC patients. Moreover, due to the poor methodology quality of the enrolled trials, more well-designed multi-center trials should be performed. PMID:29088875

Does the delivery of diagnostic news affect the likelihood of whether or not patients ask questions about the results? A conversation analytical study.

PubMed

Murtagh, Ged M; Thomas, Anne L; Furber, Lynn

2018-05-03

Asymmetries in knowledge and competence in the medical encounter often mean that doctor-patient communication can be compromised. This study explores this issue and examines whether the likelihood of patient question asking is increased following the delivery of diagnostic test results. It also examines whether that likelihood is related to the way in which the test results are delivered. To examine when and how patients initiate questions following diagnostic news announcements. We audio-recorded oncology consultations (n = 47) consisting of both first consultations and follow-up consultations with patients with different types of cancer, at a leading UK teaching hospital. From the primary sample, we identified 30 consultations based on a basic count of the frequency of patient questions and their positioning in relation to diagnostic announcements. This subset of 30 consultations consisted of a mix of first and follow-up consultations. Our data demonstrate how the design and delivery of diagnostic news announcements can either discourage or provide the opportunity for a patient-initiated question in the next turn of talk. We identified two types of announcement. Q+ generally provided for a patient-initiated question as a relevant next turn following the news announcement, whereas Q- did not. Q+ was sometimes followed up with the explanation of test results, which appeared to encourage further patient questions. The design and delivery of diagnostic news announcements can make a patient-initiated question more or less appropriate, in the next turn of talk. In addition, showing and explaining test results can encourage further opportunities for patients' questions. © 2018 The Authors. Health Expectations published by John Wiley & Sons Ltd.

Laser-induced breakdown spectroscopy (LIBS), part I: review of basic diagnostics and plasma-particle interactions: still-challenging issues within the analytical plasma community.

PubMed

Hahn, David W; Omenetto, Nicoló

2010-12-01

Laser-induced breakdown spectroscopy (LIBS) has become a very popular analytical method in the last decade in view of some of its unique features such as applicability to any type of sample, practically no sample preparation, remote sensing capability, and speed of analysis. The technique has a remarkably wide applicability in many fields, and the number of applications is still growing. From an analytical point of view, the quantitative aspects of LIBS may be considered its Achilles' heel, first due to the complex nature of the laser-sample interaction processes, which depend upon both the laser characteristics and the sample material properties, and second due to the plasma-particle interaction processes, which are space and time dependent. Together, these may cause undesirable matrix effects. Ways of alleviating these problems rely upon the description of the plasma excitation-ionization processes through the use of classical equilibrium relations and therefore on the assumption that the laser-induced plasma is in local thermodynamic equilibrium (LTE). Even in this case, the transient nature of the plasma and its spatial inhomogeneity need to be considered and overcome in order to justify the theoretical assumptions made. This first article focuses on the basic diagnostics aspects and presents a review of the past and recent LIBS literature pertinent to this topic. Previous research on non-laser-based plasma literature, and the resulting knowledge, is also emphasized. The aim is, on one hand, to make the readers aware of such knowledge and on the other hand to trigger the interest of the LIBS community, as well as the larger analytical plasma community, in attempting some diagnostic approaches that have not yet been fully exploited in LIBS.

EFIS lecture. Immune response to tuberculosis: How to control the most successful pathogen on earth.

PubMed

Kaufmann, Stefan H E

2016-07-01

Tuberculosis (TB) remains a major health threat and general agreement exists that better control measures are needed. These include better diagnostics, drugs and vaccines. In particular, vaccines will be critical for better TB control. Based on knowledge about protective immunity against TB, a vaccine was created, VPM1002, which shows high protective efficacy and safety in experimental animal models. The vaccine has proven safe and immunogenic in human adults and neonates and is currently assessed in clinical trials in the context of HIV exposure. As a next step, a phase III efficacy trial in adults and a phase IIb efficacy trial in neonates are being planned. Biosignatures that differentially diagnose TB disease versus latent infection with high sensitivity and specificity have been designed. Most recently, a prognostic biosignature which predicts progression from latent infection to active TB has been identified. Biosignatures are not only of great value for improved diagnosis and prognosis of TB, they can also provide guidelines for better understanding of molecular mechanisms underlying disease. Accordingly, distinct biomarkers of diagnostic and prognostic value but of unknown biological function are being characterized functionally. In this way, deeper insights have been obtained on the role of type I interferon and of neutrophils in TB in experimental animal models of TB. In conclusion, clinical and basic research further supported by computational biology can complement each other in the pursuit of knowledge-based development of improved intervention measures for TB control. Copyright © 2016 European Federation of Immunological Societies. Published by Elsevier B.V. All rights reserved.

Types of diagnostic errors in neurological emergencies in the emergency department.

PubMed

Dubosh, Nicole M; Edlow, Jonathan A; Lefton, Micah; Pope, Jennifer V

2015-02-01

Neurological emergencies often pose diagnostic challenges for emergency physicians because these patients often present with atypical symptoms and standard imaging tests are imperfect. Misdiagnosis occurs due to a variety of errors. These can be classified as knowledge gaps, cognitive errors, and systems-based errors. The goal of this study was to describe these errors through review of quality assurance (QA) records. This was a retrospective pilot study of patients with neurological emergency diagnoses that were missed or delayed at one urban, tertiary academic emergency department. Cases meeting inclusion criteria were identified through review of QA records. Three emergency physicians independently reviewed each case and determined the type of error that led to the misdiagnosis. Proportions, confidence intervals, and a reliability coefficient were calculated. During the study period, 1168 cases were reviewed. Forty-two cases were found to include a neurological misdiagnosis and twenty-nine were determined to be the result of an error. The distribution of error types was as follows: knowledge gap 45.2% (95% CI 29.2, 62.2), cognitive error 29.0% (95% CI 15.9, 46.8), and systems-based error 25.8% (95% CI 13.5, 43.5). Cerebellar strokes were the most common type of stroke misdiagnosed, accounting for 27.3% of missed strokes. All three error types contributed to the misdiagnosis of neurological emergencies. Misdiagnosis of cerebellar lesions and erroneous radiology resident interpretations of neuroimaging were the most common mistakes. Understanding the types of errors may enable emergency physicians to develop possible solutions and avoid them in the future.

Developing Pre-Service Teacher Capacity to Make Appropriate Choices of Tasks and Resources through Diagnostic Assessment of Children's Work

ERIC Educational Resources Information Center

Hurst, Chris

2014-01-01

This paper reports on one phase of a long-term project investigating mathematical content knowledge of pre-service teachers. A cohort of second year PSTs conducted a diagnostic assessment and a series of associated tutoring sessions with a primary aged child. The focus here is on the PSTs' ability to make appropriate task choices following the…

Ethical, Legal, and Social Implication of Cancer Research | Resources | CDP

Cancer.gov

The Cancer Diagnosis Program strives to improve the diagnosis and assessment of cancer by effectively moving new scientific knowledge into clinical practice. This national program stimulates, coordinates and funds resources and research for the development of innovative in vitro diagnostics, novel diagnostic technologies and appropriate human specimens in order to better characterize cancers and allow improved medical decision making and evaluation of response to treatment.