Text mining and its potential applications in systems biology.

PubMed

Ananiadou, Sophia; Kell, Douglas B; Tsujii, Jun-ichi

2006-12-01

With biomedical literature increasing at a rate of several thousand papers per week, it is impossible to keep abreast of all developments; therefore, automated means to manage the information overload are required. Text mining techniques, which involve the processes of information retrieval, information extraction and data mining, provide a means of solving this. By adding meaning to text, these techniques produce a more structured analysis of textual knowledge than simple word searches, and can provide powerful tools for the production and analysis of systems biology models.

Experiences with Text Mining Large Collections of Unstructured Systems Development Artifacts at JPL

NASA Technical Reports Server (NTRS)

Port, Dan; Nikora, Allen; Hihn, Jairus; Huang, LiGuo

2011-01-01

Often repositories of systems engineering artifacts at NASA's Jet Propulsion Laboratory (JPL) are so large and poorly structured that they have outgrown our capability to effectively manually process their contents to extract useful information. Sophisticated text mining methods and tools seem a quick, low-effort approach to automating our limited manual efforts. Our experiences of exploring such methods mainly in three areas including historical risk analysis, defect identification based on requirements analysis, and over-time analysis of system anomalies at JPL, have shown that obtaining useful results requires substantial unanticipated efforts - from preprocessing the data to transforming the output for practical applications. We have not observed any quick 'wins' or realized benefit from short-term effort avoidance through automation in this area. Surprisingly we have realized a number of unexpected long-term benefits from the process of applying text mining to our repositories. This paper elaborates some of these benefits and our important lessons learned from the process of preparing and applying text mining to large unstructured system artifacts at JPL aiming to benefit future TM applications in similar problem domains and also in hope for being extended to broader areas of applications.

Ten years of science news: A longitudinal analysis of scientific culture in the Spanish digital press.

PubMed

Groves, Tamar; Figuerola, Carlos G; Quintanilla, Miguel Á

2016-08-01

This article presents our study of science coverage in the digital Spanish press over the last decade. We employed automated information retrieval procedures to create a corpus of 50,763 text units dealing with science and technology, and used automated text-analysis procedures in order to provide a general picture of the structure, characteristics and evolution of science news in Spain. We found between 6% and 7% of science coverage, a clear high proportion of biomedicine and predominance of science over technology, although we also detected an increase in technological content during the second half of the decade. Analysing the extrinsic and intrinsic features of science culture, we found a predominance of intrinsic features that still need further analysis. Our attempt to use specialised software to examine big data was effective, and allowed us to reach these preliminary conclusions. © The Author(s) 2015.

Applications of Automation Methods for Nonlinear Fracture Test Analysis

NASA Technical Reports Server (NTRS)

Allen, Phillip A.; Wells, Douglas N.

2013-01-01

As fracture mechanics material testing evolves, the governing test standards continue to be refined to better reflect the latest understanding of the physics of the fracture processes involved. The traditional format of ASTM fracture testing standards, utilizing equations expressed directly in the text of the standard to assess the experimental result, is self-limiting in the complexity that can be reasonably captured. The use of automated analysis techniques to draw upon a rich, detailed solution database for assessing fracture mechanics tests provides a foundation for a new approach to testing standards that enables routine users to obtain highly reliable assessments of tests involving complex, non-linear fracture behavior. Herein, the case for automating the analysis of tests of surface cracks in tension in the elastic-plastic regime is utilized as an example of how such a database can be generated and implemented for use in the ASTM standards framework. The presented approach forms a bridge between the equation-based fracture testing standards of today and the next generation of standards solving complex problems through analysis automation.

Automated Analysis of Text in Graduate School Recommendations. Research Report. ETS RR-15-23

ERIC Educational Resources Information Center

Heilman, Michael; Breyer, F. Jay; Williams, Frank; Klieger, David; Flor, Michael

2015-01-01

Graduate school recommendations are an important part of admissions in higher education, and natural language processing may be able to provide objective and consistent analyses of recommendation texts to complement readings by faculty and admissions staff. However, these sorts of high-stakes, personal recommendations are different from the…

Automated Text Analysis Based on Skip-Gram Model for Food Evaluation in Predicting Consumer Acceptance

PubMed Central

Kim, Augustine Yongwhi; Choi, Hoduk

2018-01-01

The purpose of this paper is to evaluate food taste, smell, and characteristics from consumers' online reviews. Several studies in food sensory evaluation have been presented for consumer acceptance. However, these studies need taste descriptive word lexicon, and they are not suitable for analyzing large number of evaluators to predict consumer acceptance. In this paper, an automated text analysis method for food evaluation is presented to analyze and compare recently introduced two jjampong ramen types (mixed seafood noodles). To avoid building a sensory word lexicon, consumers' reviews are collected from SNS. Then, by training word embedding model with acquired reviews, words in the large amount of review text are converted into vectors. Based on these words represented as vectors, inference is performed to evaluate taste and smell of two jjampong ramen types. Finally, the reliability and merits of the proposed food evaluation method are confirmed by a comparison with the results from an actual consumer preference taste evaluation. PMID:29606960

Automated Text Analysis Based on Skip-Gram Model for Food Evaluation in Predicting Consumer Acceptance.

PubMed

Kim, Augustine Yongwhi; Ha, Jin Gwan; Choi, Hoduk; Moon, Hyeonjoon

2018-01-01

The purpose of this paper is to evaluate food taste, smell, and characteristics from consumers' online reviews. Several studies in food sensory evaluation have been presented for consumer acceptance. However, these studies need taste descriptive word lexicon, and they are not suitable for analyzing large number of evaluators to predict consumer acceptance. In this paper, an automated text analysis method for food evaluation is presented to analyze and compare recently introduced two jjampong ramen types (mixed seafood noodles). To avoid building a sensory word lexicon, consumers' reviews are collected from SNS. Then, by training word embedding model with acquired reviews, words in the large amount of review text are converted into vectors. Based on these words represented as vectors, inference is performed to evaluate taste and smell of two jjampong ramen types. Finally, the reliability and merits of the proposed food evaluation method are confirmed by a comparison with the results from an actual consumer preference taste evaluation.

Detecting Emotional Expression in Face-to-Face and Online Breast Cancer Support Groups

ERIC Educational Resources Information Center

Liess, Anna; Simon, Wendy; Yutsis, Maya; Owen, Jason E.; Piemme, Karen Altree; Golant, Mitch; Giese-Davis, Janine

2008-01-01

Accurately detecting emotional expression in women with primary breast cancer participating in support groups may be important for therapists and researchers. In 2 small studies (N = 20 and N = 16), the authors examined whether video coding, human text coding, and automated text analysis provided consistent estimates of the level of emotional…

Imitating manual curation of text-mined facts in biomedicine.

PubMed

Rodriguez-Esteban, Raul; Iossifov, Ivan; Rzhetsky, Andrey

2006-09-08

Text-mining algorithms make mistakes in extracting facts from natural-language texts. In biomedical applications, which rely on use of text-mined data, it is critical to assess the quality (the probability that the message is correctly extracted) of individual facts--to resolve data conflicts and inconsistencies. Using a large set of almost 100,000 manually produced evaluations (most facts were independently reviewed more than once, producing independent evaluations), we implemented and tested a collection of algorithms that mimic human evaluation of facts provided by an automated information-extraction system. The performance of our best automated classifiers closely approached that of our human evaluators (ROC score close to 0.95). Our hypothesis is that, were we to use a larger number of human experts to evaluate any given sentence, we could implement an artificial-intelligence curator that would perform the classification job at least as accurately as an average individual human evaluator. We illustrated our analysis by visualizing the predicted accuracy of the text-mined relations involving the term cocaine.

Morphosyntactic Neural Analysis for Generalized Lexical Normalization

ERIC Educational Resources Information Center

Leeman-Munk, Samuel Paul

2016-01-01

The phenomenal growth of social media, web forums, and online reviews has spurred a growing interest in automated analysis of user-generated text. At the same time, a proliferation of voice recordings and efforts to archive culture heritage documents are fueling demand for effective automatic speech recognition (ASR) and optical character…

Abstracts of SIG Sessions.

ERIC Educational Resources Information Center

Proceedings of the ASIS Annual Meeting, 1993

1993-01-01

Presents abstracts of 34 special interest group (SIG) sessions. Highlights include humanities scholars and electronic texts; information retrieval and indexing systems design; automated indexing; domain analysis; query expansion in document retrieval systems; thesauri; business intelligence; Americans with Disabilities Act; management;…

Validating Automated Measures of Text Complexity

ERIC Educational Resources Information Center

Sheehan, Kathleen M.

2017-01-01

Automated text complexity measurement tools (also called readability metrics) have been proposed as a way to help teachers, textbook publishers, and assessment developers select texts that are closely aligned with the new, more demanding text complexity expectations specified in the Common Core State Standards. This article examines a critical…

System for Computer Automated Typesetting (SCAT) of Computer Authored Texts.

ERIC Educational Resources Information Center

Keeler, F. Laurence

This description of the System for Automated Typesetting (SCAT), an automated system for typesetting text and inserting special graphic symbols in programmed instructional materials created by the computer aided authoring system AUTHOR, provides an outline of the design architecture of the system and an overview including the component…

Automatic Text Analysis Based on Transition Phenomena of Word Occurrences

ERIC Educational Resources Information Center

Pao, Miranda Lee

1978-01-01

Describes a method of selecting index terms directly from a word frequency list, an idea originally suggested by Goffman. Results of the analysis of word frequencies of two articles seem to indicate that the automated selection of index terms from a frequency list holds some promise for automatic indexing. (Author/MBR)

Left ventricular pressure and volume data acquisition and analysis using LabVIEW.

PubMed

Cassidy, S C; Teitel, D F

1997-03-01

To automate analysis of left ventricular pressure-volume data, we used LabVIEW to create applications that digitize and display data recorded from conductance and manometric catheters. Applications separate data into cardiac cycles, calculate parallel conductance, and calculate indices of left ventricular function, including end-systolic elastance, preload-recruitable stroke work, stroke volume, ejection fraction, stroke work, maximum and minimum derivative of ventricular pressure, heart rate, indices of relaxation, peak filling rate, and ventricular chamber stiffness. Pressure-volume loops can be graphically displayed. These analyses are exported to a text-file. These applications have simplified and automated the process of evaluating ventricular function.

Launch Control System Software Development System Automation Testing

NASA Technical Reports Server (NTRS)

Hwang, Andrew

2017-01-01

The Spaceport Command and Control System (SCCS) is the National Aeronautics and Space Administration's (NASA) launch control system for the Orion capsule and Space Launch System, the next generation manned rocket currently in development. This system requires high quality testing that will measure and test the capabilities of the system. For the past two years, the Exploration and Operations Division at Kennedy Space Center (KSC) has assigned a group including interns and full-time engineers to develop automated tests to save the project time and money. The team worked on automating the testing process for the SCCS GUI that would use streamed simulated data from the testing servers to produce data, plots, statuses, etc. to the GUI. The software used to develop automated tests included an automated testing framework and an automation library. The automated testing framework has a tabular-style syntax, which means the functionality of a line of code must have the appropriate number of tabs for the line to function as intended. The header section contains either paths to custom resources or the names of libraries being used. The automation library contains functionality to automate anything that appears on a desired screen with the use of image recognition software to detect and control GUI components. The data section contains any data values strictly created for the current testing file. The body section holds the tests that are being run. The function section can include any number of functions that may be used by the current testing file or any other file that resources it. The resources and body section are required for all test files; the data and function sections can be left empty if the data values and functions being used are from a resourced library or another file. To help equip the automation team with better tools, the Project Lead of the Automated Testing Team, Jason Kapusta, assigned the task to install and train an optical character recognition (OCR) tool to Brandon Echols, a fellow intern, and I. The purpose of the OCR tool is to analyze an image and find the coordinates of any group of text. Some issues that arose while installing the OCR tool included the absence of certain libraries needed to train the tool and an outdated software version. We eventually resolved the issues and successfully installed the OCR tool. Training the tool required many images and different fonts and sizes, but in the end the tool learned to accurately decipher the text in the images and their coordinates. The OCR tool produced a file that contained significant metadata for each section of text, but only the text and coordinates of the text was required for our purpose. The team made a script to parse the information we wanted from the OCR file to a different file that would be used by automation functions within the automated framework. Since a majority of development and testing for the automated test cases for the GUI in question has been done using live simulated data on the workstations at the Launch Control Center (LCC), a large amount of progress has been made. As of this writing, about 60% of all of automated testing has been implemented. Additionally, the OCR tool will help make our automated tests more robust due to the tool's text recognition being highly scalable to different text fonts and text sizes. Soon we will have the whole test system automated, allowing for more full-time engineers working on development projects.

The ACODEA Framework: Developing Segmentation and Classification Schemes for Fully Automatic Analysis of Online Discussions

ERIC Educational Resources Information Center

Mu, Jin; Stegmann, Karsten; Mayfield, Elijah; Rose, Carolyn; Fischer, Frank

2012-01-01

Research related to online discussions frequently faces the problem of analyzing huge corpora. Natural Language Processing (NLP) technologies may allow automating this analysis. However, the state-of-the-art in machine learning and text mining approaches yields models that do not transfer well between corpora related to different topics. Also,…

Toward high-throughput phenotyping: unbiased automated feature extraction and selection from knowledge sources.

PubMed

Yu, Sheng; Liao, Katherine P; Shaw, Stanley Y; Gainer, Vivian S; Churchill, Susanne E; Szolovits, Peter; Murphy, Shawn N; Kohane, Isaac S; Cai, Tianxi

2015-09-01

Analysis of narrative (text) data from electronic health records (EHRs) can improve population-scale phenotyping for clinical and genetic research. Currently, selection of text features for phenotyping algorithms is slow and laborious, requiring extensive and iterative involvement by domain experts. This paper introduces a method to develop phenotyping algorithms in an unbiased manner by automatically extracting and selecting informative features, which can be comparable to expert-curated ones in classification accuracy. Comprehensive medical concepts were collected from publicly available knowledge sources in an automated, unbiased fashion. Natural language processing (NLP) revealed the occurrence patterns of these concepts in EHR narrative notes, which enabled selection of informative features for phenotype classification. When combined with additional codified features, a penalized logistic regression model was trained to classify the target phenotype. The authors applied our method to develop algorithms to identify patients with rheumatoid arthritis and coronary artery disease cases among those with rheumatoid arthritis from a large multi-institutional EHR. The area under the receiver operating characteristic curves (AUC) for classifying RA and CAD using models trained with automated features were 0.951 and 0.929, respectively, compared to the AUCs of 0.938 and 0.929 by models trained with expert-curated features. Models trained with NLP text features selected through an unbiased, automated procedure achieved comparable or slightly higher accuracy than those trained with expert-curated features. The majority of the selected model features were interpretable. The proposed automated feature extraction method, generating highly accurate phenotyping algorithms with improved efficiency, is a significant step toward high-throughput phenotyping. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

ALE: automated label extraction from GEO metadata.

PubMed

Giles, Cory B; Brown, Chase A; Ripperger, Michael; Dennis, Zane; Roopnarinesingh, Xiavan; Porter, Hunter; Perz, Aleksandra; Wren, Jonathan D

2017-12-28

NCBI's Gene Expression Omnibus (GEO) is a rich community resource containing millions of gene expression experiments from human, mouse, rat, and other model organisms. However, information about each experiment (metadata) is in the format of an open-ended, non-standardized textual description provided by the depositor. Thus, classification of experiments for meta-analysis by factors such as gender, age of the sample donor, and tissue of origin is not feasible without assigning labels to the experiments. Automated approaches are preferable for this, primarily because of the size and volume of the data to be processed, but also because it ensures standardization and consistency. While some of these labels can be extracted directly from the textual metadata, many of the data available do not contain explicit text informing the researcher about the age and gender of the subjects with the study. To bridge this gap, machine-learning methods can be trained to use the gene expression patterns associated with the text-derived labels to refine label-prediction confidence. Our analysis shows only 26% of metadata text contains information about gender and 21% about age. In order to ameliorate the lack of available labels for these data sets, we first extract labels from the textual metadata for each GEO RNA dataset and evaluate the performance against a gold standard of manually curated labels. We then use machine-learning methods to predict labels, based upon gene expression of the samples and compare this to the text-based method. Here we present an automated method to extract labels for age, gender, and tissue from textual metadata and GEO data using both a heuristic approach as well as machine learning. We show the two methods together improve accuracy of label assignment to GEO samples.

Comparison of warfarin therapy clinical outcomes following implementation of an automated mobile phone-based critical laboratory value text alert system.

PubMed

Lin, Shu-Wen; Kang, Wen-Yi; Lin, Dong-Tsamn; Lee, James; Wu, Fe-Lin; Chen, Chuen-Liang; Tseng, Yufeng J

2014-01-01

Computerized alert and reminder systems have been widely accepted and applied to various patient care settings, with increasing numbers of clinical laboratories communicating critical laboratory test values to professionals via either manual notification or automated alerting systems/computerized reminders. Warfarin, an oral anticoagulant, exhibits narrow therapeutic range between treatment response and adverse events. It requires close monitoring of prothrombin time (PT)/international normalized ratio (INR) to ensure patient safety. This study was aimed to evaluate clinical outcomes of patients on warfarin therapy following implementation of a Personal Handy-phone System-based (PHS) alert system capable of generating and delivering text messages to communicate critical PT/INR laboratory results to practitioners' mobile phones in a large tertiary teaching hospital. A retrospective analysis was performed comparing patient clinical outcomes and physician prescribing behavior following conversion from a manual laboratory result alert system to an automated system. Clinical outcomes and practitioner responses to both alert systems were compared. Complications to warfarin therapy, warfarin utilization, and PT/INR results were evaluated for both systems, as well as clinician time to read alert messages, time to warfarin therapy modification, and monitoring frequency. No significant differences were detected in major hemorrhage and thromboembolism, warfarin prescribing patterns, PT/INR results, warfarin therapy modification, or monitoring frequency following implementation of the PHS text alert system. In both study periods, approximately 80% of critical results led to warfarin discontinuation or dose reduction. Senior physicians' follow-up response time to critical results was significantly decreased in the PHS alert study period (46.3% responded within 1 day) compared to the manual notification study period (24.7%; P = 0.015). No difference in follow-up response time was detected for junior physicians. Implementation of an automated PHS-based text alert system did not adversely impact clinical or safety outcomes of patients on warfarin therapy. Approximately 80% immediate recognition of text alerts was achieved. The potential benefits of an automated PHS alert for senior physicians were demonstrated.

Two Different Approaches to Automated Mark Up of Emotions in Text

NASA Astrophysics Data System (ADS)

Francisco, Virginia; Hervás, Raqucl; Gervás, Pablo

This paper presents two different approaches to automated marking up of texts with emotional labels. For the first approach a corpus of example texts previously annotated by human evaluators is mined for an initial assignment of emotional features to words. This results in a List of Emotional Words (LEW) which becomes a useful resource for later automated mark up. The mark up algorithm in this first approach mirrors closely the steps taken during feature extraction, employing for the actual assignment of emotional features a combination of the LEW resource and WordNet for knowledge-based expansion of words not occurring in LEW. The algorithm for automated mark up is tested against new text samples to test its coverage. The second approach mark up texts during their generation. We have a knowledge base which contains the necessary information for marking up the text. This information is related to actions and characters. The algorithm in this case employ the information of the knowledge database and decides the correct emotion for every sentence. The algorithm for automated mark up is tested against four different texts. The results of the two approaches are compared and discussed with respect to three main issues: relative adequacy of each one of the representations used, correctness and coverage of the proposed algorithms, and additional techniques and solutions that may be employed to improve the results.

Interoperability Policy Roadmap

DTIC Science & Technology

2010-01-01

Retrieval – SMART The technique developed by Dr. Gerard Salton for automated information retrieval and text analysis is called the vector-space... Salton , G., Wong, A., Yang, C.S., “A Vector Space Model for Automatic Indexing”, Commu- nications of the ACM, 18, 613-620. [10] Salton , G., McGill

Automated Sentiment Analysis

DTIC Science & Technology

2009-06-01

questions. Our prototype text classifier uses a “vector similarity” approach. This is a well-known technique introduced by Salton , Wong, and Yang (1975...Loveman & T.M. Davies Jr. (Eds.), Guerrilla warfare. Lincoln, NE: University of Nebraska Press, 1985, 47-69. Salton , G., Wong, A., & Yang, C.S. “A

Automated extraction of radiation dose information from CT dose report images.

PubMed

Li, Xinhua; Zhang, Da; Liu, Bob

2011-06-01

The purpose of this article is to describe the development of an automated tool for retrieving texts from CT dose report images. Optical character recognition was adopted to perform text recognitions of CT dose report images. The developed tool is able to automate the process of analyzing multiple CT examinations, including text recognition, parsing, error correction, and exporting data to spreadsheets. The results were precise for total dose-length product (DLP) and were about 95% accurate for CT dose index and DLP of scanned series.

Means of storage and automated monitoring of versions of text technical documentation

NASA Astrophysics Data System (ADS)

Leonovets, S. A.; Shukalov, A. V.; Zharinov, I. O.

2018-03-01

The paper presents automation of the process of preparation, storage and monitoring of version control of a text designer, and program documentation by means of the specialized software is considered. Automation of preparation of documentation is based on processing of the engineering data which are contained in the specifications and technical documentation or in the specification. Data handling assumes existence of strictly structured electronic documents prepared in widespread formats according to templates on the basis of industry standards and generation by an automated method of the program or designer text document. Further life cycle of the document and engineering data entering it are controlled. At each stage of life cycle, archive data storage is carried out. Studies of high-speed performance of use of different widespread document formats in case of automated monitoring and storage are given. The new developed software and the work benches available to the developer of the instrumental equipment are described.

Toward Machine Understanding of Information Quality.

ERIC Educational Resources Information Center

Tang, Rong; Ng, K. B.; Strzalkowski, Tomek; Kantor, Paul B.

2003-01-01

Reports preliminary results of a study to develop and automate new metrics for assessment of information quality in text documents, particularly in news. Through focus group studies, quality judgment experiments, and textual feature extraction and analysis, nine quality aspects were generated and applied in human assessments. Experiments were…

Untangling Topic Threads in Chat-Based Communication: A Case Study

DTIC Science & Technology

2011-08-01

learning techniques such as clustering are very popular for analyzing text for topic identification (Anjewierden,, Kollöffel and Hulshof 2007; Adams...Anjewierden, A., Kollöffel, B., and Hulshof , C. (2007). Towards educational data mining: Using data mining methods for automated chat analysis to

Automated Authorship Attribution Using Advanced Signal Classification Techniques

PubMed Central

Ebrahimpour, Maryam; Putniņš, Tālis J.; Berryman, Matthew J.; Allison, Andrew; Ng, Brian W.-H.; Abbott, Derek

2013-01-01

In this paper, we develop two automated authorship attribution schemes, one based on Multiple Discriminant Analysis (MDA) and the other based on a Support Vector Machine (SVM). The classification features we exploit are based on word frequencies in the text. We adopt an approach of preprocessing each text by stripping it of all characters except a-z and space. This is in order to increase the portability of the software to different types of texts. We test the methodology on a corpus of undisputed English texts, and use leave-one-out cross validation to demonstrate classification accuracies in excess of 90%. We further test our methods on the Federalist Papers, which have a partly disputed authorship and a fair degree of scholarly consensus. And finally, we apply our methodology to the question of the authorship of the Letter to the Hebrews by comparing it against a number of original Greek texts of known authorship. These tests identify where some of the limitations lie, motivating a number of open questions for future work. An open source implementation of our methodology is freely available for use at https://github.com/matthewberryman/author-detection. PMID:23437047

Trends in P Value, Confidence Interval, and Power Analysis Reporting in Health Professions Education Research Reports: A Systematic Appraisal.

PubMed

Abbott, Eduardo F; Serrano, Valentina P; Rethlefsen, Melissa L; Pandian, T K; Naik, Nimesh D; West, Colin P; Pankratz, V Shane; Cook, David A

2018-02-01

To characterize reporting of P values, confidence intervals (CIs), and statistical power in health professions education research (HPER) through manual and computerized analysis of published research reports. The authors searched PubMed, Embase, and CINAHL in May 2016, for comparative research studies. For manual analysis of abstracts and main texts, they randomly sampled 250 HPER reports published in 1985, 1995, 2005, and 2015, and 100 biomedical research reports published in 1985 and 2015. Automated computerized analysis of abstracts included all HPER reports published 1970-2015. In the 2015 HPER sample, P values were reported in 69/100 abstracts and 94 main texts. CIs were reported in 6 abstracts and 22 main texts. Most P values (≥77%) were ≤.05. Across all years, 60/164 two-group HPER studies had ≥80% power to detect a between-group difference of 0.5 standard deviations. From 1985 to 2015, the proportion of HPER abstracts reporting a CI did not change significantly (odds ratio [OR] 2.87; 95% CI 1.04, 7.88) whereas that of main texts reporting a CI increased (OR 1.96; 95% CI 1.39, 2.78). Comparison with biomedical studies revealed similar reporting of P values, but more frequent use of CIs in biomedicine. Automated analysis of 56,440 HPER abstracts found 14,867 (26.3%) reporting a P value, 3,024 (5.4%) reporting a CI, and increased reporting of P values and CIs from 1970 to 2015. P values are ubiquitous in HPER, CIs are rarely reported, and most studies are underpowered. Most reported P values would be considered statistically significant.

Automated assessment of medical training evaluation text.

PubMed

Zhang, Rui; Pakhomov, Serguei; Gladding, Sophia; Aylward, Michael; Borman-Shoap, Emily; Melton, Genevieve B

2012-01-01

Medical post-graduate residency training and medical student training increasingly utilize electronic systems to evaluate trainee performance based on defined training competencies with quantitative and qualitative data, the later of which typically consists of text comments. Medical education is concomitantly becoming a growing area of clinical research. While electronic systems have proliferated in number, little work has been done to help manage and analyze qualitative data from these evaluations. We explored the use of text-mining techniques to assist medical education researchers in sentiment analysis and topic analysis of residency evaluations with a sample of 812 evaluation statements. While comments were predominantly positive, sentiment analysis improved the ability to discriminate statements with 93% accuracy. Similar to other domains, Latent Dirichlet Analysis and Information Gain revealed groups of core subjects and appear to be useful for identifying topics from this data.

Automation of Educational Tasks for Academic Radiology.

PubMed

Lamar, David L; Richardson, Michael L; Carlson, Blake

2016-07-01

The process of education involves a variety of repetitious tasks. We believe that appropriate computer tools can automate many of these chores, and allow both educators and their students to devote a lot more of their time to actual teaching and learning. This paper details tools that we have used to automate a broad range of academic radiology-specific tasks on Mac OS X, iOS, and Windows platforms. Some of the tools we describe here require little expertise or time to use; others require some basic knowledge of computer programming. We used TextExpander (Mac, iOS) and AutoHotKey (Win) for automated generation of text files, such as resident performance reviews and radiology interpretations. Custom statistical calculations were performed using TextExpander and the Python programming language. A workflow for automated note-taking was developed using Evernote (Mac, iOS, Win) and Hazel (Mac). Automated resident procedure logging was accomplished using Editorial (iOS) and Python. We created three variants of a teaching session logger using Drafts (iOS) and Pythonista (iOS). Editorial and Drafts were used to create flashcards for knowledge review. We developed a mobile reference management system for iOS using Editorial. We used the Workflow app (iOS) to automatically generate a text message reminder for daily conferences. Finally, we developed two separate automated workflows-one with Evernote (Mac, iOS, Win) and one with Python (Mac, Win)-that generate simple automated teaching file collections. We have beta-tested these workflows, techniques, and scripts on several of our fellow radiologists. All of them expressed enthusiasm for these tools and were able to use one or more of them to automate their own educational activities. Appropriate computer tools can automate many educational tasks, and thereby allow both educators and their students to devote a lot more of their time to actual teaching and learning. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

NOUS: A Knowledge Graph Management System

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

Knowledge graphs represent information as entities and relationships between them. For tasks such as natural language question answering or automated analysis of text, a knowledge graph provides valuable context to establish the specific type of entities being discussed. It allow us to derive better context about newly arriving information and leads to intelligent reasoning capabilities. We address two primary needs: A) Automated construction of knowledge graphs is a technically challenging, expensive process; and B) The ability to synthesize new information by monitoring newly emerging knowledge is a transformational capability that does not exist in state of the art systems.

Can we replace curation with information extraction software?

PubMed

Karp, Peter D

2016-01-01

Can we use programs for automated or semi-automated information extraction from scientific texts as practical alternatives to professional curation? I show that error rates of current information extraction programs are too high to replace professional curation today. Furthermore, current IEP programs extract single narrow slivers of information, such as individual protein interactions; they cannot extract the large breadth of information extracted by professional curators for databases such as EcoCyc. They also cannot arbitrate among conflicting statements in the literature as curators can. Therefore, funding agencies should not hobble the curation efforts of existing databases on the assumption that a problem that has stymied Artificial Intelligence researchers for more than 60 years will be solved tomorrow. Semi-automated extraction techniques appear to have significantly more potential based on a review of recent tools that enhance curator productivity. But a full cost-benefit analysis for these tools is lacking. Without such analysis it is possible to expend significant effort developing information-extraction tools that automate small parts of the overall curation workflow without achieving a significant decrease in curation costs.Database URL. © The Author(s) 2016. Published by Oxford University Press.

Project TwEATs: a feasibility study testing the use of automated text messaging to monitor appetite ratings in a free-living population

PubMed Central

Schembre, Susan M.; Yuen, Jessica

2011-01-01

There are no standardized methods for monitoring appetite in free-living populations. Fifteen participants tested a computer-automated text-messaging system designed to track hunger ratings over seven days. Participants were sent text-messages (SMS) hourly and instructed to reply during waking hours with their current hunger rating. Of 168 SMS, 0.6-7.1% were undelivered, varying by mobile service provider, On average 12 SMS responses were received daily with minor variations by observation day or day of the week. Compliance was over 74% and 93% of the ratings were received within 30-minutes. Automated text-messaging is a feasible method to monitor appetite ratings in this population. PMID:21251941

Forensic Analysis of Compromised Computers

NASA Technical Reports Server (NTRS)

Wolfe, Thomas

2004-01-01

Directory Tree Analysis File Generator is a Practical Extraction and Reporting Language (PERL) script that simplifies and automates the collection of information for forensic analysis of compromised computer systems. During such an analysis, it is sometimes necessary to collect and analyze information about files on a specific directory tree. Directory Tree Analysis File Generator collects information of this type (except information about directories) and writes it to a text file. In particular, the script asks the user for the root of the directory tree to be processed, the name of the output file, and the number of subtree levels to process. The script then processes the directory tree and puts out the aforementioned text file. The format of the text file is designed to enable the submission of the file as input to a spreadsheet program, wherein the forensic analysis is performed. The analysis usually consists of sorting files and examination of such characteristics of files as ownership, time of creation, and time of most recent access, all of which characteristics are among the data included in the text file.

Deriving pathway maps from automated text analysis using a grammar-based approach.

PubMed

Olsson, Björn; Gawronska, Barbara; Erlendsson, Björn

2006-04-01

We demonstrate how automated text analysis can be used to support the large-scale analysis of metabolic and regulatory pathways by deriving pathway maps from textual descriptions found in the scientific literature. The main assumption is that correct syntactic analysis combined with domain-specific heuristics provides a good basis for relation extraction. Our method uses an algorithm that searches through the syntactic trees produced by a parser based on a Referent Grammar formalism, identifies relations mentioned in the sentence, and classifies them with respect to their semantic class and epistemic status (facts, counterfactuals, hypotheses). The semantic categories used in the classification are based on the relation set used in KEGG (Kyoto Encyclopedia of Genes and Genomes), so that pathway maps using KEGG notation can be automatically generated. We present the current version of the relation extraction algorithm and an evaluation based on a corpus of abstracts obtained from PubMed. The results indicate that the method is able to combine a reasonable coverage with high accuracy. We found that 61% of all sentences were parsed, and 97% of the parse trees were judged to be correct. The extraction algorithm was tested on a sample of 300 parse trees and was found to produce correct extractions in 90.5% of the cases.

Sharing feelings online: studying emotional well-being via automated text analysis of Facebook posts.

PubMed

Settanni, Michele; Marengo, Davide

2015-01-01

Digital traces of activity on social network sites represent a vast source of ecological data with potential connections with individual behavioral and psychological characteristics. The present study investigates the relationship between user-generated textual content shared on Facebook and emotional well-being. Self-report measures of depression, anxiety, and stress were collected from 201 adult Facebook users from North Italy. Emotion-related textual indicators, including emoticon use, were extracted form users' Facebook posts via automated text analysis. Correlation analyses revealed that individuals with higher levels of depression, anxiety expressed negative emotions on Facebook more frequently. In addition, use of emoticons expressing positive emotions correlated negatively with stress level. When comparing age groups, younger users reported higher frequency of both emotion-related words and emoticon use in their posts. Also, the relationship between online emotional expression and self-report emotional well-being was generally stronger in the younger group. Overall, findings support the feasibility and validity of studying individual emotional well-being by means of examination of Facebook profiles. Implications for online screening purposes and future research directions are discussed.

Sharing feelings online: studying emotional well-being via automated text analysis of Facebook posts

PubMed Central

Settanni, Michele; Marengo, Davide

2015-01-01

Digital traces of activity on social network sites represent a vast source of ecological data with potential connections with individual behavioral and psychological characteristics. The present study investigates the relationship between user-generated textual content shared on Facebook and emotional well-being. Self-report measures of depression, anxiety, and stress were collected from 201 adult Facebook users from North Italy. Emotion-related textual indicators, including emoticon use, were extracted form users’ Facebook posts via automated text analysis. Correlation analyses revealed that individuals with higher levels of depression, anxiety expressed negative emotions on Facebook more frequently. In addition, use of emoticons expressing positive emotions correlated negatively with stress level. When comparing age groups, younger users reported higher frequency of both emotion-related words and emoticon use in their posts. Also, the relationship between online emotional expression and self-report emotional well-being was generally stronger in the younger group. Overall, findings support the feasibility and validity of studying individual emotional well-being by means of examination of Facebook profiles. Implications for online screening purposes and future research directions are discussed. PMID:26257692

A Depression Prevention Intervention for Adolescents in the Emergency Department.

PubMed

Ranney, Megan L; Freeman, Joshua R; Connell, Gerianne; Spirito, Anthony; Boyer, Edward; Walton, Maureen; Guthrie, Kate Morrow; Cunningham, Rebecca M

2016-10-01

To evaluate acceptability and feasibility of a theoretically based two-part (brief in-person + 8-week automated text message) depression prevention program, "intervention for DepressiOn and Violence prevention in the Emergency department" (iDOVE), for high-risk adolescents. English-speaking emergency department (ED) patients (age 13-17, any chief complaint) were sequentially approached for consent on a convenience sample of shifts and screened for inclusion based on current depressive symptoms and past-year violence. After consent, baseline assessments were obtained; all participants were enrolled in the two-part intervention (brief in-ED + 8-week two-way text messaging). At 8 weeks, quantitative and qualitative follow-up assessments were obtained. Measures included feasibility, acceptability, and preliminary data on efficacy. Qualitative data were transcribed verbatim, double coded, and interpreted using thematic analysis. Quantitative results were analyzed descriptively and with paired t tests. As planned, 16 participants (eight each gender) were recruited (75% of those who were eligible; 66% nonwhite, 63% low income, mean age 15.4). The intervention had high feasibility and acceptability: 93.8% completed 8-week follow-up; 80% of daily text messages received responses; 31% of participants requested ≥1 "on-demand" text message. In-person and text message portions were rated as good/excellent by 87%. Qualitatively, participants articulated: (1) iDOVE was welcome and helpful, if unexpected in the ED; (2) the daily text message mood assessment was "most important"; (3) content was "uplifting"; and (4) balancing intervention "relatability" and automation was challenging. Participants' mean ΔBDI-2 (Beck Depression Inventory) from baseline to 8-week follow-up was -4.9, (p = .02). This automated preventive text message intervention is acceptable and feasible. Qualitative data emphasize the importance of creating positive, relevant, and interactive digital health tools for adolescents. Copyright © 2016 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Software for Analyzing Sequences of Flow-Related Images

NASA Technical Reports Server (NTRS)

Klimek, Robert; Wright, Ted

2004-01-01

Spotlight is a computer program for analysis of sequences of images generated in combustion and fluid physics experiments. Spotlight can perform analysis of a single image in an interactive mode or a sequence of images in an automated fashion. The primary type of analysis is tracking of positions of objects over sequences of frames. Features and objects that are typically tracked include flame fronts, particles, droplets, and fluid interfaces. Spotlight automates the analysis of object parameters, such as centroid position, velocity, acceleration, size, shape, intensity, and color. Images can be processed to enhance them before statistical and measurement operations are performed. An unlimited number of objects can be analyzed simultaneously. Spotlight saves results of analyses in a text file that can be exported to other programs for graphing or further analysis. Spotlight is a graphical-user-interface-based program that at present can be executed on Microsoft Windows and Linux operating systems. A version that runs on Macintosh computers is being considered.

BioTextQuest: a web-based biomedical text mining suite for concept discovery.

PubMed

Papanikolaou, Nikolas; Pafilis, Evangelos; Nikolaou, Stavros; Ouzounis, Christos A; Iliopoulos, Ioannis; Promponas, Vasilis J

2011-12-01

BioTextQuest combines automated discovery of significant terms in article clusters with structured knowledge annotation, via Named Entity Recognition services, offering interactive user-friendly visualization. A tag-cloud-based illustration of terms labeling each document cluster are semantically annotated according to the biological entity, and a list of document titles enable users to simultaneously compare terms and documents of each cluster, facilitating concept association and hypothesis generation. BioTextQuest allows customization of analysis parameters, e.g. clustering/stemming algorithms, exclusion of documents/significant terms, to better match the biological question addressed. http://biotextquest.biol.ucy.ac.cy vprobon@ucy.ac.cy; iliopj@med.uoc.gr Supplementary data are available at Bioinformatics online.

Proceeding of the ACM/IEEE-CS Joint Conference on Digital Libraries (1st, Roanoke, Virginia, June 24-28, 2001).

ERIC Educational Resources Information Center

Association for Computing Machinery, New York, NY.

Papers in this Proceedings of the ACM/IEEE-CS Joint Conference on Digital Libraries (Roanoke, Virginia, June 24-28, 2001) discuss: automatic genre analysis; text categorization; automated name authority control; automatic event generation; linked active content; designing e-books for legal research; metadata harvesting; mapping the…

OpenCyto: An Open Source Infrastructure for Scalable, Robust, Reproducible, and Automated, End-to-End Flow Cytometry Data Analysis

PubMed Central

Finak, Greg; Frelinger, Jacob; Jiang, Wenxin; Newell, Evan W.; Ramey, John; Davis, Mark M.; Kalams, Spyros A.; De Rosa, Stephen C.; Gottardo, Raphael

2014-01-01

Flow cytometry is used increasingly in clinical research for cancer, immunology and vaccines. Technological advances in cytometry instrumentation are increasing the size and dimensionality of data sets, posing a challenge for traditional data management and analysis. Automated analysis methods, despite a general consensus of their importance to the future of the field, have been slow to gain widespread adoption. Here we present OpenCyto, a new BioConductor infrastructure and data analysis framework designed to lower the barrier of entry to automated flow data analysis algorithms by addressing key areas that we believe have held back wider adoption of automated approaches. OpenCyto supports end-to-end data analysis that is robust and reproducible while generating results that are easy to interpret. We have improved the existing, widely used core BioConductor flow cytometry infrastructure by allowing analysis to scale in a memory efficient manner to the large flow data sets that arise in clinical trials, and integrating domain-specific knowledge as part of the pipeline through the hierarchical relationships among cell populations. Pipelines are defined through a text-based csv file, limiting the need to write data-specific code, and are data agnostic to simplify repetitive analysis for core facilities. We demonstrate how to analyze two large cytometry data sets: an intracellular cytokine staining (ICS) data set from a published HIV vaccine trial focused on detecting rare, antigen-specific T-cell populations, where we identify a new subset of CD8 T-cells with a vaccine-regimen specific response that could not be identified through manual analysis, and a CyTOF T-cell phenotyping data set where a large staining panel and many cell populations are a challenge for traditional analysis. The substantial improvements to the core BioConductor flow cytometry packages give OpenCyto the potential for wide adoption. It can rapidly leverage new developments in computational cytometry and facilitate reproducible analysis in a unified environment. PMID:25167361

OpenCyto: an open source infrastructure for scalable, robust, reproducible, and automated, end-to-end flow cytometry data analysis.

PubMed

Finak, Greg; Frelinger, Jacob; Jiang, Wenxin; Newell, Evan W; Ramey, John; Davis, Mark M; Kalams, Spyros A; De Rosa, Stephen C; Gottardo, Raphael

2014-08-01

Flow cytometry is used increasingly in clinical research for cancer, immunology and vaccines. Technological advances in cytometry instrumentation are increasing the size and dimensionality of data sets, posing a challenge for traditional data management and analysis. Automated analysis methods, despite a general consensus of their importance to the future of the field, have been slow to gain widespread adoption. Here we present OpenCyto, a new BioConductor infrastructure and data analysis framework designed to lower the barrier of entry to automated flow data analysis algorithms by addressing key areas that we believe have held back wider adoption of automated approaches. OpenCyto supports end-to-end data analysis that is robust and reproducible while generating results that are easy to interpret. We have improved the existing, widely used core BioConductor flow cytometry infrastructure by allowing analysis to scale in a memory efficient manner to the large flow data sets that arise in clinical trials, and integrating domain-specific knowledge as part of the pipeline through the hierarchical relationships among cell populations. Pipelines are defined through a text-based csv file, limiting the need to write data-specific code, and are data agnostic to simplify repetitive analysis for core facilities. We demonstrate how to analyze two large cytometry data sets: an intracellular cytokine staining (ICS) data set from a published HIV vaccine trial focused on detecting rare, antigen-specific T-cell populations, where we identify a new subset of CD8 T-cells with a vaccine-regimen specific response that could not be identified through manual analysis, and a CyTOF T-cell phenotyping data set where a large staining panel and many cell populations are a challenge for traditional analysis. The substantial improvements to the core BioConductor flow cytometry packages give OpenCyto the potential for wide adoption. It can rapidly leverage new developments in computational cytometry and facilitate reproducible analysis in a unified environment.

Fostering Student Introspection through Guided Reflection Forms

NASA Astrophysics Data System (ADS)

Wood, Laura; Matheson, Amanda; Franklin, Scott

2017-01-01

Student self-reflection is an important metacognitive skill to developing expert-like habits of mind. This study focuses on student responses to Guided Reflection Forms (GRFs) and individualized instructor feedback to the submissions. Student and instructor entries were hand-coded by an emergent rubric and, separately, analyzed with LIWC (Linguistic Inquiry and Word Count), a computerized text analysis program that extracts affective sentiment. Sentiment analysis supports the development of a stable basis set (rubric) to describe responses that is robust across both introductory and advanced classes. The analysis also reveals the instructor's use of the ``praise sandwich,'' instinctively embedding critiques and suggestions between specific and general encouragements. The study demonstrates the utility of validated, automated, sentiment analysis as a method by which to analyze large corpuses of written text.

The Impact of Anonymization for Automated Essay Scoring

ERIC Educational Resources Information Center

Shermis, Mark D.; Lottridge, Sue; Mayfield, Elijah

2015-01-01

This study investigated the impact of anonymizing text on predicted scores made by two kinds of automated scoring engines: one that incorporates elements of natural language processing (NLP) and one that does not. Eight data sets (N = 22,029) were used to form both training and test sets in which the scoring engines had access to both text and…

On the Relation between Automated Essay Scoring and Modern Views of the Writing Construct

ERIC Educational Resources Information Center

Deane, Paul

2013-01-01

This paper examines the construct measured by automated essay scoring (AES) systems. AES systems measure features of the text structure, linguistic structure, and conventional print form of essays; as such, the systems primarily measure text production skills. In the current state-of-the-art, AES provide little direct evidence about such matters…

Automated Illustration of Patients Instructions

PubMed Central

Bui, Duy; Nakamura, Carlos; Bray, Bruce E.; Zeng-Treitler, Qing

2012-01-01

A picture can be a powerful communication tool. However, creating pictures to illustrate patient instructions can be a costly and time-consuming task. Building on our prior research in this area, we developed a computer application that automatically converts text to pictures using natural language processing and computer graphics techniques. After iterative testing, the automated illustration system was evaluated using 49 previously unseen cardiology discharge instructions. The completeness of the system-generated illustrations was assessed by three raters using a three-level scale. The average inter-rater agreement for text correctly represented in the pictograph was about 66 percent. Since illustration in this context is intended to enhance rather than replace text, these results support the feasibility of conducting automated illustration. PMID:23304392

Machine Learning, Sentiment Analysis, and Tweets: An Examination of Alzheimer's Disease Stigma on Twitter.

PubMed

Oscar, Nels; Fox, Pamela A; Croucher, Racheal; Wernick, Riana; Keune, Jessica; Hooker, Karen

2017-09-01

Social scientists need practical methods for harnessing large, publicly available datasets that inform the social context of aging. We describe our development of a semi-automated text coding method and use a content analysis of Alzheimer's disease (AD) and dementia portrayal on Twitter to demonstrate its use. The approach improves feasibility of examining large publicly available datasets. Machine learning techniques modeled stigmatization expressed in 31,150 AD-related tweets collected via Twitter's search API based on 9 AD-related keywords. Two researchers manually coded 311 random tweets on 6 dimensions. This input from 1% of the dataset was used to train a classifier against the tweet text and code the remaining 99% of the dataset. Our automated process identified that 21.13% of the AD-related tweets used AD-related keywords to perpetuate public stigma, which could impact stereotypes and negative expectations for individuals with the disease and increase "excess disability". This technique could be applied to questions in social gerontology related to how social media outlets reflect and shape attitudes bearing on other developmental outcomes. Recommendations for the collection and analysis of large Twitter datasets are discussed. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Automated Outcome Classification of Computed Tomography Imaging Reports for Pediatric Traumatic Brain Injury.

PubMed

Yadav, Kabir; Sarioglu, Efsun; Choi, Hyeong Ah; Cartwright, Walter B; Hinds, Pamela S; Chamberlain, James M

2016-02-01

The authors have previously demonstrated highly reliable automated classification of free-text computed tomography (CT) imaging reports using a hybrid system that pairs linguistic (natural language processing) and statistical (machine learning) techniques. Previously performed for identifying the outcome of orbital fracture in unprocessed radiology reports from a clinical data repository, the performance has not been replicated for more complex outcomes. To validate automated outcome classification performance of a hybrid natural language processing (NLP) and machine learning system for brain CT imaging reports. The hypothesis was that our system has performance characteristics for identifying pediatric traumatic brain injury (TBI). This was a secondary analysis of a subset of 2,121 CT reports from the Pediatric Emergency Care Applied Research Network (PECARN) TBI study. For that project, radiologists dictated CT reports as free text, which were then deidentified and scanned as PDF documents. Trained data abstractors manually coded each report for TBI outcome. Text was extracted from the PDF files using optical character recognition. The data set was randomly split evenly for training and testing. Training patient reports were used as input to the Medical Language Extraction and Encoding (MedLEE) NLP tool to create structured output containing standardized medical terms and modifiers for negation, certainty, and temporal status. A random subset stratified by site was analyzed using descriptive quantitative content analysis to confirm identification of TBI findings based on the National Institute of Neurological Disorders and Stroke (NINDS) Common Data Elements project. Findings were coded for presence or absence, weighted by frequency of mentions, and past/future/indication modifiers were filtered. After combining with the manual reference standard, a decision tree classifier was created using data mining tools WEKA 3.7.5 and Salford Predictive Miner 7.0. Performance of the decision tree classifier was evaluated on the test patient reports. The prevalence of TBI in the sampled population was 159 of 2,217 (7.2%). The automated classification for pediatric TBI is comparable to our prior results, with the notable exception of lower positive predictive value. Manual review of misclassified reports, 95.5% of which were false-positives, revealed that a sizable number of false-positive errors were due to differing outcome definitions between NINDS TBI findings and PECARN clinical important TBI findings and report ambiguity not meeting definition criteria. A hybrid NLP and machine learning automated classification system continues to show promise in coding free-text electronic clinical data. For complex outcomes, it can reliably identify negative reports, but manual review of positive reports may be required. As such, it can still streamline data collection for clinical research and performance improvement. © 2016 by the Society for Academic Emergency Medicine.

Automated Outcome Classification of Computed Tomography Imaging Reports for Pediatric Traumatic Brain Injury

PubMed Central

Yadav, Kabir; Sarioglu, Efsun; Choi, Hyeong-Ah; Cartwright, Walter B.; Hinds, Pamela S.; Chamberlain, James M.

2016-01-01

Background The authors have previously demonstrated highly reliable automated classification of free text computed tomography (CT) imaging reports using a hybrid system that pairs linguistic (natural language processing) and statistical (machine learning) techniques. Previously performed for identifying the outcome of orbital fracture in unprocessed radiology reports from a clinical data repository, the performance has not been replicated for more complex outcomes. Objectives To validate automated outcome classification performance of a hybrid natural language processing (NLP) and machine learning system for brain CT imaging reports. The hypothesis was that our system has performance characteristics for identifying pediatric traumatic brain injury (TBI). Methods This was a secondary analysis of a subset of 2,121 CT reports from the Pediatric Emergency Care Applied Research Network (PECARN) TBI study. For that project, radiologists dictated CT reports as free text, which were then de-identified and scanned as PDF documents. Trained data abstractors manually coded each report for TBI outcome. Text was extracted from the PDF files using optical character recognition. The dataset was randomly split evenly for training and testing. Training patient reports were used as input to the Medical Language Extraction and Encoding (MedLEE) NLP tool to create structured output containing standardized medical terms and modifiers for negation, certainty, and temporal status. A random subset stratified by site was analyzed using descriptive quantitative content analysis to confirm identification of TBI findings based upon the National Institute of Neurological Disorders and Stroke Common Data Elements project. Findings were coded for presence or absence, weighted by frequency of mentions, and past/future/indication modifiers were filtered. After combining with the manual reference standard, a decision tree classifier was created using data mining tools WEKA 3.7.5 and Salford Predictive Miner 7.0. Performance of the decision tree classifier was evaluated on the test patient reports. Results The prevalence of TBI in the sampled population was 159 out of 2,217 (7.2%). The automated classification for pediatric TBI is comparable to our prior results, with the notable exception of lower positive predictive value (PPV). Manual review of misclassified reports, 95.5% of which were false positives, revealed that a sizable number of false-positive errors were due to differing outcome definitions between NINDS TBI findings and PECARN clinical important TBI findings, and report ambiguity not meeting definition criteria. Conclusions A hybrid NLP and machine learning automated classification system continues to show promise in coding free-text electronic clinical data. For complex outcomes, it can reliably identify negative reports, but manual review of positive reports may be required. As such, it can still streamline data collection for clinical research and performance improvement. PMID:26766600

The structure of the EU mediasphere.

PubMed

Flaounas, Ilias; Turchi, Marco; Ali, Omar; Fyson, Nick; De Bie, Tijl; Mosdell, Nick; Lewis, Justin; Cristianini, Nello

2010-12-08

A trend towards automation of scientific research has recently resulted in what has been termed "data-driven inquiry" in various disciplines, including physics and biology. The automation of many tasks has been identified as a possible future also for the humanities and the social sciences, particularly in those disciplines concerned with the analysis of text, due to the recent availability of millions of books and news articles in digital format. In the social sciences, the analysis of news media is done largely by hand and in a hypothesis-driven fashion: the scholar needs to formulate a very specific assumption about the patterns that might be in the data, and then set out to verify if they are present or not. In this study, we report what we think is the first large scale content-analysis of cross-linguistic text in the social sciences, by using various artificial intelligence techniques. We analyse 1.3 M news articles in 22 languages detecting a clear structure in the choice of stories covered by the various outlets. This is significantly affected by objective national, geographic, economic and cultural relations among outlets and countries, e.g., outlets from countries sharing strong economic ties are more likely to cover the same stories. We also show that the deviation from average content is significantly correlated with membership to the eurozone, as well as with the year of accession to the EU. While independently making a multitude of small editorial decisions, the leading media of the 27 EU countries, over a period of six months, shaped the contents of the EU mediasphere in a way that reflects its deep geographic, economic and cultural relations. Detecting these subtle signals in a statistically rigorous way would be out of the reach of traditional methods. This analysis demonstrates the power of the available methods for significant automation of media content analysis.

The Structure of the EU Mediasphere

PubMed Central

Flaounas, Ilias; Turchi, Marco; Ali, Omar; Fyson, Nick; De Bie, Tijl; Mosdell, Nick; Lewis, Justin; Cristianini, Nello

2010-01-01

Background A trend towards automation of scientific research has recently resulted in what has been termed “data-driven inquiry” in various disciplines, including physics and biology. The automation of many tasks has been identified as a possible future also for the humanities and the social sciences, particularly in those disciplines concerned with the analysis of text, due to the recent availability of millions of books and news articles in digital format. In the social sciences, the analysis of news media is done largely by hand and in a hypothesis-driven fashion: the scholar needs to formulate a very specific assumption about the patterns that might be in the data, and then set out to verify if they are present or not. Methodology/Principal Findings In this study, we report what we think is the first large scale content-analysis of cross-linguistic text in the social sciences, by using various artificial intelligence techniques. We analyse 1.3 M news articles in 22 languages detecting a clear structure in the choice of stories covered by the various outlets. This is significantly affected by objective national, geographic, economic and cultural relations among outlets and countries, e.g., outlets from countries sharing strong economic ties are more likely to cover the same stories. We also show that the deviation from average content is significantly correlated with membership to the eurozone, as well as with the year of accession to the EU. Conclusions/Significance While independently making a multitude of small editorial decisions, the leading media of the 27 EU countries, over a period of six months, shaped the contents of the EU mediasphere in a way that reflects its deep geographic, economic and cultural relations. Detecting these subtle signals in a statistically rigorous way would be out of the reach of traditional methods. This analysis demonstrates the power of the available methods for significant automation of media content analysis. PMID:21170383

Feasibility and effectiveness of an automated bilingual text message intervention for weight loss: pilot study.

PubMed

Kolodziejczyk, Julia K; Norman, Gregory J; Barrera-Ng, Angelica; Dillon, Lindsay; Marshall, Simon; Arredondo, Elva; Rock, Cheryl L; Raab, Fred; Griswold, William G; Sullivan, Mark; Patrick, Kevin

2013-11-06

Little is known about the feasibility and acceptability of tailored text message based weight loss programs for English and Spanish-language speakers. This pilot study evaluated the feasibility, acceptability, and estimated impact of a tailored text message based weight loss program for English and Spanish-language speakers. The purpose of this pilot study was to inform the development of a full-scale randomized trial. There were 20 overweight or obese participants (mean age 40.10, SD 8.05; 8/20, 40% male; 9/20, 45% Spanish-speakers) that were recruited in San Diego, California, from March to May 2011 and evaluated in a one-group pre/post clinical trial. For 8 weeks, participants received and responded to 3-5 text messages daily sent from a fully automated text messaging system. They also received printed weight loss materials and brief 10-15 minute weekly counseling calls. To estimate the impact of the program, the primary outcome was weight (kg) measured during face-to-face measurement visits by trained research staff. Pre and post differences in weight were analyzed with a one-way repeated measures analysis of variance. Differences by language preference at both time points were analyzed with t tests. Body mass index and weight management behaviors also were examined. Feasibility and acceptability were determined by recruitment success, adherence (ie, percentage of replies to interactive text messages and attrition), and participant satisfaction. Participants who completed the final assessment (N=18) decreased body weight by 1.85 kg (F1,17=10.80, P=.004, CI∆ 0.66-3.03, η(2)=0.39). At both time points, there were no differences in weight by language preference. Participants responded to 88.04% (986/1120) of interactive text messages, attrition rate was 10% (2/20), and 94% (19/20) of participants reported satisfaction with the program. This fully automated text message based weight program was feasible with English and Spanish-speakers and may have promoted modest weight loss over an 8-week period. Clinicaltrials.gov NCT01171586; http://clinicaltrials.gov/ct2/show/NCT01171586 (Archived by WebCite at http://www.webcitation.org/6Ksr6dl7n).

A probabilistic-entropy approach of finding thematically similar documents with creating context-semantic graph for investigating evolution of society opinion

NASA Astrophysics Data System (ADS)

Moloshnikov, I. A.; Sboev, A. G.; Rybka, R. B.; Gydovskikh, D. V.

2016-02-01

The composite algorithm integrating, on one hand, the algorithm of finding documents on a given topic, and, on the other hand, the method of emotiveness evaluation of topical texts is presented. This method is convenient for analysis of people opinions expressed in social media and, as a result, for automated analysis of event evolutions in social media. Some examples of such analysing are demonstrated and discussed.

Applications of Automation Methods for Nonlinear Fracture Test Analysis

NASA Technical Reports Server (NTRS)

Allen, Phillip A.; Wells, Douglas N.

2013-01-01

Using automated and standardized computer tools to calculate the pertinent test result values has several advantages such as: 1. allowing high-fidelity solutions to complex nonlinear phenomena that would be impractical to express in written equation form, 2. eliminating errors associated with the interpretation and programing of analysis procedures from the text of test standards, 3. lessening the need for expertise in the areas of solid mechanics, fracture mechanics, numerical methods, and/or finite element modeling, to achieve sound results, 4. and providing one computer tool and/or one set of solutions for all users for a more "standardized" answer. In summary, this approach allows a non-expert with rudimentary training to get the best practical solution based on the latest understanding with minimum difficulty.Other existing ASTM standards that cover complicated phenomena use standard computer programs: 1. ASTM C1340/C1340M-10- Standard Practice for Estimation of Heat Gain or Loss Through Ceilings Under Attics Containing Radiant Barriers by Use of a Computer Program 2. ASTM F 2815 - Standard Practice for Chemical Permeation through Protective Clothing Materials: Testing Data Analysis by Use of a Computer Program 3. ASTM E2807 - Standard Specification for 3D Imaging Data Exchange, Version 1.0 The verification, validation, and round-robin processes required of a computer tool closely parallel the methods that are used to ensure the solution validity for equations included in test standard. The use of automated analysis tools allows the creation and practical implementation of advanced fracture mechanics test standards that capture the physics of a nonlinear fracture mechanics problem without adding undue burden or expense to the user. The presented approach forms a bridge between the equation-based fracture testing standards of today and the next generation of standards solving complex problems through analysis automation.

Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB.

PubMed

Chatziioannou, Aristotelis; Moulos, Panagiotis; Kolisis, Fragiskos N

2009-10-27

The microarray data analysis realm is ever growing through the development of various tools, open source and commercial. However there is absence of predefined rational algorithmic analysis workflows or batch standardized processing to incorporate all steps, from raw data import up to the derivation of significantly differentially expressed gene lists. This absence obfuscates the analytical procedure and obstructs the massive comparative processing of genomic microarray datasets. Moreover, the solutions provided, heavily depend on the programming skills of the user, whereas in the case of GUI embedded solutions, they do not provide direct support of various raw image analysis formats or a versatile and simultaneously flexible combination of signal processing methods. We describe here Gene ARMADA (Automated Robust MicroArray Data Analysis), a MATLAB implemented platform with a Graphical User Interface. This suite integrates all steps of microarray data analysis including automated data import, noise correction and filtering, normalization, statistical selection of differentially expressed genes, clustering, classification and annotation. In its current version, Gene ARMADA fully supports 2 coloured cDNA and Affymetrix oligonucleotide arrays, plus custom arrays for which experimental details are given in tabular form (Excel spreadsheet, comma separated values, tab-delimited text formats). It also supports the analysis of already processed results through its versatile import editor. Besides being fully automated, Gene ARMADA incorporates numerous functionalities of the Statistics and Bioinformatics Toolboxes of MATLAB. In addition, it provides numerous visualization and exploration tools plus customizable export data formats for seamless integration by other analysis tools or MATLAB, for further processing. Gene ARMADA requires MATLAB 7.4 (R2007a) or higher and is also distributed as a stand-alone application with MATLAB Component Runtime. Gene ARMADA provides a highly adaptable, integrative, yet flexible tool which can be used for automated quality control, analysis, annotation and visualization of microarray data, constituting a starting point for further data interpretation and integration with numerous other tools.

Analyzing Language in Suicide Notes and Legacy Tokens.

PubMed

Egnoto, Michael J; Griffin, Darrin J

2016-03-01

Identifying precursors that will aid in the discovery of individuals who may harm themselves or others has long been a focus of scholarly research. This work set out to determine if it is possible to use the legacy tokens of active shooters and notes left from individuals who completed suicide to uncover signals that foreshadow their behavior. A total of 25 suicide notes and 21 legacy tokens were compared with a sample of over 20,000 student writings for a preliminary computer-assisted text analysis to determine what differences can be coded with existing computer software to better identify students who may commit self-harm or harm to others. The results support that text analysis techniques with the Linguistic Inquiry and Word Count (LIWC) tool are effective for identifying suicidal or homicidal writings as distinct from each other and from a variety of student writings in an automated fashion. Findings indicate support for automated identification of writings that were associated with harm to self, harm to others, and various other student writing products. This work begins to uncover the viability or larger scale, low cost methods of automatic detection for individuals suffering from harmful ideation.

Don't go with the 'FLO' - a student mobile texting service to enhance nursing student retention.

PubMed

Boath, Elizabeth; Jinks, Annette; Thomas, Nigel; Thompson, Roy; Evans, Jayne; O'Connell, Phil; Taylor, Lisa

2016-10-01

The review undertaken revealed that there is an abundance of literature concerning retention and the high levels of attrition among undergraduate students and of relevance here, nurse education. The study undertaken evaluated the use of mobile phone automated texts designed to provide information, support and reassurance to help alleviate the stress and anxieties that some undergraduate nursing students experience during the early phase of their studies and which can lead to some students leaving their programme. The objective of the study was to evaluate how use of automated mobile phone texts, using a system known as FLO, could usefully supplement pastoral support, as an intervention to reduce attrition among undergraduate nursing students. A qualitative and quantitative evaluation was conducted using an open-ended questionnaire designed specifically for the study. The sample were two cohorts of undergraduate first year student nurses (n=178). Of these 123 (69%) signed up to FLO and 77 (63%) completed the evaluation form. The evaluation form that was administered in a classroom situation one week after use of FLO had ceased. Data were analysed through use of a descriptive statistics and thematic analysis approaches. A range of key themes emerged from the analysis including that text messages were helpful and supportive, increased a sense of belonging to the University and encouraged retention. There were some unresolved issues concerning the costs incurred by participants when sending reply text messages. It is concluded that FLO or use of similar mobile phone protocols can be a useful addition to approaches to improve undergraduate nursing student retention rates. Copyright © 2016 Elsevier Ltd. All rights reserved.

Tashkeela: Novel corpus of Arabic vocalized texts, data for auto-diacritization systems.

PubMed

Zerrouki, Taha; Balla, Amar

2017-04-01

Arabic diacritics are often missed in Arabic scripts. This feature is a handicap for new learner to read َArabic, text to speech conversion systems, reading and semantic analysis of Arabic texts. The automatic diacritization systems are the best solution to handle this issue. But such automation needs resources as diactritized texts to train and evaluate such systems. In this paper, we describe our corpus of Arabic diacritized texts. This corpus is called Tashkeela. It can be used as a linguistic resource tool for natural language processing such as automatic diacritics systems, dis-ambiguity mechanism, features and data extraction. The corpus is freely available, it contains 75 million of fully vocalized words mainly 97 books from classical and modern Arabic language. The corpus is collected from manually vocalized texts using web crawling process.

An Investigation of the "e-rater"® Automated Scoring Engine's Grammar, Usage, Mechanics, and Style Microfeatures and Their Aggregation Model. Research Report. ETS RR-17-04

ERIC Educational Resources Information Center

Chen, Jing; Zhang, Mo; Bejar, Isaac I.

2017-01-01

Automated essay scoring (AES) generally computes essay scores as a function of macrofeatures derived from a set of microfeatures extracted from the text using natural language processing (NLP). In the "e-rater"® automated scoring engine, developed at "Educational Testing Service" (ETS) for the automated scoring of essays, each…

Text recognition and correction for automated data collection by mobile devices

NASA Astrophysics Data System (ADS)

Ozarslan, Suleyman; Eren, P. Erhan

2014-03-01

Participatory sensing is an approach which allows mobile devices such as mobile phones to be used for data collection, analysis and sharing processes by individuals. Data collection is the first and most important part of a participatory sensing system, but it is time consuming for the participants. In this paper, we discuss automatic data collection approaches for reducing the time required for collection, and increasing the amount of collected data. In this context, we explore automated text recognition on images of store receipts which are captured by mobile phone cameras, and the correction of the recognized text. Accordingly, our first goal is to evaluate the performance of the Optical Character Recognition (OCR) method with respect to data collection from store receipt images. Images captured by mobile phones exhibit some typical problems, and common image processing methods cannot handle some of them. Consequently, the second goal is to address these types of problems through our proposed Knowledge Based Correction (KBC) method used in support of the OCR, and also to evaluate the KBC method with respect to the improvement on the accurate recognition rate. Results of the experiments show that the KBC method improves the accurate data recognition rate noticeably.

Automated extraction of radiation dose information for CT examinations.

PubMed

Cook, Tessa S; Zimmerman, Stefan; Maidment, Andrew D A; Kim, Woojin; Boonn, William W

2010-11-01

Exposure to radiation as a result of medical imaging is currently in the spotlight, receiving attention from Congress as well as the lay press. Although scanner manufacturers are moving toward including effective dose information in the Digital Imaging and Communications in Medicine headers of imaging studies, there is a vast repository of retrospective CT data at every imaging center that stores dose information in an image-based dose sheet. As such, it is difficult for imaging centers to participate in the ACR's Dose Index Registry. The authors have designed an automated extraction system to query their PACS archive and parse CT examinations to extract the dose information stored in each dose sheet. First, an open-source optical character recognition program processes each dose sheet and converts the information to American Standard Code for Information Interchange (ASCII) text. Each text file is parsed, and radiation dose information is extracted and stored in a database which can be queried using an existing pathology and radiology enterprise search tool. Using this automated extraction pipeline, it is possible to perform dose analysis on the >800,000 CT examinations in the PACS archive and generate dose reports for all of these patients. It is also possible to more effectively educate technologists, radiologists, and referring physicians about exposure to radiation from CT by generating report cards for interpreted and performed studies. The automated extraction pipeline enables compliance with the ACR's reporting guidelines and greater awareness of radiation dose to patients, thus resulting in improved patient care and management. Copyright © 2010 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Age and automation interact to influence performance of a simulated luggage screening task.

PubMed

Wiegmann, Douglas; McCarley, Jason S; Kramer, Arthur F; Wickens, Christopher D

2006-08-01

An experiment examined the impact of automation on young and old adults' abilities to detect threat objects in a simulated baggage-screening task. Younger and older adult participants viewed X-ray images of cluttered baggage, 20% of which contained a hidden knife. Some participants were provided an automated aid with a hit rate of 0.90 and a false alarm rate of 0.25. The aid provided assistance to participants in one of three forms: a text message that appeared before the stimulus image; a text message that appeared following the stimulus image; or a spatial cue concurrent with the stimulus image. Control participants performed the task with no assistance from an aid. Spatial cuing improved performance for both age groups. Text cuing improved young adults' performance, but had no benefit for older participants. Effects were similar whether the text cue preceded or followed the search stimulus itself. Results indicate that spatial cuing rather than text alerts may be more effective in aiding performance during a baggage screening task and such benefits are likely to occur regardless of operator age.

Text Mining Improves Prediction of Protein Functional Sites

PubMed Central

Cohn, Judith D.; Ravikumar, Komandur E.

2012-01-01

We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions. PMID:22393388

Development of Automated Image Analysis Software for Suspended Marine Particle Classification

DTIC Science & Technology

2003-09-30

Development of Automated Image Analysis Software for Suspended Marine Particle Classification Scott Samson Center for Ocean Technology...REPORT TYPE 3. DATES COVERED 00-00-2003 to 00-00-2003 4. TITLE AND SUBTITLE Development of Automated Image Analysis Software for Suspended...objective is to develop automated image analysis software to reduce the effort and time required for manual identification of plankton images. Automated

Ask and Ye Shall Receive? Automated Text Mining of Michigan Capital Facility Finance Bond Election Proposals to Identify Which Topics Are Associated with Bond Passage and Voter Turnout

ERIC Educational Resources Information Center

Bowers, Alex J.; Chen, Jingjing

2015-01-01

The purpose of this study is to bring together recent innovations in the research literature around school district capital facility finance, municipal bond elections, statistical models of conditional time-varying outcomes, and data mining algorithms for automated text mining of election ballot proposals to examine the factors that influence the…

Applied Actant Network Theory: Toward the Automated Detection of Technoscientific Emergence from Full Text Publications and Patents (Open Access)

DTIC Science & Technology

2012-11-02

Applied Actant-Network Theory: Toward the Automated Detection of Technoscientific Emergence from Full-Text Publications and Patents David C...Brock**, Olga Babko-Malaya*, James Pustejovsky***, Patrick Thomas****, *BAE Systems Advanced Information Technologies, ** David C. Brock Consulting... Wojick , D. 2008. Population modeling of the emergence and development of scientific fields. Scientometrics, 75(3):495–518. Cook, T. D. and

The Effect of Information Analysis Automation Display Content on Human Judgment Performance in Noisy Environments.

PubMed

Bass, Ellen J; Baumgart, Leigh A; Shepley, Kathryn Klein

2013-03-01

Displaying both the strategy that information analysis automation employs to makes its judgments and variability in the task environment may improve human judgment performance, especially in cases where this variability impacts the judgment performance of the information analysis automation. This work investigated the contribution of providing either information analysis automation strategy information, task environment information, or both, on human judgment performance in a domain where noisy sensor data are used by both the human and the information analysis automation to make judgments. In a simplified air traffic conflict prediction experiment, 32 participants made probability of horizontal conflict judgments under different display content conditions. After being exposed to the information analysis automation, judgment achievement significantly improved for all participants as compared to judgments without any of the automation's information. Participants provided with additional display content pertaining to cue variability in the task environment had significantly higher aided judgment achievement compared to those provided with only the automation's judgment of a probability of conflict. When designing information analysis automation for environments where the automation's judgment achievement is impacted by noisy environmental data, it may be beneficial to show additional task environment information to the human judge in order to improve judgment performance.

Effects of response bias and judgment framing on operator use of an automated aid in a target detection task.

PubMed

Rice, Stephen; McCarley, Jason S

2011-12-01

Automated diagnostic aids prone to false alarms often produce poorer human performance in signal detection tasks than equally reliable miss-prone aids. However, it is not yet clear whether this is attributable to differences in the perceptual salience of the automated aids' misses and false alarms or is the result of inherent differences in operators' cognitive responses to different forms of automation error. The present experiments therefore examined the effects of automation false alarms and misses on human performance under conditions in which the different forms of error were matched in their perceptual characteristics. Young adult participants performed a simulated baggage x-ray screening task while assisted by an automated diagnostic aid. Judgments from the aid were rendered as text messages presented at the onset of each trial, and every trial was followed by a second text message providing response feedback. Thus, misses and false alarms from the aid were matched for their perceptual salience. Experiment 1 found that even under these conditions, false alarms from the aid produced poorer human performance and engendered lower automation use than misses from the aid. Experiment 2, however, found that the asymmetry between misses and false alarms was reduced when the aid's false alarms were framed as neutral messages rather than explicit misjudgments. Results suggest that automation false alarms and misses differ in their inherent cognitive salience and imply that changes in diagnosis framing may allow designers to encourage better use of imperfectly reliable automated aids.

SPICODYN: A Toolbox for the Analysis of Neuronal Network Dynamics and Connectivity from Multi-Site Spike Signal Recordings.

PubMed

Pastore, Vito Paolo; Godjoski, Aleksandar; Martinoia, Sergio; Massobrio, Paolo

2018-01-01

We implemented an automated and efficient open-source software for the analysis of multi-site neuronal spike signals. The software package, named SPICODYN, has been developed as a standalone windows GUI application, using C# programming language with Microsoft Visual Studio based on .NET framework 4.5 development environment. Accepted input data formats are HDF5, level 5 MAT and text files, containing recorded or generated time series spike signals data. SPICODYN processes such electrophysiological signals focusing on: spiking and bursting dynamics and functional-effective connectivity analysis. In particular, for inferring network connectivity, a new implementation of the transfer entropy method is presented dealing with multiple time delays (temporal extension) and with multiple binary patterns (high order extension). SPICODYN is specifically tailored to process data coming from different Multi-Electrode Arrays setups, guarantying, in those specific cases, automated processing. The optimized implementation of the Delayed Transfer Entropy and the High-Order Transfer Entropy algorithms, allows performing accurate and rapid analysis on multiple spike trains from thousands of electrodes.

Automated registration of tail bleeding in rats.

PubMed

Johansen, Peter B; Henriksen, Lars; Andresen, Per R; Lauritzen, Brian; Jensen, Kåre L; Juhl, Trine N; Tranholm, Mikael

2008-05-01

An automated system for registration of tail bleeding in rats using a camera and a user-designed PC-based software program has been developed. The live and processed images are displayed on the screen and are exported together with a text file for later statistical processing of the data allowing calculation of e.g. number of bleeding episodes, bleeding times and bleeding areas. Proof-of-principle was achieved when the camera captured the blood stream after infusion of rat whole blood into saline. Suitability was assessed by recording of bleeding profiles in heparin-treated rats, demonstrating that the system was able to capture on/off bleedings and that the data transfer and analysis were conducted successfully. Then, bleeding profiles were visually recorded by two independent observers simultaneously with the automated recordings after tail transection in untreated rats. Linear relationships were found in the number of bleedings, demonstrating, however, a statistically significant difference in the recording of bleeding episodes between observers. Also, the bleeding time was longer for visual compared to automated recording. No correlation was found between blood loss and bleeding time in untreated rats, but in heparinized rats a correlation was suggested. Finally, the blood loss correlated with the automated recording of bleeding area. In conclusion, the automated system has proven suitable for replacing visual recordings of tail bleedings in rats. Inter-observer differences can be eliminated, monotonous repetitive work avoided, and a higher through-put of animals in less time achieved. The automated system will lead to an increased understanding of the nature of bleeding following tail transection in different rodent models.

Delivery of Patient-Reported Outcome Instruments by Automated Mobile Phone Text Messaging.

PubMed

Anthony, Christopher A; Lawler, Ericka A; Glass, Natalie A; McDonald, Katelyn; Shah, Apurva S

2017-11-01

Patient-reported outcome (PRO) instruments allow patients to interpret their health and are integral in evaluating orthopedic treatments and outcomes. The purpose of this study was to define: (1) correlation between PROs collected by automated delivery of text messages on mobile phones compared with paper delivery; and (2) patient use characteristics of a technology platform utilizing automated delivery of text messages on mobile phones. Paper versions of the 12-Item Short Form Health Survey (SF-12) and the short form of the Disabilities of the Arm, Shoulder and Hand (QuickDASH) were completed by patients in orthopedic hand and upper extremity clinics. Over the next 48 hours, the same patients also completed the mobile phone portion of the study outside of the clinic which included text message delivery of the SF-12 and QuickDASH, assigned in a random order. Correlations between paper and text message delivery of the 2 PROs were assessed. Among 72 patients, the intraclass correlation coefficient (ICC) between the written and mobile phone delivery of QuickDASH was 0.91 (95% confidence interval [CI], 0.85-0.95). The ICC between the paper and mobile phone delivery of the SF-12 physical health composite score was 0.88 (95% CI, 0.79-0.93) and 0.86 (95% CI, 0.75-0.92) for the SF-12 mental health composite score. We find that text message delivery using mobile phones permits valid assessment of SF-12 and QuickDASH scores. The findings suggest that software-driven automated delivery of text communication to patients via mobile phones may be a valid method to obtain other PRO scores in orthopedic patients.

Feasibility and Utility of Lexical Analysis for Occupational Health Text.

PubMed

Harber, Philip; Leroy, Gondy

2017-06-01

Assess feasibility and potential utility of natural language processing (NLP) for storing and analyzing occupational health data. Basic NLP lexical analysis methods were applied to 89,000 Mine Safety and Health Administration (MSHA) free text records. Steps included tokenization, term and co-occurrence counts, term annotation, and identifying exposure-health effect relationships. Presence of terms in the Unified Medical Language System (UMLS) was assessed. The methods efficiently demonstrated common exposures, health effects, and exposure-injury relationships. Many workplace terms are not present in UMLS or map inaccurately. Use of free text rather than narrowly defined numerically coded fields is feasible, flexible, and efficient. It has potential to encourage workers and clinicians to provide more data and to support automated knowledge creation. The lexical method used is easily generalizable to other areas. The UMLS vocabularies should be enhanced to be relevant to occupational health.

Automated document analysis system

NASA Astrophysics Data System (ADS)

Black, Jeffrey D.; Dietzel, Robert; Hartnett, David

2002-08-01

A software application has been developed to aid law enforcement and government intelligence gathering organizations in the translation and analysis of foreign language documents with potential intelligence content. The Automated Document Analysis System (ADAS) provides the capability to search (data or text mine) documents in English and the most commonly encountered foreign languages, including Arabic. Hardcopy documents are scanned by a high-speed scanner and are optical character recognized (OCR). Documents obtained in an electronic format bypass the OCR and are copied directly to a working directory. For translation and analysis, the script and the language of the documents are first determined. If the document is not in English, the document is machine translated to English. The documents are searched for keywords and key features in either the native language or translated English. The user can quickly review the document to determine if it has any intelligence content and whether detailed, verbatim human translation is required. The documents and document content are cataloged for potential future analysis. The system allows non-linguists to evaluate foreign language documents and allows for the quick analysis of a large quantity of documents. All document processing can be performed manually or automatically on a single document or a batch of documents.

Reproducibility of Automated Voice Range Profiles, a Systematic Literature Review.

PubMed

Printz, Trine; Rosenberg, Tine; Godballe, Christian; Dyrvig, Anne-Kirstine; Grøntved, Ågot Møller

2018-05-01

Reliable voice range profiles are of great importance when measuring effects and side effects from surgery affecting voice capacity. Automated recording systems are increasingly used, but the reproducibility of results is uncertain. Our objective was to identify and review the existing literature on test-retest accuracy of the automated voice range profile assessment. Systematic review. PubMed, Scopus, Cochrane Library, ComDisDome, Embase, and CINAHL (EBSCO). We conducted a systematic literature search of six databases from 1983 to 2016. The following keywords were used: phonetogram, voice range profile, and acoustic voice analysis. Inclusion criteria were automated recording procedure, healthy voices, and no intervention between test and retest. Test-retest values concerning fundamental frequency and voice intensity were reviewed. Of 483 abstracts, 231 full-text articles were read, resulting in six articles included in the final results. The studies found high reliability, but data are few and heterogeneous. The reviewed articles generally reported high reliability of the voice range profile, and thus clinical usefulness, but uncertainty remains because of low sample sizes and different procedures for selecting, collecting, and analyzing data. More data are needed, and clinical conclusions must be drawn with caution. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Evaluating Fault Management Operations Concepts for Next-Generation Spacecraft: What Eye Movements Tell Us

NASA Technical Reports Server (NTRS)

Hayashi, Miwa; Ravinder, Ujwala; McCann, Robert S.; Beutter, Brent; Spirkovska, Lily

2009-01-01

Performance enhancements associated with selected forms of automation were quantified in a recent human-in-the-loop evaluation of two candidate operational concepts for fault management on next-generation spacecraft. The baseline concept, called Elsie, featured a full-suite of "soft" fault management interfaces. However, operators were forced to diagnose malfunctions with minimal assistance from the standalone caution and warning system. The other concept, called Besi, incorporated a more capable C&W system with an automated fault diagnosis capability. Results from analyses of participants' eye movements indicate that the greatest empirical benefit of the automation stemmed from eliminating the need for text processing on cluttered, text-rich displays.

The Effect of Information Analysis Automation Display Content on Human Judgment Performance in Noisy Environments

PubMed Central

Bass, Ellen J.; Baumgart, Leigh A.; Shepley, Kathryn Klein

2014-01-01

Displaying both the strategy that information analysis automation employs to makes its judgments and variability in the task environment may improve human judgment performance, especially in cases where this variability impacts the judgment performance of the information analysis automation. This work investigated the contribution of providing either information analysis automation strategy information, task environment information, or both, on human judgment performance in a domain where noisy sensor data are used by both the human and the information analysis automation to make judgments. In a simplified air traffic conflict prediction experiment, 32 participants made probability of horizontal conflict judgments under different display content conditions. After being exposed to the information analysis automation, judgment achievement significantly improved for all participants as compared to judgments without any of the automation's information. Participants provided with additional display content pertaining to cue variability in the task environment had significantly higher aided judgment achievement compared to those provided with only the automation's judgment of a probability of conflict. When designing information analysis automation for environments where the automation's judgment achievement is impacted by noisy environmental data, it may be beneficial to show additional task environment information to the human judge in order to improve judgment performance. PMID:24847184

Using machine learning to disentangle homonyms in large text corpora.

PubMed

Roll, Uri; Correia, Ricardo A; Berger-Tal, Oded

2018-06-01

Systematic reviews are an increasingly popular decision-making tool that provides an unbiased summary of evidence to support conservation action. These reviews bridge the gap between researchers and managers by presenting a comprehensive overview of all studies relating to a particular topic and identify specifically where and under which conditions an effect is present. However, several technical challenges can severely hinder the feasibility and applicability of systematic reviews, for example, homonyms (terms that share spelling but differ in meaning). Homonyms add noise to search results and cannot be easily identified or removed. We developed a semiautomated approach that can aid in the classification of homonyms among narratives. We used a combination of automated content analysis and artificial neural networks to quickly and accurately sift through large corpora of academic texts and classify them to distinct topics. As an example, we explored the use of the word reintroduction in academic texts. Reintroduction is used within the conservation context to indicate the release of organisms to their former native habitat; however, a Web of Science search for this word returned thousands of publications in which the term has other meanings and contexts. Using our method, we automatically classified a sample of 3000 of these publications with over 99% accuracy, relative to a manual classification. Our approach can be used easily with other homonyms and can greatly facilitate systematic reviews or similar work in which homonyms hinder the harnessing of large text corpora. Beyond homonyms we see great promise in combining automated content analysis and machine-learning methods to handle and screen big data for relevant information in conservation science. © 2017 Society for Conservation Biology.

Information Extraction for System-Software Safety Analysis: Calendar Year 2008 Year-End Report

NASA Technical Reports Server (NTRS)

Malin, Jane T.

2009-01-01

This annual report describes work to integrate a set of tools to support early model-based analysis of failures and hazards due to system-software interactions. The tools perform and assist analysts in the following tasks: 1) extract model parts from text for architecture and safety/hazard models; 2) combine the parts with library information to develop the models for visualization and analysis; 3) perform graph analysis and simulation to identify and evaluate possible paths from hazard sources to vulnerable entities and functions, in nominal and anomalous system-software configurations and scenarios; and 4) identify resulting candidate scenarios for software integration testing. There has been significant technical progress in model extraction from Orion program text sources, architecture model derivation (components and connections) and documentation of extraction sources. Models have been derived from Internal Interface Requirements Documents (IIRDs) and FMEA documents. Linguistic text processing is used to extract model parts and relationships, and the Aerospace Ontology also aids automated model development from the extracted information. Visualizations of these models assist analysts in requirements overview and in checking consistency and completeness.

Towards an automated intelligence product generation capability

NASA Astrophysics Data System (ADS)

Smith, Alison M.; Hawes, Timothy W.; Nolan, James J.

2015-05-01

Creating intelligence information products is a time consuming and difficult process for analysts faced with identifying key pieces of information relevant to a complex set of information requirements. Complicating matters, these key pieces of information exist in multiple modalities scattered across data stores, buried in huge volumes of data. This results in the current predicament analysts find themselves; information retrieval and management consumes huge amounts of time that could be better spent performing analysis. The persistent growth in data accumulation rates will only increase the amount of time spent on these tasks without a significant advance in automated solutions for information product generation. We present a product generation tool, Automated PrOduct Generation and Enrichment (APOGEE), which aims to automate the information product creation process in order to shift the bulk of the analysts' effort from data discovery and management to analysis. APOGEE discovers relevant text, imagery, video, and audio for inclusion in information products using semantic and statistical models of unstructured content. APOGEEs mixed-initiative interface, supported by highly responsive backend mechanisms, allows analysts to dynamically control the product generation process ensuring a maximally relevant result. The combination of these capabilities results in significant reductions in the time it takes analysts to produce information products while helping to increase the overall coverage. Through evaluation with a domain expert, APOGEE has been shown the potential to cut down the time for product generation by 20x. The result is a flexible end-to-end system that can be rapidly deployed in new operational settings.

Protocols for Automated Protist Analysis

DTIC Science & Technology

2011-12-01

Report No: CG-D-14-13 Protocols for Automated Protist Analysis December 2011 Distribution Statement A: Approved for public...release; distribution is unlimited. Protocols for Automated Protist Analysis ii UNCLAS//Public | CG-926 RDC | B. Nelson, et al. | Public...Director United States Coast Guard Research & Development Center 1 Chelsea Street New London, CT 06320 Protocols for Automated Protist Analysis

USSR Report: Cybernetics, Computers and Automation Technology. No. 69.

DTIC Science & Technology

1983-05-06

computers in multiprocessor and multistation design , control and scientific research automation systems. The results of comparing the efficiency of...Podvizhnaya, Scientific Research Institute of Control Computers, Severodonetsk] [Text] The most significant change in the design of the SM-2M compared to...UPRAVLYAYUSHCHIYE SISTEMY I MASHINY, Nov-Dec 82) 95 APPLICATIONS Kiev Automated Control System, Design Features and Prospects for Development (V. A

A system for classifying disease comorbidity status from medical discharge summaries using automated hotspot and negated concept detection.

PubMed

Ambert, Kyle H; Cohen, Aaron M

2009-01-01

OBJECTIVE Free-text clinical reports serve as an important part of patient care management and clinical documentation of patient disease and treatment status. Free-text notes are commonplace in medical practice, but remain an under-used source of information for clinical and epidemiological research, as well as personalized medicine. The authors explore the challenges associated with automatically extracting information from clinical reports using their submission to the Integrating Informatics with Biology and the Bedside (i2b2) 2008 Natural Language Processing Obesity Challenge Task. DESIGN A text mining system for classifying patient comorbidity status, based on the information contained in clinical reports. The approach of the authors incorporates a variety of automated techniques, including hot-spot filtering, negated concept identification, zero-vector filtering, weighting by inverse class-frequency, and error-correcting of output codes with linear support vector machines. MEASUREMENTS Performance was evaluated in terms of the macroaveraged F1 measure. RESULTS The automated system performed well against manual expert rule-based systems, finishing fifth in the Challenge's intuitive task, and 13(th) in the textual task. CONCLUSIONS The system demonstrates that effective comorbidity status classification by an automated system is possible.

mActive: A Randomized Clinical Trial of an Automated mHealth Intervention for Physical Activity Promotion.

PubMed

Martin, Seth S; Feldman, David I; Blumenthal, Roger S; Jones, Steven R; Post, Wendy S; McKibben, Rebeccah A; Michos, Erin D; Ndumele, Chiadi E; Ratchford, Elizabeth V; Coresh, Josef; Blaha, Michael J

2015-11-09

We hypothesized that a fully automated mobile health (mHealth) intervention with tracking and texting components would increase physical activity. mActive enrolled smartphone users aged 18 to 69 years at an ambulatory cardiology center in Baltimore, Maryland. We used sequential randomization to evaluate the intervention's 2 core components. After establishing baseline activity during a blinded run-in (week 1), in phase I (weeks 2 to 3), we randomized 2:1 to unblinded versus blinded tracking. Unblinding allowed continuous access to activity data through a smartphone interface. In phase II (weeks 4 to 5), we randomized unblinded participants 1:1 to smart texts versus no texts. Smart texts provided smartphone-delivered coaching 3 times/day aimed at individual encouragement and fostering feedback loops by a fully automated, physician-written, theory-based algorithm using real-time activity data and 16 personal factors with a 10 000 steps/day goal. Forty-eight outpatients (46% women, 21% nonwhite) enrolled with a mean±SD age of 58±8 years, body mass index of 31±6 kg/m(2), and baseline activity of 9670±4350 steps/day. Daily activity data capture was 97.4%. The phase I change in activity was nonsignificantly higher in unblinded participants versus blinded controls by 1024 daily steps (95% confidence interval [CI], -580 to 2628; P=0.21). In phase II, participants receiving texts increased their daily steps over those not receiving texts by 2534 (95% CI, 1318 to 3750; P<0.001) and over blinded controls by 3376 (95% CI, 1951 to 4801; P<0.001). An automated tracking-texting intervention increased physical activity with, but not without, the texting component. These results support new mHealth tracking technologies as facilitators in need of behavior change drivers. URL: http://ClinicalTrials.gov/. Unique identifier: NCT01917812. © 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

The software for automatic creation of the formal grammars used by speech recognition, computer vision, editable text conversion systems, and some new functions

NASA Astrophysics Data System (ADS)

Kardava, Irakli; Tadyszak, Krzysztof; Gulua, Nana; Jurga, Stefan

2017-02-01

For more flexibility of environmental perception by artificial intelligence it is needed to exist the supporting software modules, which will be able to automate the creation of specific language syntax and to make a further analysis for relevant decisions based on semantic functions. According of our proposed approach, of which implementation it is possible to create the couples of formal rules of given sentences (in case of natural languages) or statements (in case of special languages) by helping of computer vision, speech recognition or editable text conversion system for further automatic improvement. In other words, we have developed an approach, by which it can be achieved to significantly improve the training process automation of artificial intelligence, which as a result will give us a higher level of self-developing skills independently from us (from users). At the base of our approach we have developed a software demo version, which includes the algorithm and software code for the entire above mentioned component's implementation (computer vision, speech recognition and editable text conversion system). The program has the ability to work in a multi - stream mode and simultaneously create a syntax based on receiving information from several sources.

Automated Protist Analysis of Complex Samples: Recent Investigations Using Motion and Thresholding

DTIC Science & Technology

2012-01-01

Report No: CG-D-15-13 Automated Protist Analysis of Complex Samples: Recent Investigations Using Motion and Thresholding...Distribution Statement A: Approved for public release; distribution is unlimited. January 2012 Automated Protist Analysis of Complex Samples...Chelsea Street New London, CT 06320 Automated Protist Analysis of Complex Samples iii UNCLAS//PUBLIC | CG-926 R&DC | B. Nelson, et al

An Automated Quiet Sleep Detection Approach in Preterm Infants as a Gateway to Assess Brain Maturation.

PubMed

Dereymaeker, Anneleen; Pillay, Kirubin; Vervisch, Jan; Van Huffel, Sabine; Naulaers, Gunnar; Jansen, Katrien; De Vos, Maarten

2017-09-01

Sleep state development in preterm neonates can provide crucial information regarding functional brain maturation and give insight into neurological well being. However, visual labeling of sleep stages from EEG requires expertise and is very time consuming, prompting the need for an automated procedure. We present a robust method for automated detection of preterm sleep from EEG, over a wide postmenstrual age ([Formula: see text] age) range, focusing first on Quiet Sleep (QS) as an initial marker for sleep assessment. Our algorithm, CLuster-based Adaptive Sleep Staging (CLASS), detects QS if it remains relatively more discontinuous than non-QS over PMA. CLASS was optimized on a training set of 34 recordings aged 27-42 weeks PMA, and performance then assessed on a distinct test set of 55 recordings of the same age range. Results were compared to visual QS labeling from two independent raters (with inter-rater agreement [Formula: see text]), using Sensitivity, Specificity, Detection Factor ([Formula: see text] of visual QS periods correctly detected by CLASS) and Misclassification Factor ([Formula: see text] of CLASS-detected QS periods that are misclassified). CLASS performance proved optimal across recordings at 31-38 weeks (median [Formula: see text], median MF 0-0.25, median Sensitivity 0.93-1.0, and median Specificity 0.80-0.91 across this age range), with minimal misclassifications at 35-36 weeks (median [Formula: see text]). To illustrate the potential of CLASS in facilitating clinical research, normal maturational trends over PMA were derived from CLASS-estimated QS periods, visual QS estimates, and nonstate specific periods (containing QS and non-QS) in the EEG recording. CLASS QS trends agreed with those from visual QS, with both showing stronger correlations than nonstate specific trends. This highlights the benefit of automated QS detection for exploring brain maturation.

Automating Content Analysis of Open-Ended Responses: Wordscores and Affective Intonation

PubMed Central

Baek, Young Min; Cappella, Joseph N.; Bindman, Alyssa

2014-01-01

This study presents automated methods for predicting valence and quantifying valenced thoughts of a text. First, it examines whether Wordscores, developed by Laver, Benoit, and Garry (2003), can be adapted to reliably predict the valence of open-ended responses in a survey about bioethical issues in genetics research, and then tests a complementary and novel technique for coding the number of valenced thoughts in open-ended responses, termed Affective Intonation. Results show that Wordscores successfully predicts the valence of brief and grammatically imperfect open-ended responses, and Affective Intonation achieves comparable performance to human coders when estimating number of valenced thoughts. Both Wordscores and Affective Intonation have promise as reliable, effective, and efficient methods when researchers content-analyze large amounts of textual data systematically. PMID:25558294

Spotlight-8 Image Analysis Software

NASA Technical Reports Server (NTRS)

Klimek, Robert; Wright, Ted

2006-01-01

Spotlight is a cross-platform GUI-based software package designed to perform image analysis on sequences of images generated by combustion and fluid physics experiments run in a microgravity environment. Spotlight can perform analysis on a single image in an interactive mode or perform analysis on a sequence of images in an automated fashion. Image processing operations can be employed to enhance the image before various statistics and measurement operations are performed. An arbitrarily large number of objects can be analyzed simultaneously with independent areas of interest. Spotlight saves results in a text file that can be imported into other programs for graphing or further analysis. Spotlight can be run on Microsoft Windows, Linux, and Apple OS X platforms.

BoB, a best-of-breed automated text de-identification system for VHA clinical documents.

PubMed

Ferrández, Oscar; South, Brett R; Shen, Shuying; Friedlin, F Jeffrey; Samore, Matthew H; Meystre, Stéphane M

2013-01-01

De-identification allows faster and more collaborative clinical research while protecting patient confidentiality. Clinical narrative de-identification is a tedious process that can be alleviated by automated natural language processing methods. The goal of this research is the development of an automated text de-identification system for Veterans Health Administration (VHA) clinical documents. We devised a novel stepwise hybrid approach designed to improve the current strategies used for text de-identification. The proposed system is based on a previous study on the best de-identification methods for VHA documents. This best-of-breed automated clinical text de-identification system (aka BoB) tackles the problem as two separate tasks: (1) maximize patient confidentiality by redacting as much protected health information (PHI) as possible; and (2) leave de-identified documents in a usable state preserving as much clinical information as possible. We evaluated BoB with a manually annotated corpus of a variety of VHA clinical notes, as well as with the 2006 i2b2 de-identification challenge corpus. We present evaluations at the instance- and token-level, with detailed results for BoB's main components. Moreover, an existing text de-identification system was also included in our evaluation. BoB's design efficiently takes advantage of the methods implemented in its pipeline, resulting in high sensitivity values (especially for sensitive PHI categories) and a limited number of false positives. Our system successfully addressed VHA clinical document de-identification, and its hybrid stepwise design demonstrates robustness and efficiency, prioritizing patient confidentiality while leaving most clinical information intact.

Biblio-MetReS: A bibliometric network reconstruction application and server

PubMed Central

2011-01-01

Background Reconstruction of genes and/or protein networks from automated analysis of the literature is one of the current targets of text mining in biomedical research. Some user-friendly tools already perform this analysis on precompiled databases of abstracts of scientific papers. Other tools allow expert users to elaborate and analyze the full content of a corpus of scientific documents. However, to our knowledge, no user friendly tool that simultaneously analyzes the latest set of scientific documents available on line and reconstructs the set of genes referenced in those documents is available. Results This article presents such a tool, Biblio-MetReS, and compares its functioning and results to those of other user-friendly applications (iHOP, STRING) that are widely used. Under similar conditions, Biblio-MetReS creates networks that are comparable to those of other user friendly tools. Furthermore, analysis of full text documents provides more complete reconstructions than those that result from using only the abstract of the document. Conclusions Literature-based automated network reconstruction is still far from providing complete reconstructions of molecular networks. However, its value as an auxiliary tool is high and it will increase as standards for reporting biological entities and relationships become more widely accepted and enforced. Biblio-MetReS is an application that can be downloaded from http://metres.udl.cat/. It provides an easy to use environment for researchers to reconstruct their networks of interest from an always up to date set of scientific documents. PMID:21975133

Automated Diagnosis Coding with Combined Text Representations.

PubMed

Berndorfer, Stefan; Henriksson, Aron

2017-01-01

Automated diagnosis coding can be provided efficiently by learning predictive models from historical data; however, discriminating between thousands of codes while allowing a variable number of codes to be assigned is extremely difficult. Here, we explore various text representations and classification models for assigning ICD-9 codes to discharge summaries in MIMIC-III. It is shown that the relative effectiveness of the investigated representations depends on the frequency of the diagnosis code under consideration and that the best performance is obtained by combining models built using different representations.

ParamAP: Standardized Parameterization of Sinoatrial Node Myocyte Action Potentials.

PubMed

Rickert, Christian; Proenza, Catherine

2017-08-22

Sinoatrial node myocytes act as cardiac pacemaker cells by generating spontaneous action potentials (APs). Much information is encoded in sinoatrial AP waveforms, but both the analysis and the comparison of AP parameters between studies is hindered by the lack of standardized parameter definitions and the absence of automated analysis tools. Here we introduce ParamAP, a standalone cross-platform computational tool that uses a template-free detection algorithm to automatically identify and parameterize APs from text input files. ParamAP employs a graphic user interface with automatic and user-customizable input modes, and it outputs data files in text and PDF formats. ParamAP returns a total of 16 AP waveform parameters including time intervals such as the AP duration, membrane potentials such as the maximum diastolic potential, and rates of change of the membrane potential such as the diastolic depolarization rate. ParamAP provides a robust AP detection algorithm in combination with a standardized AP parameter analysis over a wide range of AP waveforms and firing rates, owing in part to the use of an iterative algorithm for the determination of the threshold potential and the diastolic depolarization rate that is independent of the maximum upstroke velocity, a parameter that can vary significantly among sinoatrial APs. Because ParamAP is implemented in Python 3, it is also highly customizable and extensible. In conclusion, ParamAP is a powerful computational tool that facilitates quantitative analysis and enables comparison of sinoatrial APs by standardizing parameter definitions and providing an automated work flow. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

DeTEXT: A Database for Evaluating Text Extraction from Biomedical Literature Figures

PubMed Central

Yin, Xu-Cheng; Yang, Chun; Pei, Wei-Yi; Man, Haixia; Zhang, Jun; Learned-Miller, Erik; Yu, Hong

2015-01-01

Hundreds of millions of figures are available in biomedical literature, representing important biomedical experimental evidence. Since text is a rich source of information in figures, automatically extracting such text may assist in the task of mining figure information. A high-quality ground truth standard can greatly facilitate the development of an automated system. This article describes DeTEXT: A database for evaluating text extraction from biomedical literature figures. It is the first publicly available, human-annotated, high quality, and large-scale figure-text dataset with 288 full-text articles, 500 biomedical figures, and 9308 text regions. This article describes how figures were selected from open-access full-text biomedical articles and how annotation guidelines and annotation tools were developed. We also discuss the inter-annotator agreement and the reliability of the annotations. We summarize the statistics of the DeTEXT data and make available evaluation protocols for DeTEXT. Finally we lay out challenges we observed in the automated detection and recognition of figure text and discuss research directions in this area. DeTEXT is publicly available for downloading at http://prir.ustb.edu.cn/DeTEXT/. PMID:25951377

Development and Testing of an Automated 4-Day Text Messaging Guidance as an Aid for Improving Colonoscopy Preparation.

PubMed

Walter, Benjamin Michael; Klare, Peter; Neu, Bruno; Schmid, Roland M; von Delius, Stefan

2016-06-21

In gastroenterology a sufficient colon cleansing improves adenoma detection rate and prevents the need for preterm repeat colonoscopies due to invalid preparation. It has been shown that patient education is of major importance for improvement of colon cleansing. Objective of this study was to assess the function of an automated text messaging (short message service, SMS)-supported colonoscopy preparation starting 4 days before colonoscopy appointment. After preevaluation to assess mobile phone usage in the patient population for relevance of this approach, a Web-based, automated SMS text messaging system was developed, following which a single-center feasibility study at a tertiary care center was performed. Patients scheduled for outpatient colonoscopy were invited to participate. Patients enrolled in the study group received automated information about dietary recommendations and bowel cleansing during colonoscopy preparation. Data of outpatient colonoscopies with regular preparation procedure were used for pair matching and served as control. Primary end point was feasibility of SMS text messaging support in colonoscopy preparation assessed as stable and satisfactory function of the system. Secondary end points were quality of bowel preparation according to the Boston Bowel Preparation Scale (BBPS) and patient satisfaction with SMS text messaging-provided information assessed by a questionnaire. Web-based SMS text messaging-supported colonoscopy preparation was successful and feasible in 19 of 20 patients. Mean (standard error of the mean, SEM) total BBPS score was slightly higher in the SMS group than in the control group (7.3, SEM 0.3 vs 6.4, SEM 0.2) and for each colonic region (left, transverse, and right colon). Patient satisfaction regarding SMS text messaging-based information was high. Using SMS for colonoscopy preparation with 4 days' guidance including dietary recommendation is a new approach to improve colonoscopy preparation. Quality of colonoscopy preparation was sufficient and patients were highly satisfied with the system during colonoscopy preparation.

Development and Testing of an Automated 4-Day Text Messaging Guidance as an Aid for Improving Colonoscopy Preparation

PubMed Central

Klare, Peter; Neu, Bruno; Schmid, Roland M; von Delius, Stefan

2016-01-01

Background In gastroenterology a sufficient colon cleansing improves adenoma detection rate and prevents the need for preterm repeat colonoscopies due to invalid preparation. It has been shown that patient education is of major importance for improvement of colon cleansing. Objective Objective of this study was to assess the function of an automated text messaging (short message service, SMS)–supported colonoscopy preparation starting 4 days before colonoscopy appointment. Methods After preevaluation to assess mobile phone usage in the patient population for relevance of this approach, a Web-based, automated SMS text messaging system was developed, following which a single-center feasibility study at a tertiary care center was performed. Patients scheduled for outpatient colonoscopy were invited to participate. Patients enrolled in the study group received automated information about dietary recommendations and bowel cleansing during colonoscopy preparation. Data of outpatient colonoscopies with regular preparation procedure were used for pair matching and served as control. Primary end point was feasibility of SMS text messaging support in colonoscopy preparation assessed as stable and satisfactory function of the system. Secondary end points were quality of bowel preparation according to the Boston Bowel Preparation Scale (BBPS) and patient satisfaction with SMS text messaging–provided information assessed by a questionnaire. Results Web-based SMS text messaging–supported colonoscopy preparation was successful and feasible in 19 of 20 patients. Mean (standard error of the mean, SEM) total BBPS score was slightly higher in the SMS group than in the control group (7.3, SEM 0.3 vs 6.4, SEM 0.2) and for each colonic region (left, transverse, and right colon). Patient satisfaction regarding SMS text messaging–based information was high. Conclusions Using SMS for colonoscopy preparation with 4 days’ guidance including dietary recommendation is a new approach to improve colonoscopy preparation. Quality of colonoscopy preparation was sufficient and patients were highly satisfied with the system during colonoscopy preparation. PMID:27329204

Automatically Detecting Failures in Natural Language Processing Tools for Online Community Text.

PubMed

Park, Albert; Hartzler, Andrea L; Huh, Jina; McDonald, David W; Pratt, Wanda

2015-08-31

The prevalence and value of patient-generated health text are increasing, but processing such text remains problematic. Although existing biomedical natural language processing (NLP) tools are appealing, most were developed to process clinician- or researcher-generated text, such as clinical notes or journal articles. In addition to being constructed for different types of text, other challenges of using existing NLP include constantly changing technologies, source vocabularies, and characteristics of text. These continuously evolving challenges warrant the need for applying low-cost systematic assessment. However, the primarily accepted evaluation method in NLP, manual annotation, requires tremendous effort and time. The primary objective of this study is to explore an alternative approach-using low-cost, automated methods to detect failures (eg, incorrect boundaries, missed terms, mismapped concepts) when processing patient-generated text with existing biomedical NLP tools. We first characterize common failures that NLP tools can make in processing online community text. We then demonstrate the feasibility of our automated approach in detecting these common failures using one of the most popular biomedical NLP tools, MetaMap. Using 9657 posts from an online cancer community, we explored our automated failure detection approach in two steps: (1) to characterize the failure types, we first manually reviewed MetaMap's commonly occurring failures, grouped the inaccurate mappings into failure types, and then identified causes of the failures through iterative rounds of manual review using open coding, and (2) to automatically detect these failure types, we then explored combinations of existing NLP techniques and dictionary-based matching for each failure cause. Finally, we manually evaluated the automatically detected failures. From our manual review, we characterized three types of failure: (1) boundary failures, (2) missed term failures, and (3) word ambiguity failures. Within these three failure types, we discovered 12 causes of inaccurate mappings of concepts. We used automated methods to detect almost half of 383,572 MetaMap's mappings as problematic. Word sense ambiguity failure was the most widely occurring, comprising 82.22% of failures. Boundary failure was the second most frequent, amounting to 15.90% of failures, while missed term failures were the least common, making up 1.88% of failures. The automated failure detection achieved precision, recall, accuracy, and F1 score of 83.00%, 92.57%, 88.17%, and 87.52%, respectively. We illustrate the challenges of processing patient-generated online health community text and characterize failures of NLP tools on this patient-generated health text, demonstrating the feasibility of our low-cost approach to automatically detect those failures. Our approach shows the potential for scalable and effective solutions to automatically assess the constantly evolving NLP tools and source vocabularies to process patient-generated text.

Automated analysis of short responses in an interactive synthetic tutoring system for introductory physics

NASA Astrophysics Data System (ADS)

Nakamura, Christopher M.; Murphy, Sytil K.; Christel, Michael G.; Stevens, Scott M.; Zollman, Dean A.

2016-06-01

Computer-automated assessment of students' text responses to short-answer questions represents an important enabling technology for online learning environments. We have investigated the use of machine learning to train computer models capable of automatically classifying short-answer responses and assessed the results. Our investigations are part of a project to develop and test an interactive learning environment designed to help students learn introductory physics concepts. The system is designed around an interactive video tutoring interface. We have analyzed 9 with about 150 responses or less. We observe for 4 of the 9 automated assessment with interrater agreement of 70% or better with the human rater. This level of agreement may represent a baseline for practical utility in instruction and indicates that the method warrants further investigation for use in this type of application. Our results also suggest strategies that may be useful for writing activities and questions that are more appropriate for automated assessment. These strategies include building activities that have relatively few conceptually distinct ways of perceiving the physical behavior of relatively few physical objects. Further success in this direction may allow us to promote interactivity and better provide feedback in online learning systems. These capabilities could enable our system to function more like a real tutor.

49 CFR 1104.2 - Document specifications.

Code of Federal Regulations, 2014 CFR

2014-10-01

... to facilitate automated processing in document sheet feeders, original documents of more than one... textual submissions. Use of color in filings is limited to images such as graphs, maps and photographs. To facilitate automated processing of color pages, color pages may not be inserted among pages containing text...

49 CFR 1104.2 - Document specifications.

Code of Federal Regulations, 2010 CFR

2010-10-01

... to facilitate automated processing in document sheet feeders, original documents of more than one... textual submissions. Use of color in filings is limited to images such as graphs, maps and photographs. To facilitate automated processing of color pages, color pages may not be inserted among pages containing text...

49 CFR 1104.2 - Document specifications.

Code of Federal Regulations, 2012 CFR

2012-10-01

... to facilitate automated processing in document sheet feeders, original documents of more than one... textual submissions. Use of color in filings is limited to images such as graphs, maps and photographs. To facilitate automated processing of color pages, color pages may not be inserted among pages containing text...

49 CFR 1104.2 - Document specifications.

Code of Federal Regulations, 2011 CFR

2011-10-01

... to facilitate automated processing in document sheet feeders, original documents of more than one... textual submissions. Use of color in filings is limited to images such as graphs, maps and photographs. To facilitate automated processing of color pages, color pages may not be inserted among pages containing text...

49 CFR 1104.2 - Document specifications.

Code of Federal Regulations, 2013 CFR

2013-10-01

... to facilitate automated processing in document sheet feeders, original documents of more than one... textual submissions. Use of color in filings is limited to images such as graphs, maps and photographs. To facilitate automated processing of color pages, color pages may not be inserted among pages containing text...

Implementation of a Flexible Tool for Automated Literature-Mining and Knowledgebase Development (DevToxMine)

EPA Science Inventory

Deriving novel relationships from the scientific literature is an important adjunct to datamining activities for complex datasets in genomics and high-throughput screening activities. Automated text-mining algorithms can be used to extract relevant content from the literature and...

Feasibility of Developing a Protocol for Automated Protist Analysis

DTIC Science & Technology

2010-03-01

Acquisition Directorate Research & Development Center Report No: CG-D-02-ll Feasibility of Developing a Protocol for Automated Protist Analysis...Technical Information Service, Springfield, VA 22161. March 2010 Homeland Security Feasibility of Developing a Protocol for Automated Protist ...March 21)10 Feasibility of Developing a Protocol for Automated Protist Analysis 00 00 o CM Technical Report Documentation Page 1. Report No CG-D

Feasibility of using a large Clinical Data Warehouse to automate the selection of diagnostic cohorts.

PubMed

Stephen, Reejis; Boxwala, Aziz; Gertman, Paul

2003-01-01

Data from Clinical Data Warehouses (CDWs) can be used for retrospective studies and for benchmarking. However, automated identification of cases from large datasets containing data items in free text fields is challenging. We developed an algorithm for categorizing pediatric patients presenting with respiratory distress into Bronchiolitis, Bacterial pneumonia and Asthma using clinical variables from a CDW. A feasibility study of this approach indicates that case selection may be automated.

The NLM Indexing Initiative's Medical Text Indexer.

PubMed

Aronson, Alan R; Mork, James G; Gay, Clifford W; Humphrey, Susanne M; Rogers, Willie J

2004-01-01

The Medical Text Indexer (MTI) is a program for producing MeSH indexing recommendations. It is the major product of NLM's Indexing Initiative and has been used in both semi-automated and fully automated indexing environments at the Library since mid 2002. We report here on an experiment conducted with MEDLINE indexers to evaluate MTI's performance and to generate ideas for its improvement as a tool for user-assisted indexing. We also discuss some filtering techniques developed to improve MTI's accuracy for use primarily in automatically producing the indexing for several abstracts collections.

Development of Automated Image Analysis Software for Suspended Marine Particle Classification

DTIC Science & Technology

2002-09-30

Development of Automated Image Analysis Software for Suspended Marine Particle Classification Scott Samson Center for Ocean Technology...and global water column. 1 OBJECTIVES The project’s objective is to develop automated image analysis software to reduce the effort and time

Precision and Disclosure in Text and Voice Interviews on Smartphones

PubMed Central

Antoun, Christopher; Ehlen, Patrick; Fail, Stefanie; Hupp, Andrew L.; Johnston, Michael; Vickers, Lucas; Yan, H. Yanna; Zhang, Chan

2015-01-01

As people increasingly communicate via asynchronous non-spoken modes on mobile devices, particularly text messaging (e.g., SMS), longstanding assumptions and practices of social measurement via telephone survey interviewing are being challenged. In the study reported here, 634 people who had agreed to participate in an interview on their iPhone were randomly assigned to answer 32 questions from US social surveys via text messaging or speech, administered either by a human interviewer or by an automated interviewing system. 10 interviewers from the University of Michigan Survey Research Center administered voice and text interviews; automated systems launched parallel text and voice interviews at the same time as the human interviews were launched. The key question was how the interview mode affected the quality of the response data, in particular the precision of numerical answers (how many were not rounded), variation in answers to multiple questions with the same response scale (differentiation), and disclosure of socially undesirable information. Texting led to higher quality data—fewer rounded numerical answers, more differentiated answers to a battery of questions, and more disclosure of sensitive information—than voice interviews, both with human and automated interviewers. Text respondents also reported a strong preference for future interviews by text. The findings suggest that people interviewed on mobile devices at a time and place that is convenient for them, even when they are multitasking, can give more trustworthy and accurate answers than those in more traditional spoken interviews. The findings also suggest that answers from text interviews, when aggregated across a sample, can tell a different story about a population than answers from voice interviews, potentially altering the policy implications from a survey. PMID:26060991

Precision and Disclosure in Text and Voice Interviews on Smartphones.

PubMed

Schober, Michael F; Conrad, Frederick G; Antoun, Christopher; Ehlen, Patrick; Fail, Stefanie; Hupp, Andrew L; Johnston, Michael; Vickers, Lucas; Yan, H Yanna; Zhang, Chan

2015-01-01

As people increasingly communicate via asynchronous non-spoken modes on mobile devices, particularly text messaging (e.g., SMS), longstanding assumptions and practices of social measurement via telephone survey interviewing are being challenged. In the study reported here, 634 people who had agreed to participate in an interview on their iPhone were randomly assigned to answer 32 questions from US social surveys via text messaging or speech, administered either by a human interviewer or by an automated interviewing system. 10 interviewers from the University of Michigan Survey Research Center administered voice and text interviews; automated systems launched parallel text and voice interviews at the same time as the human interviews were launched. The key question was how the interview mode affected the quality of the response data, in particular the precision of numerical answers (how many were not rounded), variation in answers to multiple questions with the same response scale (differentiation), and disclosure of socially undesirable information. Texting led to higher quality data-fewer rounded numerical answers, more differentiated answers to a battery of questions, and more disclosure of sensitive information-than voice interviews, both with human and automated interviewers. Text respondents also reported a strong preference for future interviews by text. The findings suggest that people interviewed on mobile devices at a time and place that is convenient for them, even when they are multitasking, can give more trustworthy and accurate answers than those in more traditional spoken interviews. The findings also suggest that answers from text interviews, when aggregated across a sample, can tell a different story about a population than answers from voice interviews, potentially altering the policy implications from a survey.

Prevalence of Heart Failure Signs and Symptoms in a Large Primary Care Population Identified Through the Use of Text and Data Mining of the Electronic Health Record

PubMed Central

Vijayakrishnan, Rajakrishnan; Steinhubl, Steven R.; Ng, Kenney; Sun, Jimeng; Byrd, Roy J.; Daar, Zahra; Williams, Brent A.; deFilippi, Christopher; Ebadollahi, Shahram; Stewart, Walter F.

2014-01-01

Background The electronic health record contains a tremendous amount of data that if appropriately detected can lead to earlier identification of disease states such as heart failure (HF). Using a novel text and data analytic tool we explored the longitudinal EHR of over 50,000 primary care patients to identify the documentation of the signs and symptoms of HF in the years preceding its diagnosis. Methods and Results Retrospective analysis consisting of 4,644 incident HF cases and 45,981 group-matched controls. Documentation of Framingham HF signs and symptoms within encounter notes were carried out using a previously validated natural language processing procedure. A total of 892,805 affirmed criteria were documented over an average observation period of 3.4 years. Among eventual HF cases, 85% had at least one criterion within a year prior to their HF diagnosis (as did 55% of controls). Substantial variability in the prevalence of individual signs and symptoms were found in both cases and controls. Conclusions HF signs and symptoms are frequently documented in a primary care population as identified through automated text and data mining of EHRs. Their frequent identification demonstrates the rich data available within EHRs that will allow for future work on automated criterion identification to help develop predictive models for HF. PMID:24709663

An Intelligent Automation Platform for Rapid Bioprocess Design.

PubMed

Wu, Tianyi; Zhou, Yuhong

2014-08-01

Bioprocess development is very labor intensive, requiring many experiments to characterize each unit operation in the process sequence to achieve product safety and process efficiency. Recent advances in microscale biochemical engineering have led to automated experimentation. A process design workflow is implemented sequentially in which (1) a liquid-handling system performs high-throughput wet lab experiments, (2) standalone analysis devices detect the data, and (3) specific software is used for data analysis and experiment design given the user's inputs. We report an intelligent automation platform that integrates these three activities to enhance the efficiency of such a workflow. A multiagent intelligent architecture has been developed incorporating agent communication to perform the tasks automatically. The key contribution of this work is the automation of data analysis and experiment design and also the ability to generate scripts to run the experiments automatically, allowing the elimination of human involvement. A first-generation prototype has been established and demonstrated through lysozyme precipitation process design. All procedures in the case study have been fully automated through an intelligent automation platform. The realization of automated data analysis and experiment design, and automated script programming for experimental procedures has the potential to increase lab productivity. © 2013 Society for Laboratory Automation and Screening.

Outpatient blood pressure monitoring using bi-directional text messaging.

PubMed

Anthony, Chris A; Polgreen, Linnea A; Chounramany, James; Foster, Eric D; Goerdt, Christopher J; Miller, Michelle L; Suneja, Manish; Segre, Alberto M; Carter, Barry L; Polgreen, Philip M

2015-05-01

To diagnose hypertension, multiple blood pressure (BP) measurements are recommended. We randomized patients into three groups: EMR-only (patients recorded BP measurements in an electronic medical record [EMR] web portal), EMR + reminders (patients were sent text message reminders to record their BP measurements in the EMR), and bi-directional text messaging (patients were sent a text message asking them to respond with their current BP). Subjects were asked to complete 14 measurements. Automated messages were sent to each patient in the bi-directional text messaging and EMR + reminder groups twice daily. Among 121 patients, those in the bi-directional text messaging group reported the full 14 measurements more often than both the EMR-only group (P < .001) and the EMR + reminders group (P = .038). Also, the EMR + reminders group outperformed the EMR-only group (P < .001). Bi-directional automated text messaging is an effective way to gather patient BP data. Text-message-based reminders alone are an effective way to encourage patients to record BP measurements. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Preparing Electronic Clinical Data for Quality Improvement and Comparative Effectiveness Research: The SCOAP CERTAIN Automation and Validation Project

PubMed Central

Devine, Emily Beth; Capurro, Daniel; van Eaton, Erik; Alfonso-Cristancho, Rafael; Devlin, Allison; Yanez, N. David; Yetisgen-Yildiz, Meliha; Flum, David R.; Tarczy-Hornoch, Peter

2013-01-01

Background: The field of clinical research informatics includes creation of clinical data repositories (CDRs) used to conduct quality improvement (QI) activities and comparative effectiveness research (CER). Ideally, CDR data are accurately and directly abstracted from disparate electronic health records (EHRs), across diverse health-systems. Objective: Investigators from Washington State’s Surgical Care Outcomes and Assessment Program (SCOAP) Comparative Effectiveness Research Translation Network (CERTAIN) are creating such a CDR. This manuscript describes the automation and validation methods used to create this digital infrastructure. Methods: SCOAP is a QI benchmarking initiative. Data are manually abstracted from EHRs and entered into a data management system. CERTAIN investigators are now deploying Caradigm’s Amalga™ tool to facilitate automated abstraction of data from multiple, disparate EHRs. Concordance is calculated to compare data automatically to manually abstracted. Performance measures are calculated between Amalga and each parent EHR. Validation takes place in repeated loops, with improvements made over time. When automated abstraction reaches the current benchmark for abstraction accuracy - 95% - itwill ‘go-live’ at each site. Progress to Date: A technical analysis was completed at 14 sites. Five sites are contributing; the remaining sites prioritized meeting Meaningful Use criteria. Participating sites are contributing 15–18 unique data feeds, totaling 13 surgical registry use cases. Common feeds are registration, laboratory, transcription/dictation, radiology, and medications. Approximately 50% of 1,320 designated data elements are being automatically abstracted—25% from structured data; 25% from text mining. Conclusion: In semi-automating data abstraction and conducting a rigorous validation, CERTAIN investigators will semi-automate data collection to conduct QI and CER, while advancing the Learning Healthcare System. PMID:25848565

Building-level analyses to prospectively detect influenza outbreaks in long-term care facilities: New York City, 2013-2014.

PubMed

Levin-Rector, Alison; Nivin, Beth; Yeung, Alice; Fine, Annie D; Greene, Sharon K

2015-08-01

Timely outbreak detection is necessary to successfully control influenza in long-term care facilities (LTCFs) and other institutions. To supplement nosocomial outbreak reports, calls from infection control staff, and active laboratory surveillance, the New York City (NYC) Department of Health and Mental Hygiene implemented an automated building-level analysis to proactively identify LTCFs with laboratory-confirmed influenza activity. Geocoded addresses of LTCFs in NYC were compared with geocoded residential addresses for all case-patients with laboratory-confirmed influenza reported through passive surveillance. An automated daily analysis used the geocoded building identification number, approximate text matching, and key-word searches to identify influenza in residents of LTCFs for review and follow-up by surveillance coordinators. Our aim was to determine whether the building analysis improved prospective outbreak detection during the 2013-2014 influenza season. Of 119 outbreaks identified in LTCFs, 109 (92%) were ever detected by the building analysis, and 55 (46%) were first detected by the building analysis. Of the 5,953 LTCF staff and residents who received antiviral prophylaxis during the 2013-2014 season, 929 (16%) were at LTCFs where outbreaks were initially detected by the building analysis. A novel building-level analysis improved influenza outbreak identification in LTCFs in NYC, prompting timely infection control measures. Copyright © 2015 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Strategies for rare-event detection: an approach for automated fetal cell detection in maternal blood.

PubMed Central

Oosterwijk, J C; Knepflé, C F; Mesker, W E; Vrolijk, H; Sloos, W C; Pattenier, H; Ravkin, I; van Ommen, G J; Kanhai, H H; Tanke, H J

1998-01-01

This article explores the feasibility of the use of automated microscopy and image analysis to detect the presence of rare fetal nucleated red blood cells (NRBCs) circulating in maternal blood. The rationales for enrichment and for automated image analysis for "rare-event" detection are reviewed. We also describe the application of automated image analysis to 42 maternal blood samples, using a protocol consisting of one-step enrichment followed by immunocytochemical staining for fetal hemoglobin (HbF) and FISH for X- and Y-chromosomal sequences. Automated image analysis consisted of multimode microscopy and subsequent visual evaluation of image memories containing the selected objects. The FISH results were compared with the results of conventional karyotyping of the chorionic villi. By use of manual screening, 43% of the slides were found to be positive (>=1 NRBC), with a mean number of 11 NRBCs (range 1-40). By automated microscopy, 52% were positive, with on average 17 NRBCs (range 1-111). There was a good correlation between both manual and automated screening, but the NRBC yield from automated image analysis was found to be superior to that from manual screening (P=.0443), particularly when the NRBC count was >15. Seven (64%) of 11 XY fetuses were correctly diagnosed by FISH analysis of automatically detected cells, and all discrepancies were restricted to the lower cell-count range. We believe that automated microscopy and image analysis reduce the screening workload, are more sensitive than manual evaluation, and can be used to detect rare HbF-containing NRBCs in maternal blood. PMID:9837832

Correlating mammographic and pathologic findings in clinical decision support using natural language processing and data mining methods.

PubMed

Patel, Tejal A; Puppala, Mamta; Ogunti, Richard O; Ensor, Joe E; He, Tiancheng; Shewale, Jitesh B; Ankerst, Donna P; Kaklamani, Virginia G; Rodriguez, Angel A; Wong, Stephen T C; Chang, Jenny C

2017-01-01

A key challenge to mining electronic health records for mammography research is the preponderance of unstructured narrative text, which strikingly limits usable output. The imaging characteristics of breast cancer subtypes have been described previously, but without standardization of parameters for data mining. The authors searched the enterprise-wide data warehouse at the Houston Methodist Hospital, the Methodist Environment for Translational Enhancement and Outcomes Research (METEOR), for patients with Breast Imaging Reporting and Data System (BI-RADS) category 5 mammogram readings performed between January 2006 and May 2015 and an available pathology report. The authors developed natural language processing (NLP) software algorithms to automatically extract mammographic and pathologic findings from free text mammogram and pathology reports. The correlation between mammographic imaging features and breast cancer subtype was analyzed using one-way analysis of variance and the Fisher exact test. The NLP algorithm was able to obtain key characteristics for 543 patients who met the inclusion criteria. Patients with estrogen receptor-positive tumors were more likely to have spiculated margins (P = .0008), and those with tumors that overexpressed human epidermal growth factor receptor 2 (HER2) were more likely to have heterogeneous and pleomorphic calcifications (P = .0078 and P = .0002, respectively). Mammographic imaging characteristics, obtained from an automated text search and the extraction of mammogram reports using NLP techniques, correlated with pathologic breast cancer subtype. The results of the current study validate previously reported trends assessed by manual data collection. Furthermore, NLP provides an automated means with which to scale up data extraction and analysis for clinical decision support. Cancer 2017;114-121. © 2016 American Cancer Society. © 2016 American Cancer Society.

Automated, computer-guided PASI measurements by digital image analysis versus conventional physicians' PASI calculations: study protocol for a comparative, single-centre, observational study.

PubMed

Fink, Christine; Uhlmann, Lorenz; Klose, Christina; Haenssle, Holger A

2018-05-17

Reliable and accurate assessment of severity in psoriasis is very important in order to meet indication criteria for initiation of systemic treatment or to evaluate treatment efficacy. The most acknowledged tool for measuring the extent of psoriatic skin changes is the Psoriasis Area and Severity Index (PASI). However, the calculation of PASI can be tedious and subjective and high intraobserver and interobserver variability is an important concern. Therefore, there is a great need for a standardised and objective method that guarantees a reproducible PASI calculation. Within this study we will investigate the precision and reproducibility of automated, computer-guided PASI measurements in comparison to trained physicians to address these limitations. Non-interventional analyses of PASI calculations by either physicians in a prospective versus retrospective setting or an automated computer-guided algorithm in 120 patients with plaque psoriasis. All retrospective PASI calculations by physicians or by the computer algorithm are based on total body digital images. The primary objective of this study is comparison of automated computer-guided PASI measurements by means of digital image analysis versus conventional, prospective or retrospective physicians' PASI assessments. Secondary endpoints include (1) the assessment of physicians' interobserver variance in PASI calculations, (2) the assessment of physicians' intraobserver variance in PASI assessments of the same patients' images after a time interval of at least 4 weeks, (3) the assessment of the deviation between physicians' prospective versus retrospective PASI calculations, and (4) the reproducibility of automated computer-guided PASI measurements by assessment of two sets of total body digital images of the same patients taken at one time point. Ethical approval was provided by the Ethics Committee of the Medical Faculty of the University of Heidelberg (ethics approval number S-379/2016). DRKS00011818; Results. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Machine-Aided Indexing of Technical Literature

ERIC Educational Resources Information Center

Klingbiel, Paul H.

1973-01-01

To index at the Defense Documentation Center (DDC), an automated system must choose single words or phrases rapidly and economically. Automation of DDC's indexing has been machine-aided from its inception. A machine-aided indexing system is described that indexes one million words of text per hour of CPU time. (22 references) (Author/SJ)

Progress in Fully Automated Abdominal CT Interpretation

PubMed Central

Summers, Ronald M.

2016-01-01

OBJECTIVE Automated analysis of abdominal CT has advanced markedly over just the last few years. Fully automated assessment of organs, lymph nodes, adipose tissue, muscle, bowel, spine, and tumors are some examples where tremendous progress has been made. Computer-aided detection of lesions has also improved dramatically. CONCLUSION This article reviews the progress and provides insights into what is in store in the near future for automated analysis for abdominal CT, ultimately leading to fully automated interpretation. PMID:27101207

Semi-automated and automated glioma grading using dynamic susceptibility-weighted contrast-enhanced perfusion MRI relative cerebral blood volume measurements.

PubMed

Friedman, S N; Bambrough, P J; Kotsarini, C; Khandanpour, N; Hoggard, N

2012-12-01

Despite the established role of MRI in the diagnosis of brain tumours, histopathological assessment remains the clinically used technique, especially for the glioma group. Relative cerebral blood volume (rCBV) is a dynamic susceptibility-weighted contrast-enhanced perfusion MRI parameter that has been shown to correlate to tumour grade, but assessment requires a specialist and is time consuming. We developed analysis software to determine glioma gradings from perfusion rCBV scans in a manner that is quick, easy and does not require a specialist operator. MRI perfusion data from 47 patients with different histopathological grades of glioma were analysed with custom-designed software. Semi-automated analysis was performed with a specialist and non-specialist operator separately determining the maximum rCBV value corresponding to the tumour. Automated histogram analysis was performed by calculating the mean, standard deviation, median, mode, skewness and kurtosis of rCBV values. All values were compared with the histopathologically assessed tumour grade. A strong correlation between specialist and non-specialist observer measurements was found. Significantly different values were obtained between tumour grades using both semi-automated and automated techniques, consistent with previous results. The raw (unnormalised) data single-pixel maximum rCBV semi-automated analysis value had the strongest correlation with glioma grade. Standard deviation of the raw data had the strongest correlation of the automated analysis. Semi-automated calculation of raw maximum rCBV value was the best indicator of tumour grade and does not require a specialist operator. Both semi-automated and automated MRI perfusion techniques provide viable non-invasive alternatives to biopsy for glioma tumour grading.

Automated toxicological screening reports of modified Agilent MSD Chemstation combined with Microsoft Visual Basic application programs.

PubMed

Choe, Sanggil; Kim, Suncheun; Choi, Hyeyoung; Choi, Hwakyoung; Chung, Heesun; Hwang, Bangyeon

2010-06-15

Agilent GC-MS MSD Chemstation offers automated library search report for toxicological screening using total ion chromatogram (TIC) and mass spectroscopy in normal mode. Numerous peaks appear in the chromatogram of biological specimen such as blood or urine and often large migrating peaks obscure small target peaks, in addition, any target peaks of low abundance regularly give wrong library search result or low matching score. As a result, retention time and mass spectrum of all the peaks in the chromatogram have to be checked to see if they are relevant. These repeated actions are very tedious and time-consuming to toxicologists. MSD Chemstation software operates using a number of macro files which give commands and instructions on how to work on and extract data from the chromatogram and spectroscopy. These macro files are developed by the own compiler of the software. All the original macro files can be modified and new macro files can be added to the original software by users. To get more accurate results with more convenient method and to save time for data analysis, we developed new macro files for reports generation and inserted new menus in the Enhanced Data Analysis program. Toxicological screening reports generated by these new macro files are in text mode or graphic mode and these reports can be generated with three different automated subtraction options. Text reports have Brief mode and Full mode and graphic reports have the option with or without mass spectrum mode. Matched mass spectrum and matching score for detected compounds are printed in reports by modified library searching modules. We have also developed an independent application program named DrugMan. This program manages drug groups, lists and parameters that are in use in MSD Chemstation. The incorporation of DrugMan with modified macro modules provides a powerful tool for toxicological screening and save a lot of valuable time on toxicological work. (c) 2010 Elsevier Ireland Ltd. All rights reserved.

Effects of automation of information-processing functions on teamwork.

PubMed

Wright, Melanie C; Kaber, David B

2005-01-01

We investigated the effects of automation as applied to different stages of information processing on team performance in a complex decision-making task. Forty teams of 2 individuals performed a simulated Theater Defense Task. Four automation conditions were simulated with computer assistance applied to realistic combinations of information acquisition, information analysis, and decision selection functions across two levels of task difficulty. Multiple measures of team effectiveness and team coordination were used. Results indicated different forms of automation have different effects on teamwork. Compared with a baseline condition, an increase in automation of information acquisition led to an increase in the ratio of information transferred to information requested; an increase in automation of information analysis resulted in higher team coordination ratings; and automation of decision selection led to better team effectiveness under low levels of task difficulty but at the cost of higher workload. The results support the use of early and intermediate forms of automation related to acquisition and analysis of information in the design of team tasks. Decision-making automation may provide benefits in more limited contexts. Applications of this research include the design and evaluation of automation in team environments.

Robust binarization of degraded document images using heuristics

NASA Astrophysics Data System (ADS)

Parker, Jon; Frieder, Ophir; Frieder, Gideon

2013-12-01

Historically significant documents are often discovered with defects that make them difficult to read and analyze. This fact is particularly troublesome if the defects prevent software from performing an automated analysis. Image enhancement methods are used to remove or minimize document defects, improve software performance, and generally make images more legible. We describe an automated, image enhancement method that is input page independent and requires no training data. The approach applies to color or greyscale images with hand written script, typewritten text, images, and mixtures thereof. We evaluated the image enhancement method against the test images provided by the 2011 Document Image Binarization Contest (DIBCO). Our method outperforms all 2011 DIBCO entrants in terms of average F1 measure - doing so with a significantly lower variance than top contest entrants. The capability of the proposed method is also illustrated using select images from a collection of historic documents stored at Yad Vashem Holocaust Memorial in Israel.

Words, concepts, or both: optimal indexing units for automated information retrieval.

PubMed Central

Hersh, W. R.; Hickam, D. H.; Leone, T. J.

1992-01-01

What is the best way to represent the content of documents in an information retrieval system? This study compares the retrieval effectiveness of five different methods for automated (machine-assigned) indexing using three test collections. The consistently best methods are those that use indexing based on the words that occur in the available text of each document. Methods used to map text into concepts from a controlled vocabulary showed no advantage over the word-based methods. This study also looked at an approach to relevance feedback which showed benefit for both word-based and concept-based methods. PMID:1482951

An Intelligent Automation Platform for Rapid Bioprocess Design

PubMed Central

Wu, Tianyi

2014-01-01

Bioprocess development is very labor intensive, requiring many experiments to characterize each unit operation in the process sequence to achieve product safety and process efficiency. Recent advances in microscale biochemical engineering have led to automated experimentation. A process design workflow is implemented sequentially in which (1) a liquid-handling system performs high-throughput wet lab experiments, (2) standalone analysis devices detect the data, and (3) specific software is used for data analysis and experiment design given the user’s inputs. We report an intelligent automation platform that integrates these three activities to enhance the efficiency of such a workflow. A multiagent intelligent architecture has been developed incorporating agent communication to perform the tasks automatically. The key contribution of this work is the automation of data analysis and experiment design and also the ability to generate scripts to run the experiments automatically, allowing the elimination of human involvement. A first-generation prototype has been established and demonstrated through lysozyme precipitation process design. All procedures in the case study have been fully automated through an intelligent automation platform. The realization of automated data analysis and experiment design, and automated script programming for experimental procedures has the potential to increase lab productivity. PMID:24088579

Aquarius's Instrument Science Data System (ISDS) Automated to Acquire, Process, Trend Data and Produce Radiometric System Assessment Reports

NASA Technical Reports Server (NTRS)

2008-01-01

The Aquarius Radiometer, a subsystem of the Aquarius Instrument required a data acquisition ground system to support calibration and radiometer performance assessment. To support calibration and compose performance assessments, we developed an automated system which uploaded raw data to a ftp server and saved raw and processed data to a database. This paper details the overall functionalities of the Aquarius Instrument Science Data System (ISDS) and the individual electrical ground support equipment (EGSE) which produced data files that were infused into the ISDS. Real time EGSEs include an ICDS Simulator, Calibration GSE, Labview controlled power supply, and a chamber data acquisition system. ICDS Simulator serves as a test conductor primary workstation, collecting radiometer housekeeping (HK) and science data and passing commands and HK telemetry collection request to the radiometer. Calibration GSE (Radiometer Active Test Source) provides source choice from multiple targets for the radiometer external calibration. Power Supply GSE, controlled by labview, provides real time voltage and current monitoring of the radiometer. And finally the chamber data acquisition system produces data reflecting chamber vacuum pressure, thermistor temperatures, AVG and watts. Each GSE system produce text based data files every two to six minutes and automatically copies the data files to the Central Archiver PC. The Archiver PC stores the data files, schedules automated uploads of these files to an external FTP server, and accepts request to copy all data files to the ISDS for offline data processing and analysis. Aquarius Radiometer ISDS contains PHP and MATLab programs to parse, process and save all data to a MySQL database. Analysis tools (MATLab programs) in the ISDS system are capable of displaying radiometer science, telemetry and auxiliary data in near real time as well as performing data analysis and producing automated performance assessment reports of the Aquarius Radiometer.

[Research applications in digital radiology. Big data and co].

PubMed

Müller, H; Hanbury, A

2016-02-01

Medical imaging produces increasingly complex images (e.g. thinner slices and higher resolution) with more protocols, so that image reading has also become much more complex. More information needs to be processed and usually the number of radiologists available for these tasks has not increased to the same extent. The objective of this article is to present current research results from projects on the use of image data for clinical decision support. An infrastructure that can allow large volumes of data to be accessed is presented. In this way the best performing tools can be identified without the medical data having to leave secure servers. The text presents the results of the VISCERAL and Khresmoi EU-funded projects, which allow the analysis of previous cases from institutional archives to support decision-making and for process automation. The results also represent a secure evaluation environment for medical image analysis. This allows the use of data extracted from past cases to solve information needs occurring when diagnosing new cases. The presented research prototypes allow direct extraction of knowledge from the visual data of the images and to use this for decision support or process automation. Real clinical use has not been tested but several subjective user tests showed the effectiveness and efficiency of the process. The future in radiology will clearly depend on better use of the important knowledge in clinical image archives to automate processes and aid decision-making via big data analysis. This can help concentrate the work of radiologists towards the most important parts of diagnostics.

Automated CD-SEM recipe creation technology for mass production using CAD data

NASA Astrophysics Data System (ADS)

Kawahara, Toshikazu; Yoshida, Masamichi; Tanaka, Masashi; Ido, Sanyu; Nakano, Hiroyuki; Adachi, Naokaka; Abe, Yuichi; Nagatomo, Wataru

2011-03-01

Critical Dimension Scanning Electron Microscope (CD-SEM) recipe creation needs sample preparation necessary for matching pattern registration, and recipe creation on CD-SEM using the sample, which hinders the reduction in test production cost and time in semiconductor manufacturing factories. From the perspective of cost reduction and improvement of the test production efficiency, automated CD-SEM recipe creation without the sample preparation and the manual operation has been important in the production lines. For the automated CD-SEM recipe creation, we have introduced RecipeDirector (RD) that enables the recipe creation by using Computer-Aided Design (CAD) data and text data that includes measurement information. We have developed a system that automatically creates the CAD data and the text data necessary for the recipe creation on RD; and, for the elimination of the manual operation, we have enhanced RD so that all measurement information can be specified in the text data. As a result, we have established an automated CD-SEM recipe creation system without the sample preparation and the manual operation. For the introduction of the CD-SEM recipe creation system using RD to the production lines, the accuracy of the pattern matching was an issue. The shape of design templates for the matching created from the CAD data was different from that of SEM images in vision. Thus, a development of robust pattern matching algorithm that considers the shape difference was needed. The addition of image processing of the templates for the matching and shape processing of the CAD patterns in the lower layer has enabled the robust pattern matching. This paper describes the automated CD-SEM recipe creation technology for the production lines without the sample preparation and the manual operation using RD applied in Sony Semiconductor Kyusyu Corporation Kumamoto Technology Center (SCK Corporation Kumamoto TEC).

Stakeholder Views of Nanosilver Linings: Macroethics Education and Automated Text Analysis Through Participatory Governance Role Play in a Workshop Format.

PubMed

Dempsey, Joshua; Stamets, Justin; Eggleson, Kathleen

2017-06-01

The Nanosilver Linings role play case offers participants first-person experience with interpersonal interaction in the context of the wicked problems of emerging technology macroethics. In the fictional scenario, diverse societal stakeholders convene at a town hall meeting to consider whether a nanotechnology-enabled food packaging industry should be offered incentives to establish an operation in their economically struggling Midwestern city. This original creative work was built with a combination of elements, selected for their established pedagogical efficacy (e.g. active learning, case-based learning) and as topical dimensions of the realistic scenario (e.g. nanosilver in food packaging, occupational safety and health). The product life cycle is used as a framework for integrated consideration of scientific, societal, and ethical issues. The Nanosilver Linings hypothetical case was delivered through the format of the 3-hour workshop Ethics when Biocomplexity meets Human Complexity, providing an immersive, holistic ethics learning experience for STEM graduate students. Through their participation in the Nanosilver Linings case and Ethics when Biocomplexity meets Human Complexity workshop, four cohorts of science and engineering doctoral students reported the achievement of specific learning objectives pertaining to a range of macroethics concepts and professional practices, including stakeholder perspectives, communication, human values, and ethical frameworks. Automated text analysis of workshop transcripts revealed differences in sentiment and in ethical framework (consequentialism/deontology) preference between societal stakeholder roles. These resources have been recognized as ethics education exemplars by the U.S. National Academy of Engineering .

Factors Associated with Use of Automated Smoking Cessation Interventions: Findings from the eQuit Study

ERIC Educational Resources Information Center

Balmford, James; Borland, Ron; Benda, Peter; Howard, Steve

2013-01-01

The aim was to better understand structural factors associated with uptake of automated tailored interventions for smoking cessation. In a prospective randomized controlled trial with interventions only offered, not mandated, participants were randomized based on the following: web-based expert system (QuitCoach); text messaging program (onQ);…

The Impact of Misspelled Words on Automated Computer Scoring: A Case Study of Scientific Explanations

ERIC Educational Resources Information Center

Ha, Minsu; Nehm, Ross H.

2016-01-01

Automated computerized scoring systems (ACSSs) are being increasingly used to analyze text in many educational settings. Nevertheless, the impact of misspelled words (MSW) on scoring accuracy remains to be investigated in many domains, particularly jargon-rich disciplines such as the life sciences. Empirical studies confirm that MSW are a…

Open-Source Tools for Enhancing Full-Text Searching of OPACs: Use of Koha, Greenstone and Fedora

ERIC Educational Resources Information Center

Anuradha, K. T.; Sivakaminathan, R.; Kumar, P. Arun

2011-01-01

Purpose: There are many library automation packages available as open-source software, comprising two modules: staff-client module and online public access catalogue (OPAC). Although the OPAC of these library automation packages provides advanced features of searching and retrieval of bibliographic records, none of them facilitate full-text…

High-Reproducibility and High-Accuracy Method for Automated Topic Classification

NASA Astrophysics Data System (ADS)

Lancichinetti, Andrea; Sirer, M. Irmak; Wang, Jane X.; Acuna, Daniel; Körding, Konrad; Amaral, Luís A. Nunes

2015-01-01

Much of human knowledge sits in large databases of unstructured text. Leveraging this knowledge requires algorithms that extract and record metadata on unstructured text documents. Assigning topics to documents will enable intelligent searching, statistical characterization, and meaningful classification. Latent Dirichlet allocation (LDA) is the state of the art in topic modeling. Here, we perform a systematic theoretical and numerical analysis that demonstrates that current optimization techniques for LDA often yield results that are not accurate in inferring the most suitable model parameters. Adapting approaches from community detection in networks, we propose a new algorithm that displays high reproducibility and high accuracy and also has high computational efficiency. We apply it to a large set of documents in the English Wikipedia and reveal its hierarchical structure.

Comparative Analysis.

DTIC Science & Technology

1987-11-01

differential qualita- tive (DQ) analysis, which solves the task, providing explanations suitable for use by design systems, automated diagnosis, intelligent...solves the task, providing explanations suitable for use by design systems, automated diagnosis, intelligent tutoring systems, and explanation based...comparative analysis as an important component; the explanation is used in many different ways. * One way method of automated design is the principlvd

Automation Framework for Flight Dynamics Products Generation

NASA Technical Reports Server (NTRS)

Wiegand, Robert E.; Esposito, Timothy C.; Watson, John S.; Jun, Linda; Shoan, Wendy; Matusow, Carla

2010-01-01

XFDS provides an easily adaptable automation platform. To date it has been used to support flight dynamics operations. It coordinates the execution of other applications such as Satellite TookKit, FreeFlyer, MATLAB, and Perl code. It provides a mechanism for passing messages among a collection of XFDS processes, and allows sending and receiving of GMSEC messages. A unified and consistent graphical user interface (GUI) is used for the various tools. Its automation configuration is stored in text files, and can be edited either directly or using the GUI.

Automation or De-automation

NASA Astrophysics Data System (ADS)

Gorlach, Igor; Wessel, Oliver

2008-09-01

In the global automotive industry, for decades, vehicle manufacturers have continually increased the level of automation of production systems in order to be competitive. However, there is a new trend to decrease the level of automation, especially in final car assembly, for reasons of economy and flexibility. In this research, the final car assembly lines at three production sites of Volkswagen are analysed in order to determine the best level of automation for each, in terms of manufacturing costs, productivity, quality and flexibility. The case study is based on the methodology proposed by the Fraunhofer Institute. The results of the analysis indicate that fully automated assembly systems are not necessarily the best option in terms of cost, productivity and quality combined, which is attributed to high complexity of final car assembly systems; some de-automation is therefore recommended. On the other hand, the analysis shows that low automation can result in poor product quality due to reasons related to plant location, such as inadequate workers' skills, motivation, etc. Hence, the automation strategy should be formulated on the basis of analysis of all relevant aspects of the manufacturing process, such as costs, quality, productivity and flexibility in relation to the local context. A more balanced combination of automated and manual assembly operations provides better utilisation of equipment, reduces production costs and improves throughput.

Traffic Analysis For Highway-To-Highway Interchanges On Automated Highway Systems, Congestion In Absence Of Dedicated Ramps

DOT National Transportation Integrated Search

1997-01-01

SPECIAL CONNECTOR RAMPS LINKING THE AUTOMATED LANES AT AUTOMATED HIGHWAY-TO-AUTOMATED HIGHWAY INTERCHANGES MAY BE NEEDED TO ENABLE CONTINUOUS AUTOMATED DRIVING BETWEEN TWO CROSSING HIGHWAYS. ALTHOUGH A TYPICAL CLOVERLEAF CONFIGURATION HAS ONLY TWO LE...

Robotics/Automated Systems Task Analysis and Description of Required Job Competencies Report. Task Analysis and Description of Required Job Competencies of Robotics/Automated Systems Technicians.

ERIC Educational Resources Information Center

Hull, Daniel M.; Lovett, James E.

This task analysis report for the Robotics/Automated Systems Technician (RAST) curriculum project first provides a RAST job description. It then discusses the task analysis, including the identification of tasks, the grouping of tasks according to major areas of specialty, and the comparison of the competencies to existing or new courses to…

Text de-identification for privacy protection: a study of its impact on clinical text information content.

PubMed

Meystre, Stéphane M; Ferrández, Óscar; Friedlin, F Jeffrey; South, Brett R; Shen, Shuying; Samore, Matthew H

2014-08-01

As more and more electronic clinical information is becoming easier to access for secondary uses such as clinical research, approaches that enable faster and more collaborative research while protecting patient privacy and confidentiality are becoming more important. Clinical text de-identification offers such advantages but is typically a tedious manual process. Automated Natural Language Processing (NLP) methods can alleviate this process, but their impact on subsequent uses of the automatically de-identified clinical narratives has only barely been investigated. In the context of a larger project to develop and investigate automated text de-identification for Veterans Health Administration (VHA) clinical notes, we studied the impact of automated text de-identification on clinical information in a stepwise manner. Our approach started with a high-level assessment of clinical notes informativeness and formatting, and ended with a detailed study of the overlap of select clinical information types and Protected Health Information (PHI). To investigate the informativeness (i.e., document type information, select clinical data types, and interpretation or conclusion) of VHA clinical notes, we used five different existing text de-identification systems. The informativeness was only minimally altered by these systems while formatting was only modified by one system. To examine the impact of de-identification on clinical information extraction, we compared counts of SNOMED-CT concepts found by an open source information extraction application in the original (i.e., not de-identified) version of a corpus of VHA clinical notes, and in the same corpus after de-identification. Only about 1.2-3% less SNOMED-CT concepts were found in de-identified versions of our corpus, and many of these concepts were PHI that was erroneously identified as clinical information. To study this impact in more details and assess how generalizable our findings were, we examined the overlap between select clinical information annotated in the 2010 i2b2 NLP challenge corpus and automatic PHI annotations from our best-of-breed VHA clinical text de-identification system (nicknamed 'BoB'). Overall, only 0.81% of the clinical information exactly overlapped with PHI, and 1.78% partly overlapped. We conclude that automated text de-identification's impact on clinical information is small, but not negligible, and that improved clinical acronyms and eponyms disambiguation could significantly reduce this impact. Copyright © 2014 Elsevier Inc. All rights reserved.

Evaluating Text Complexity and Flesch-Kincaid Grade Level

ERIC Educational Resources Information Center

Solnyshkina, Marina I.; Zamaletdinov, Radif R.; Gorodetskaya, Ludmila A.; Gabitov, Azat I.

2017-01-01

The article presents the results of an exploratory study of the use of T.E.R.A., an automated tool measuring text complexity and readability based on the assessment of five text complexity parameters: narrativity, syntactic simplicity, word concreteness, referential cohesion and deep cohesion. Aimed at finding ways to utilize T.E.R.A. for…

It’s about This and That: A Description of Anaphoric Expressions in Clinical Text

PubMed Central

Wang, Yan; Melton, Genevieve B.; Pakhomov, Serguei

2011-01-01

Although anaphoric expressions are very common in biomedical and clinical documents, little work has been done to systematically characterize their use in clinical text. Samples of ‘it’, ‘this’, and ‘that’ expressions occurring in inpatient clinical notes from four metropolitan hospitals were analyzed using a combination of semi-automated and manual annotation techniques. We developed a rule-based approach to filter potential non-referential expressions. A physician then manually annotated 1000 potential referential instances to determine referent status and the antecedent of each referent expression. A distributional analysis of the three referring expressions in the entire corpus of notes demonstrates a high prevalence of anaphora and large variance in distributions of referential expressions with different notes. Our results confirm that anaphoric expressions are common in clinical texts. Effective co-reference resolution with anaphoric expressions remains an important challenge in medical natural language processing research. PMID:22195211

Combining computational analyses and interactive visualization for document exploration and sensemaking in jigsaw.

PubMed

Görg, Carsten; Liu, Zhicheng; Kihm, Jaeyeon; Choo, Jaegul; Park, Haesun; Stasko, John

2013-10-01

Investigators across many disciplines and organizations must sift through large collections of text documents to understand and piece together information. Whether they are fighting crime, curing diseases, deciding what car to buy, or researching a new field, inevitably investigators will encounter text documents. Taking a visual analytics approach, we integrate multiple text analysis algorithms with a suite of interactive visualizations to provide a flexible and powerful environment that allows analysts to explore collections of documents while sensemaking. Our particular focus is on the process of integrating automated analyses with interactive visualizations in a smooth and fluid manner. We illustrate this integration through two example scenarios: an academic researcher examining InfoVis and VAST conference papers and a consumer exploring car reviews while pondering a purchase decision. Finally, we provide lessons learned toward the design and implementation of visual analytics systems for document exploration and understanding.

Task Analysis and Descriptions of Required Job Competencies of Robotics/Automated Systems Technicians. Outlines for New Courses and Modules.

ERIC Educational Resources Information Center

Hull, Daniel M.; Lovett, James E.

The six new robotics and automated systems specialty courses developed by the Robotics/Automated Systems Technician (RAST) project are described in this publication. Course titles are Fundamentals of Robotics and Automated Systems, Automated Systems and Support Components, Controllers for Robots and Automated Systems, Robotics and Automated…

GIDEP Batching Tool

NASA Technical Reports Server (NTRS)

Fong, Danny; Odell,Dorice; Barry, Peter; Abrahamian, Tomik

2008-01-01

This software provides internal, automated search mechanics of GIDEP (Government- Industry Data Exchange Program) Alert data imported from the GIDEP government Web site. The batching tool allows the import of a single parts list in tab-delimited text format into the local JPL GIDEP database. Delimiters from every part number are removed. The original part numbers with delimiters are compared, as well as the newly generated list without the delimiters. The two lists run against the GIDEP imports, and output any matches. This feature only works with Netscape 2.0 or greater, or Internet Explorer 4.0 or greater. The user selects the browser button to choose a text file to import. When the submit button is pressed, this script will import alerts from the text file into the local JPL GIDEP database. This batch tool provides complete in-house control over exported material and data for automated batch match abilities. The batching tool has the ability to match capabilities of the parts list to tables, and yields results that aid further research and analysis. This provides more control over GIDEP information for metrics and reports information not provided by the government site. This software yields results quickly and gives more control over external data from the government site in order to generate other reports not available from the external source. There is enough space to store years of data. The program relates to risk identification and management with regard to projects and GIDEP alert information encompassing flight parts for space exploration.

Automated Program Analysis for Cybersecurity (APAC)

DTIC Science & Technology

2016-07-14

AUTOMATED PROGRAM ANALYSIS FOR CYBERSECURITY (APAC) FIVE DIRECTIONS, INC JULY 2016 FINAL TECHNICAL REPORT APPROVED... CYBERSECURITY (APAC) 5a. CONTRACT NUMBER FA8750-14-C-0050 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT NUMBER 61101E 6. AUTHOR(S) William Arbaugh...AC Team Adversarial Challenge Team, responsible for creating malicious applications APAC Automated Program Analysis for Cybersecurity BAE BAE Systems

ADP Analysis project for the Human Resources Management Division

NASA Technical Reports Server (NTRS)

Tureman, Robert L., Jr.

1993-01-01

The ADP (Automated Data Processing) Analysis Project was conducted for the Human Resources Management Division (HRMD) of NASA's Langley Research Center. The three major areas of work in the project were computer support, automated inventory analysis, and an ADP study for the Division. The goal of the computer support work was to determine automation needs of Division personnel and help them solve computing problems. The goal of automated inventory analysis was to find a way to analyze installed software and usage on a Macintosh. Finally, the ADP functional systems study for the Division was designed to assess future HRMD needs concerning ADP organization and activities.

Automated frame selection process for high-resolution microendoscopy

NASA Astrophysics Data System (ADS)

Ishijima, Ayumu; Schwarz, Richard A.; Shin, Dongsuk; Mondrik, Sharon; Vigneswaran, Nadarajah; Gillenwater, Ann M.; Anandasabapathy, Sharmila; Richards-Kortum, Rebecca

2015-04-01

We developed an automated frame selection algorithm for high-resolution microendoscopy video sequences. The algorithm rapidly selects a representative frame with minimal motion artifact from a short video sequence, enabling fully automated image analysis at the point-of-care. The algorithm was evaluated by quantitative comparison of diagnostically relevant image features and diagnostic classification results obtained using automated frame selection versus manual frame selection. A data set consisting of video sequences collected in vivo from 100 oral sites and 167 esophageal sites was used in the analysis. The area under the receiver operating characteristic curve was 0.78 (automated selection) versus 0.82 (manual selection) for oral sites, and 0.93 (automated selection) versus 0.92 (manual selection) for esophageal sites. The implementation of fully automated high-resolution microendoscopy at the point-of-care has the potential to reduce the number of biopsies needed for accurate diagnosis of precancer and cancer in low-resource settings where there may be limited infrastructure and personnel for standard histologic analysis.

Universal microfluidic automaton for autonomous sample processing: application to the Mars Organic Analyzer.

PubMed

Kim, Jungkyu; Jensen, Erik C; Stockton, Amanda M; Mathies, Richard A

2013-08-20

A fully integrated multilayer microfluidic chemical analyzer for automated sample processing and labeling, as well as analysis using capillary zone electrophoresis is developed and characterized. Using lifting gate microfluidic control valve technology, a microfluidic automaton consisting of a two-dimensional microvalve cellular array is fabricated with soft lithography in a format that enables facile integration with a microfluidic capillary electrophoresis device. The programmable sample processor performs precise mixing, metering, and routing operations that can be combined to achieve automation of complex and diverse assay protocols. Sample labeling protocols for amino acid, aldehyde/ketone and carboxylic acid analysis are performed automatically followed by automated transfer and analysis by the integrated microfluidic capillary electrophoresis chip. Equivalent performance to off-chip sample processing is demonstrated for each compound class; the automated analysis resulted in a limit of detection of ~16 nM for amino acids. Our microfluidic automaton provides a fully automated, portable microfluidic analysis system capable of autonomous analysis of diverse compound classes in challenging environments.

Design and realization of the compound text-based test questions library management system

NASA Astrophysics Data System (ADS)

Shi, Lei; Feng, Lin; Zhao, Xin

2011-12-01

The test questions library management system is the essential part of the on-line examination system. The basic demand for which is to deal with compound text including information like images, formulae and create the corresponding Word documents. Having compared with the two current solutions of creating documents, this paper presents a design proposal of Word Automation mechanism based on OLE/COM technology, and discusses the way of Word Automation application in detail and at last provides the operating results of the system which have high reference value in improving the generated efficiency of project documents and report forms.

An automated, broad-based, near real-time public health surveillance system using presentations to hospital Emergency Departments in New South Wales, Australia.

PubMed

Muscatello, David J; Churches, Tim; Kaldor, Jill; Zheng, Wei; Chiu, Clayton; Correll, Patricia; Jorm, Louisa

2005-12-22

In a climate of concern over bioterrorism threats and emergent diseases, public health authorities are trialling more timely surveillance systems. The 2003 Rugby World Cup (RWC) provided an opportunity to test the viability of a near real-time syndromic surveillance system in metropolitan Sydney, Australia. We describe the development and early results of this largely automated system that used data routinely collected in Emergency Departments (EDs). Twelve of 49 EDs in the Sydney metropolitan area automatically transmitted surveillance data from their existing information systems to a central database in near real-time. Information captured for each ED visit included patient demographic details, presenting problem and nursing assessment entered as free-text at triage time, physician-assigned provisional diagnosis codes, and status at departure from the ED. Both diagnoses from the EDs and triage text were used to assign syndrome categories. The text information was automatically classified into one or more of 26 syndrome categories using automated "naïve Bayes" text categorisation techniques. Automated processes were used to analyse both diagnosis and free text-based syndrome data and to produce web-based statistical summaries for daily review. An adjusted cumulative sum (cusum) was used to assess the statistical significance of trends. During the RWC the system did not identify any major public health threats associated with the tournament, mass gatherings or the influx of visitors. This was consistent with evidence from other sources, although two known outbreaks were already in progress before the tournament. Limited baseline in early monitoring prevented the system from automatically identifying these ongoing outbreaks. Data capture was invisible to clinical staff in EDs and did not add to their workload. We have demonstrated the feasibility and potential utility of syndromic surveillance using routinely collected data from ED information systems. Key features of our system are its nil impact on clinical staff, and its use of statistical methods to assign syndrome categories based on clinical free text information. The system is ongoing, and has expanded to cover 30 EDs. Results of formal evaluations of both the technical efficiency and the public health impacts of the system will be described subsequently.

Text mining to decipher free-response consumer complaints: insights from the NHTSA vehicle owner's complaint database.

PubMed

Ghazizadeh, Mahtab; McDonald, Anthony D; Lee, John D

2014-09-01

This study applies text mining to extract clusters of vehicle problems and associated trends from free-response data in the National Highway Traffic Safety Administration's vehicle owner's complaint database. As the automotive industry adopts new technologies, it is important to systematically assess the effect of these changes on traffic safety. Driving simulators, naturalistic driving data, and crash databases all contribute to a better understanding of how drivers respond to changing vehicle technology, but other approaches, such as automated analysis of incident reports, are needed. Free-response data from incidents representing two severity levels (fatal incidents and incidents involving injury) were analyzed using a text mining approach: latent semantic analysis (LSA). LSA and hierarchical clustering identified clusters of complaints for each severity level, which were compared and analyzed across time. Cluster analysis identified eight clusters of fatal incidents and six clusters of incidents involving injury. Comparisons showed that although the airbag clusters across the two severity levels have the same most frequent terms, the circumstances around the incidents differ. The time trends show clear increases in complaints surrounding the Ford/Firestone tire recall and the Toyota unintended acceleration recall. Increases in complaints may be partially driven by these recall announcements and the associated media attention. Text mining can reveal useful information from free-response databases that would otherwise be prohibitively time-consuming and difficult to summarize manually. Text mining can extend human analysis capabilities for large free-response databases to support earlier detection of problems and more timely safety interventions.

Generating Automated Text Complexity Classifications That Are Aligned with Targeted Text Complexity Standards. Research Report. ETS RR-10-28

ERIC Educational Resources Information Center

Sheehan, Kathleen M.; Kostin, Irene; Futagi, Yoko; Flor, Michael

2010-01-01

The Common Core Standards call for students to be exposed to a much greater level of text complexity than has been the norm in schools for the past 40 years. Textbook publishers, teachers, and assessment developers are being asked to refocus materials and methods to ensure that students are challenged to read texts at steadily increasing…

Evaluation of an automated karyotyping system for chromosome aberration analysis

NASA Technical Reports Server (NTRS)

Prichard, Howard M.

1987-01-01

Chromosome aberration analysis is a promising complement to conventional radiation dosimetry, particularly in the complex radiation fields encountered in the space environment. The capabilities of a recently developed automated karyotyping system were evaluated both to determine current capabilities and limitations and to suggest areas where future development should be emphasized. Cells exposed to radiometric chemicals and to photon and particulate radiation were evaluated by manual inspection and by automated karyotyping. It was demonstrated that the evaluated programs were appropriate for image digitization, storage, and transmission. However, automated and semi-automated scoring techniques must be advanced significantly if in-flight chromosome aberration analysis is to be practical. A degree of artificial intelligence may be necessary to realize this goal.

PLACE: an open-source python package for laboratory automation, control, and experimentation.

PubMed

Johnson, Jami L; Tom Wörden, Henrik; van Wijk, Kasper

2015-02-01

In modern laboratories, software can drive the full experimental process from data acquisition to storage, processing, and analysis. The automation of laboratory data acquisition is an important consideration for every laboratory. When implementing a laboratory automation scheme, important parameters include its reliability, time to implement, adaptability, and compatibility with software used at other stages of experimentation. In this article, we present an open-source, flexible, and extensible Python package for Laboratory Automation, Control, and Experimentation (PLACE). The package uses modular organization and clear design principles; therefore, it can be easily customized or expanded to meet the needs of diverse laboratories. We discuss the organization of PLACE, data-handling considerations, and then present an example using PLACE for laser-ultrasound experiments. Finally, we demonstrate the seamless transition to post-processing and analysis with Python through the development of an analysis module for data produced by PLACE automation. © 2014 Society for Laboratory Automation and Screening.

Automated Detection of Atrial Fibrillation Based on Time-Frequency Analysis of Seismocardiograms.

PubMed

Hurnanen, Tero; Lehtonen, Eero; Tadi, Mojtaba Jafari; Kuusela, Tom; Kiviniemi, Tuomas; Saraste, Antti; Vasankari, Tuija; Airaksinen, Juhani; Koivisto, Tero; Pankaala, Mikko

2017-09-01

In this paper, a novel method to detect atrial fibrillation (AFib) from a seismocardiogram (SCG) is presented. The proposed method is based on linear classification of the spectral entropy and a heart rate variability index computed from the SCG. The performance of the developed algorithm is demonstrated on data gathered from 13 patients in clinical setting. After motion artifact removal, in total 119 min of AFib data and 126 min of sinus rhythm data were considered for automated AFib detection. No other arrhythmias were considered in this study. The proposed algorithm requires no direct heartbeat peak detection from the SCG data, which makes it tolerant against interpersonal variations in the SCG morphology, and noise. Furthermore, the proposed method relies solely on the SCG and needs no complementary electrocardiography to be functional. For the considered data, the detection method performs well even on relatively low quality SCG signals. Using a majority voting scheme that takes five randomly selected segments from a signal and classifies these segments using the proposed algorithm, we obtained an average true positive rate of [Formula: see text] and an average true negative rate of [Formula: see text] for detecting AFib in leave-one-out cross-validation. This paper facilitates adoption of microelectromechanical sensor based heart monitoring devices for arrhythmia detection.

Automated segmentation of geographic atrophy in fundus autofluorescence images using supervised pixel classification.

PubMed

Hu, Zhihong; Medioni, Gerard G; Hernandez, Matthias; Sadda, Srinivas R

2015-01-01

Geographic atrophy (GA) is a manifestation of the advanced or late stage of age-related macular degeneration (AMD). AMD is the leading cause of blindness in people over the age of 65 in the western world. The purpose of this study is to develop a fully automated supervised pixel classification approach for segmenting GA, including uni- and multifocal patches in fundus autofluorescene (FAF) images. The image features include region-wise intensity measures, gray-level co-occurrence matrix measures, and Gaussian filter banks. A [Formula: see text]-nearest-neighbor pixel classifier is applied to obtain a GA probability map, representing the likelihood that the image pixel belongs to GA. Sixteen randomly chosen FAF images were obtained from 16 subjects with GA. The algorithm-defined GA regions are compared with manual delineation performed by a certified image reading center grader. Eight-fold cross-validation is applied to evaluate the algorithm performance. The mean overlap ratio (OR), area correlation (Pearson's [Formula: see text]), accuracy (ACC), true positive rate (TPR), specificity (SPC), positive predictive value (PPV), and false discovery rate (FDR) between the algorithm- and manually defined GA regions are [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text], respectively.

AUTOMATED SOLID PHASE EXTRACTION GC/MS FOR ANALYSIS OF SEMIVOLATILES IN WATER AND SEDIMENTS

EPA Science Inventory

Data is presented on the development of a new automated system combining solid phase extraction (SPE) with GC/MS spectrometry for the single-run analysis of water samples containing a broad range of organic compounds. The system uses commercially available automated in-line sampl...

Mobile Phone-Based Mood Ratings Prospectively Predict Psychotherapy Attendance.

PubMed

Bruehlman-Senecal, Emma; Aguilera, Adrian; Schueller, Stephen M

2017-09-01

Psychotherapy nonattendance is a costly and pervasive problem. While prior research has identified stable patient-level predictors of attendance, far less is known about dynamic (i.e., time-varying) factors. Identifying dynamic predictors can clarify how clinical states relate to psychotherapy attendance and inform effective "just-in-time" interventions to promote attendance. The present study examines whether daily mood, as measured by responses to automated mobile phone-based text messages, prospectively predicts attendance in group cognitive-behavioral therapy (CBT) for depression. Fifty-six Spanish-speaking Latino patients with elevated depressive symptoms (46 women, mean age=50.92years, SD=10.90years), enrolled in a manualized program of group CBT, received daily automated mood-monitoring text messages. Patients' daily mood ratings, message response rate, and delay in responding were recorded. Patients' self-reported mood the day prior to a scheduled psychotherapy session significantly predicted attendance, even after controlling for patients' prior attendance history and age (OR=1.33, 95% CI [1.04, 1.70], p=.02). Positive mood corresponded to a greater likelihood of attendance. Our results demonstrate the clinical utility of automated mood-monitoring text messages in predicting attendance. These results underscore the value of text messaging, and other mobile technologies, as adjuncts to psychotherapy. Future work should explore the use of such monitoring to guide interventions to increase attendance, and ultimately the efficacy of psychotherapy. Copyright © 2017. Published by Elsevier Ltd.

Subgraph augmented non-negative tensor factorization (SANTF) for modeling clinical narrative text

PubMed Central

Xin, Yu; Hochberg, Ephraim; Joshi, Rohit; Uzuner, Ozlem; Szolovits, Peter

2015-01-01

Objective Extracting medical knowledge from electronic medical records requires automated approaches to combat scalability limitations and selection biases. However, existing machine learning approaches are often regarded by clinicians as black boxes. Moreover, training data for these automated approaches at often sparsely annotated at best. The authors target unsupervised learning for modeling clinical narrative text, aiming at improving both accuracy and interpretability. Methods The authors introduce a novel framework named subgraph augmented non-negative tensor factorization (SANTF). In addition to relying on atomic features (e.g., words in clinical narrative text), SANTF automatically mines higher-order features (e.g., relations of lymphoid cells expressing antigens) from clinical narrative text by converting sentences into a graph representation and identifying important subgraphs. The authors compose a tensor using patients, higher-order features, and atomic features as its respective modes. We then apply non-negative tensor factorization to cluster patients, and simultaneously identify latent groups of higher-order features that link to patient clusters, as in clinical guidelines where a panel of immunophenotypic features and laboratory results are used to specify diagnostic criteria. Results and Conclusion SANTF demonstrated over 10% improvement in averaged F-measure on patient clustering compared to widely used non-negative matrix factorization (NMF) and k-means clustering methods. Multiple baselines were established by modeling patient data using patient-by-features matrices with different feature configurations and then performing NMF or k-means to cluster patients. Feature analysis identified latent groups of higher-order features that lead to medical insights. We also found that the latent groups of atomic features help to better correlate the latent groups of higher-order features. PMID:25862765

Finding Relevant Data in a Sea of Languages

DTIC Science & Technology

2016-04-26

full machine-translated text , unbiased word clouds , query-biased word clouds , and query-biased sentence...and information retrieval to automate language processing tasks so that the limited number of linguists available for analyzing text and spoken...the crime (stock market). The Cross-LAnguage Search Engine (CLASE) has already preprocessed the documents, extracting text to identify the language

An approach to describing and analysing bulk biological annotation quality: a case study using UniProtKB.

PubMed

Bell, Michael J; Gillespie, Colin S; Swan, Daniel; Lord, Phillip

2012-09-15

Annotations are a key feature of many biological databases, used to convey our knowledge of a sequence to the reader. Ideally, annotations are curated manually, however manual curation is costly, time consuming and requires expert knowledge and training. Given these issues and the exponential increase of data, many databases implement automated annotation pipelines in an attempt to avoid un-annotated entries. Both manual and automated annotations vary in quality between databases and annotators, making assessment of annotation reliability problematic for users. The community lacks a generic measure for determining annotation quality and correctness, which we look at addressing within this article. Specifically we investigate word reuse within bulk textual annotations and relate this to Zipf's Principle of Least Effort. We use the UniProt Knowledgebase (UniProtKB) as a case study to demonstrate this approach since it allows us to compare annotation change, both over time and between automated and manually curated annotations. By applying power-law distributions to word reuse in annotation, we show clear trends in UniProtKB over time, which are consistent with existing studies of quality on free text English. Further, we show a clear distinction between manual and automated analysis and investigate cohorts of protein records as they mature. These results suggest that this approach holds distinct promise as a mechanism for judging annotation quality. Source code is available at the authors website: http://homepages.cs.ncl.ac.uk/m.j.bell1/annotation. phillip.lord@newcastle.ac.uk.

Development of an automated asbestos counting software based on fluorescence microscopy.

PubMed

Alexandrov, Maxym; Ichida, Etsuko; Nishimura, Tomoki; Aoki, Kousuke; Ishida, Takenori; Hirota, Ryuichi; Ikeda, Takeshi; Kawasaki, Tetsuo; Kuroda, Akio

2015-01-01

An emerging alternative to the commonly used analytical methods for asbestos analysis is fluorescence microscopy (FM), which relies on highly specific asbestos-binding probes to distinguish asbestos from interfering non-asbestos fibers. However, all types of microscopic asbestos analysis require laborious examination of large number of fields of view and are prone to subjective errors and large variability between asbestos counts by different analysts and laboratories. A possible solution to these problems is automated counting of asbestos fibers by image analysis software, which would lower the cost and increase the reliability of asbestos testing. This study seeks to develop a fiber recognition and counting software for FM-based asbestos analysis. We discuss the main features of the developed software and the results of its testing. Software testing showed good correlation between automated and manual counts for the samples with medium and high fiber concentrations. At low fiber concentrations, the automated counts were less accurate, leading us to implement correction mode for automated counts. While the full automation of asbestos analysis would require further improvements in accuracy of fiber identification, the developed software could already assist professional asbestos analysts and record detailed fiber dimensions for the use in epidemiological research.

Manual versus Automated Rodent Behavioral Assessment: Comparing Efficacy and Ease of Bederson and Garcia Neurological Deficit Scores to an Open Field Video-Tracking System.

PubMed

Desland, Fiona A; Afzal, Aqeela; Warraich, Zuha; Mocco, J

2014-01-01

Animal models of stroke have been crucial in advancing our understanding of the pathophysiology of cerebral ischemia. Currently, the standards for determining neurological deficit in rodents are the Bederson and Garcia scales, manual assessments scoring animals based on parameters ranked on a narrow scale of severity. Automated open field analysis of a live-video tracking system that analyzes animal behavior may provide a more sensitive test. Results obtained from the manual Bederson and Garcia scales did not show significant differences between pre- and post-stroke animals in a small cohort. When using the same cohort, however, post-stroke data obtained from automated open field analysis showed significant differences in several parameters. Furthermore, large cohort analysis also demonstrated increased sensitivity with automated open field analysis versus the Bederson and Garcia scales. These early data indicate use of automated open field analysis software may provide a more sensitive assessment when compared to traditional Bederson and Garcia scales.

Automated Sneak Circuit Analysis Technique

DTIC Science & Technology

1990-06-01

the OrCAD/SDT module Port facility. 2. The terminals of all in- circuit voltage sources (e , batteries) must be labeled using the OrCAD/SDT module port...ELECTE 1 MAY 2 01994 _- AUTOMATED SNEAK CIRCUIT ANALYSIS TECHNIQUEIt~ w I wtA who RADC 94-14062 Systems Reliability & Engineering Division Rome...Air Develpment Center Best Avai~lable copy AUTOMATED SNEAK CIRCUIT ANALYSIS TECHNIQUE RADC June 1990 Systems Reliability & Engineering Division Rome Air

Effectiveness of Automated Chinese Sentence Scoring with Latent Semantic Analysis

ERIC Educational Resources Information Center

Liao, Chen-Huei; Kuo, Bor-Chen; Pai, Kai-Chih

2012-01-01

Automated scoring by means of Latent Semantic Analysis (LSA) has been introduced lately to improve the traditional human scoring system. The purposes of the present study were to develop a LSA-based assessment system to evaluate children's Chinese sentence construction skills and to examine the effectiveness of LSA-based automated scoring function…

AUTOMATED LITERATURE PROCESSING HANDLING AND ANALYSIS SYSTEM--FIRST GENERATION.

ERIC Educational Resources Information Center

Redstone Scientific Information Center, Redstone Arsenal, AL.

THE REPORT PRESENTS A SUMMARY OF THE DEVELOPMENT AND THE CHARACTERISTICS OF THE FIRST GENERATION OF THE AUTOMATED LITERATURE PROCESSING, HANDLING AND ANALYSIS (ALPHA-1) SYSTEM. DESCRIPTIONS OF THE COMPUTER TECHNOLOGY OF ALPHA-1 AND THE USE OF THIS AUTOMATED LIBRARY TECHNIQUE ARE PRESENTED. EACH OF THE SUBSYSTEMS AND MODULES NOW IN OPERATION ARE…

Enhancements for a Dynamic Data Warehousing and Mining System for Large-scale HSCB Data

DTIC Science & Technology

2016-07-20

Intelligent Automation Incorporated Enhancements for a Dynamic Data Warehousing and Mining ...Page | 2 Intelligent Automation Incorporated Monthly Report No. 4 Enhancements for a Dynamic Data Warehousing and Mining System Large-Scale HSCB...including Top Videos, Top Users, Top Words, and Top Languages, and also applied NER to the text associated with YouTube posts. We have also developed UI for

Enhancements for a Dynamic Data Warehousing and Mining System for Large-Scale HSCB Data

DTIC Science & Technology

2016-07-20

Intelligent Automation Incorporated Enhancements for a Dynamic Data Warehousing and Mining ...Page | 2 Intelligent Automation Incorporated Monthly Report No. 4 Enhancements for a Dynamic Data Warehousing and Mining System Large-Scale HSCB...including Top Videos, Top Users, Top Words, and Top Languages, and also applied NER to the text associated with YouTube posts. We have also developed UI for

Building an efficient curation workflow for the Arabidopsis literature corpus

PubMed Central

Li, Donghui; Berardini, Tanya Z.; Muller, Robert J.; Huala, Eva

2012-01-01

TAIR (The Arabidopsis Information Resource) is the model organism database (MOD) for Arabidopsis thaliana, a model plant with a literature corpus of about 39 000 articles in PubMed, with over 4300 new articles added in 2011. We have developed a literature curation workflow incorporating both automated and manual elements to cope with this flood of new research articles. The current workflow can be divided into two phases: article selection and curation. Structured controlled vocabularies, such as the Gene Ontology and Plant Ontology are used to capture free text information in the literature as succinct ontology-based annotations suitable for the application of computational analysis methods. We also describe our curation platform and the use of text mining tools in our workflow. Database URL: www.arabidopsis.org PMID:23221298

Look@NanoSIMS--a tool for the analysis of nanoSIMS data in environmental microbiology.

PubMed

Polerecky, Lubos; Adam, Birgit; Milucka, Jana; Musat, Niculina; Vagner, Tomas; Kuypers, Marcel M M

2012-04-01

We describe an open-source freeware programme for high throughput analysis of nanoSIMS (nanometre-scale secondary ion mass spectrometry) data. The programme implements basic data processing and analytical functions, including display and drift-corrected accumulation of scanned planes, interactive and semi-automated definition of regions of interest (ROIs), and export of the ROIs' elemental and isotopic composition in graphical and text-based formats. Additionally, the programme offers new functions that were custom-designed to address the needs of environmental microbiologists. Specifically, it allows manual and automated classification of ROIs based on the information that is derived either from the nanoSIMS dataset itself (e.g. from labelling achieved by halogen in situ hybridization) or is provided externally (e.g. as a fluorescence in situ hybridization image). Moreover, by implementing post-processing routines coupled to built-in statistical tools, the programme allows rapid synthesis and comparative analysis of results from many different datasets. After validation of the programme, we illustrate how these new processing and analytical functions increase flexibility, efficiency and depth of the nanoSIMS data analysis. Through its custom-made and open-source design, the programme provides an efficient, reliable and easily expandable tool that can help a growing community of environmental microbiologists and researchers from other disciplines process and analyse their nanoSIMS data. © 2012 Society for Applied Microbiology and Blackwell Publishing Ltd.

SYRIAC: The systematic review information automated collection system a data warehouse for facilitating automated biomedical text classification.

PubMed

Yang, Jianji J; Cohen, Aaron M; Cohen, Aaron; McDonagh, Marian S

2008-11-06

Automatic document classification can be valuable in increasing the efficiency in updating systematic reviews (SR). In order for the machine learning process to work well, it is critical to create and maintain high-quality training datasets consisting of expert SR inclusion/exclusion decisions. This task can be laborious, especially when the number of topics is large and source data format is inconsistent.To approach this problem, we build an automated system to streamline the required steps, from initial notification of update in source annotation files to loading the data warehouse, along with a web interface to monitor the status of each topic. In our current collection of 26 SR topics, we were able to standardize almost all of the relevance judgments and recovered PMIDs for over 80% of all articles. Of those PMIDs, over 99% were correct in a manual random sample study. Our system performs an essential function in creating training and evaluation data sets for SR text mining research.

SYRIAC: The SYstematic Review Information Automated Collection System A Data Warehouse for Facilitating Automated Biomedical Text Classification

PubMed Central

Yang, Jianji J.; Cohen, Aaron M.; McDonagh, Marian S.

2008-01-01

Automatic document classification can be valuable in increasing the efficiency in updating systematic reviews (SR). In order for the machine learning process to work well, it is critical to create and maintain high-quality training datasets consisting of expert SR inclusion/exclusion decisions. This task can be laborious, especially when the number of topics is large and source data format is inconsistent. To approach this problem, we build an automated system to streamline the required steps, from initial notification of update in source annotation files to loading the data warehouse, along with a web interface to monitor the status of each topic. In our current collection of 26 SR topics, we were able to standardize almost all of the relevance judgments and recovered PMIDs for over 80% of all articles. Of those PMIDs, over 99% were correct in a manual random sample study. Our system performs an essential function in creating training and evaluation datasets for SR text mining research. PMID:18999194

Streamlined sign-out of capillary protein electrophoresis using middleware and an open-source macro application.

PubMed

Mathur, Gagan; Haugen, Thomas H; Davis, Scott L; Krasowski, Matthew D

2014-01-01

Interfacing of clinical laboratory instruments with the laboratory information system (LIS) via "middleware" software is increasingly common. Our clinical laboratory implemented capillary electrophoresis using a Sebia(®) Capillarys-2™ (Norcross, GA, USA) instrument for serum and urine protein electrophoresis. Using Data Innovations Instrument Manager, an interface was established with the LIS (Cerner) that allowed for bi-directional transmission of numeric data. However, the text of the interpretive pathology report was not properly transferred. To reduce manual effort and possibility for error in text data transfer, we developed scripts in AutoHotkey, a free, open-source macro-creation and automation software utility. Scripts were written to create macros that automated mouse and key strokes. The scripts retrieve the specimen accession number, capture user input text, and insert the text interpretation in the correct patient record in the desired format. The scripts accurately and precisely transfer narrative interpretation into the LIS. Combined with bar-code reading by the electrophoresis instrument, the scripts transfer data efficiently to the correct patient record. In addition, the AutoHotKey script automated repetitive key strokes required for manual entry into the LIS, making protein electrophoresis sign-out easier to learn and faster to use by the pathology residents. Scripts allow for either preliminary verification by residents or final sign-out by the attending pathologist. Using the open-source AutoHotKey software, we successfully improved the transfer of text data between capillary electrophoresis software and the LIS. The use of open-source software tools should not be overlooked as tools to improve interfacing of laboratory instruments.

Accuracy and efficiency of computer-aided anatomical analysis using 3D visualization software based on semi-automated and automated segmentations.

PubMed

An, Gao; Hong, Li; Zhou, Xiao-Bing; Yang, Qiong; Li, Mei-Qing; Tang, Xiang-Yang

2017-03-01

We investigated and compared the functionality of two 3D visualization software provided by a CT vendor and a third-party vendor, respectively. Using surgical anatomical measurement as baseline, we evaluated the accuracy of 3D visualization and verified their utility in computer-aided anatomical analysis. The study cohort consisted of 50 adult cadavers fixed with the classical formaldehyde method. The computer-aided anatomical analysis was based on CT images (in DICOM format) acquired by helical scan with contrast enhancement, using a CT vendor provided 3D visualization workstation (Syngo) and a third-party 3D visualization software (Mimics) that was installed on a PC. Automated and semi-automated segmentations were utilized in the 3D visualization workstation and software, respectively. The functionality and efficiency of automated and semi-automated segmentation methods were compared. Using surgical anatomical measurement as a baseline, the accuracy of 3D visualization based on automated and semi-automated segmentations was quantitatively compared. In semi-automated segmentation, the Mimics 3D visualization software outperformed the Syngo 3D visualization workstation. No significant difference was observed in anatomical data measurement by the Syngo 3D visualization workstation and the Mimics 3D visualization software (P>0.05). Both the Syngo 3D visualization workstation provided by a CT vendor and the Mimics 3D visualization software by a third-party vendor possessed the needed functionality, efficiency and accuracy for computer-aided anatomical analysis. Copyright © 2016 Elsevier GmbH. All rights reserved.

Driver-centred vehicle automation: using network analysis for agent-based modelling of the driver in highly automated driving systems.

PubMed

Banks, Victoria A; Stanton, Neville A

2016-11-01

To the average driver, the concept of automation in driving infers that they can become completely 'hands and feet free'. This is a common misconception, however, one that has been shown through the application of Network Analysis to new Cruise Assist technologies that may feature on our roads by 2020. Through the adoption of a Systems Theoretic approach, this paper introduces the concept of driver-initiated automation which reflects the role of the driver in highly automated driving systems. Using a combination of traditional task analysis and the application of quantitative network metrics, this agent-based modelling paper shows how the role of the driver remains an integral part of the driving system implicating the need for designers to ensure they are provided with the tools necessary to remain actively in-the-loop despite giving increasing opportunities to delegate their control to the automated subsystems. Practitioner Summary: This paper describes and analyses a driver-initiated command and control system of automation using representations afforded by task and social networks to understand how drivers remain actively involved in the task. A network analysis of different driver commands suggests that such a strategy does maintain the driver in the control loop.

Analysis of trust in autonomy for convoy operations

NASA Astrophysics Data System (ADS)

Gremillion, Gregory M.; Metcalfe, Jason S.; Marathe, Amar R.; Paul, Victor J.; Christensen, James; Drnec, Kim; Haynes, Benjamin; Atwater, Corey

2016-05-01

With growing use of automation in civilian and military contexts that engage cooperatively with humans, the operator's level of trust in the automated system is a major factor in determining the efficacy of the human-autonomy teams. Suboptimal levels of human trust in autonomy (TiA) can be detrimental to joint team performance. This mis-calibrated trust can manifest in several ways, such as distrust and complete disuse of the autonomy or complacency, which results in an unsupervised autonomous system. This work investigates human behaviors that may reflect TiA in the context of an automated driving task, with the goal of improving team performance. Subjects performed a simulated leaderfollower driving task with an automated driving assistant. The subjects had could choose to engage an automated lane keeping and active cruise control system of varying performance levels. Analysis of the experimental data was performed to identify contextual features of the simulation environment that correlated to instances of automation engagement and disengagement. Furthermore, behaviors that potentially indicate inappropriate TiA levels were identified in the subject trials using estimates of momentary risk and agent performance, as functions of these contextual features. Inter-subject and intra-subject trends in automation usage and performance were also identified. This analysis indicated that for poorer performing automation, TiA decreases with time, while higher performing automation induces less drift toward diminishing usage, and in some cases increases in TiA. Subject use of automation was also found to be largely influenced by course features.

Human performance consequences of stages and levels of automation: an integrated meta-analysis.

PubMed

Onnasch, Linda; Wickens, Christopher D; Li, Huiyang; Manzey, Dietrich

2014-05-01

We investigated how automation-induced human performance consequences depended on the degree of automation (DOA). Function allocation between human and automation can be represented in terms of the stages and levels taxonomy proposed by Parasuraman, Sheridan, and Wickens. Higher DOAs are achieved both by later stages and higher levels within stages. A meta-analysis based on data of 18 experiments examines the mediating effects of DOA on routine system performance, performance when the automation fails, workload, and situation awareness (SA). The effects of DOA on these measures are summarized by level of statistical significance. We found (a) a clear automation benefit for routine system performance with increasing DOA, (b) a similar but weaker pattern for workload when automation functioned properly, and (c) a negative impact of higher DOA on failure system performance and SA. Most interesting was the finding that negative consequences of automation seem to be most likely when DOA moved across a critical boundary, which was identified between automation supporting information analysis and automation supporting action selection. Results support the proposed cost-benefit trade-off with regard to DOA. It seems that routine performance and workload on one hand, and the potential loss of SA and manual skills on the other hand, directly trade off and that appropriate function allocation can serve only one of the two aspects. Findings contribute to the body of research on adequate function allocation by providing an overall picture through quantitatively combining data from a variety of studies across varying domains.

Improved Cloud Detection Utilizing Defense Meteorological Satellite Program near Infrared Measurements

DTIC Science & Technology

1982-01-27

Visible 3. 3 Ea r th Location, Colocation, and Normalization 4. IMAGE ANALYSIS 4. 1 Interactive Capabilities 4.2 Examples 5. AUTOMATED CLOUD...computer Interactive Data Access System (McIDAS) before image analysis and algorithm development were done. Earth-location is an automated procedure to...the factor l / s in (SSE) toward the gain settings given in Table 5. 4. IMAGE ANALYSIS 4.1 Interactive Capabilities The development of automated

English Textbooks for Russian Students: Problems and Specific Features

ERIC Educational Resources Information Center

Solnyshkina, Marina I.; Vishnyakova, Ol'ga D.; Gafiyatova, Elzara V.; Gabitov, Azat I.

2017-01-01

The research identifies the complexity level of eight texts from Spotlight 11 used in Russian TEFL to prepare students for National Unified Exam in English and assess their reading skills. The results of the analyses conducted with the help of T.E.R.A., an automated text processor, prove that all texts fell within the range of 6-9 Flesch-Kincaid…

Semi-Automated Methods for Refining a Domain-Specific Terminology Base

DTIC Science & Technology

2011-02-01

only as a resource for written and oral translation, but also for Natural Language Processing ( NLP ) applications, text retrieval, document indexing...Natural Language Processing ( NLP ) applications, text retrieval, document indexing, and other knowledge management tasks. The objective of this...also for Natural Language Processing ( NLP ) applications, text retrieval (1), document indexing, and other knowledge management tasks. The National

Understanding disciplinary vocabularies using a full-text enabled domain-independent term extraction approach.

PubMed

Yan, Erjia; Williams, Jake; Chen, Zheng

2017-01-01

Publication metadata help deliver rich analyses of scholarly communication. However, research concepts and ideas are more effectively expressed through unstructured fields such as full texts. Thus, the goals of this paper are to employ a full-text enabled method to extract terms relevant to disciplinary vocabularies, and through them, to understand the relationships between disciplines. This paper uses an efficient, domain-independent term extraction method to extract disciplinary vocabularies from a large multidisciplinary corpus of PLoS ONE publications. It finds a power-law pattern in the frequency distributions of terms present in each discipline, indicating a semantic richness potentially sufficient for further study and advanced analysis. The salient relationships amongst these vocabularies become apparent in application of a principal component analysis. For example, Mathematics and Computer and Information Sciences were found to have similar vocabulary use patterns along with Engineering and Physics; while Chemistry and the Social Sciences were found to exhibit contrasting vocabulary use patterns along with the Earth Sciences and Chemistry. These results have implications to studies of scholarly communication as scholars attempt to identify the epistemological cultures of disciplines, and as a full text-based methodology could lead to machine learning applications in the automated classification of scholarly work according to disciplinary vocabularies.

Understanding disciplinary vocabularies using a full-text enabled domain-independent term extraction approach

PubMed Central

Williams, Jake; Chen, Zheng

2017-01-01

Publication metadata help deliver rich analyses of scholarly communication. However, research concepts and ideas are more effectively expressed through unstructured fields such as full texts. Thus, the goals of this paper are to employ a full-text enabled method to extract terms relevant to disciplinary vocabularies, and through them, to understand the relationships between disciplines. This paper uses an efficient, domain-independent term extraction method to extract disciplinary vocabularies from a large multidisciplinary corpus of PLoS ONE publications. It finds a power-law pattern in the frequency distributions of terms present in each discipline, indicating a semantic richness potentially sufficient for further study and advanced analysis. The salient relationships amongst these vocabularies become apparent in application of a principal component analysis. For example, Mathematics and Computer and Information Sciences were found to have similar vocabulary use patterns along with Engineering and Physics; while Chemistry and the Social Sciences were found to exhibit contrasting vocabulary use patterns along with the Earth Sciences and Chemistry. These results have implications to studies of scholarly communication as scholars attempt to identify the epistemological cultures of disciplines, and as a full text-based methodology could lead to machine learning applications in the automated classification of scholarly work according to disciplinary vocabularies. PMID:29186141

Automated Image Analysis Corrosion Working Group Update: February 1, 2018

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

Wendelberger, James G.

These are slides for the automated image analysis corrosion working group update. The overall goals were: automate the detection and quantification of features in images (faster, more accurate), how to do this (obtain data, analyze data), focus on Laser Scanning Confocal Microscope (LCM) data (laser intensity, laser height/depth, optical RGB, optical plus laser RGB).

Automated Sensitivity Analysis of Interplanetary Trajectories

NASA Technical Reports Server (NTRS)

Knittel, Jeremy; Hughes, Kyle; Englander, Jacob; Sarli, Bruno

2017-01-01

This work describes a suite of Python tools known as the Python EMTG Automated Trade Study Application (PEATSA). PEATSA was written to automate the operation of trajectory optimization software, simplify the process of performing sensitivity analysis, and was ultimately found to out-perform a human trajectory designer in unexpected ways. These benefits will be discussed and demonstrated on sample mission designs.

Characterization of Temporal Semantic Shifts of Peer-to-Peer Communication in a Health-Related Online Community: Implications for Data-driven Health Promotion.

PubMed

Sridharan, Vishnupriya; Cohen, Trevor; Cobb, Nathan; Myneni, Sahiti

2016-01-01

With online social platforms gaining popularity as venues of behavior change, it is important to understand the ways in which these platforms facilitate peer interactions. In this paper, we characterize temporal trends in user communication through mapping of theoretically-linked semantic content. We used qualitative coding and automated text analysis to assign theoretical techniques to peer interactions in an online community for smoking cessation, subsequently facilitating temporal visualization of the observed techniques. Results indicate manifestation of several behavior change techniques such as feedback and monitoring' and 'rewards'. Automated methods yielded reasonable results (F-measure=0.77). Temporal trends among relapsers revealed reduction in communication after a relapse event. This social withdrawal may be attributed to failure guilt after the relapse. Results indicate significant change in thematic categories such as 'social support', 'natural consequences', and 'comparison of outcomes' pre and post relapse. Implications for development of behavioral support technologies that promote long-term abstinence are discussed.

Process development for automated solar cell and module production. Task 4: Automated array assembly

NASA Technical Reports Server (NTRS)

1980-01-01

A process sequence which can be used in conjunction with automated equipment for the mass production of solar cell modules for terrestrial use was developed. The process sequence was then critically analyzed from a technical and economic standpoint to determine the technological readiness of certain process steps for implementation. The steps receiving analysis were: back contact metallization, automated cell array layup/interconnect, and module edge sealing. For automated layup/interconnect, both hard automation and programmable automation (using an industrial robot) were studied. The programmable automation system was then selected for actual hardware development.

Measuring Up: Implementing a Dental Quality Measure in the Electronic Health Record Context

PubMed Central

Bhardwaj, Aarti; Ramoni, Rachel; Kalenderian, Elsbeth; Neumann, Ana; Hebballi, Nutan B; White, Joel M; McClellan, Lyle; Walji, Muhammad F

2015-01-01

Background Quality improvement requires quality measures that are validly implementable. In this work, we assessed the feasibility and performance of an automated electronic Meaningful Use dental clinical quality measure (percentage of children who received fluoride varnish). Methods We defined how to implement the automated measure queries in a dental electronic health record (EHR). Within records identified through automated query, we manually reviewed a subsample to assess the performance of the query. Results The automated query found 71.0% of patients to have had fluoride varnish compared to 77.6% found using the manual chart review. The automated quality measure performance was 90.5% sensitivity, 90.8% specificity, 96.9% positive predictive value, and 75.2% negative predictive value. Conclusions Our findings support the feasibility of automated dental quality measure queries in the context of sufficient structured data. Information noted only in the free text rather than in structured data would require natural language processing approaches to effectively query. Practical Implications To participate in self-directed quality improvement, dental clinicians must embrace the accountability era. Commitment to quality will require enhanced documentation in order to support near-term automated calculation of quality measures. PMID:26562736

Automated Assessment of Patients' Self-Narratives for Posttraumatic Stress Disorder Screening Using Natural Language Processing and Text Mining.

PubMed

He, Qiwei; Veldkamp, Bernard P; Glas, Cees A W; de Vries, Theo

2017-03-01

Patients' narratives about traumatic experiences and symptoms are useful in clinical screening and diagnostic procedures. In this study, we presented an automated assessment system to screen patients for posttraumatic stress disorder via a natural language processing and text-mining approach. Four machine-learning algorithms-including decision tree, naive Bayes, support vector machine, and an alternative classification approach called the product score model-were used in combination with n-gram representation models to identify patterns between verbal features in self-narratives and psychiatric diagnoses. With our sample, the product score model with unigrams attained the highest prediction accuracy when compared with practitioners' diagnoses. The addition of multigrams contributed most to balancing the metrics of sensitivity and specificity. This article also demonstrates that text mining is a promising approach for analyzing patients' self-expression behavior, thus helping clinicians identify potential patients from an early stage.

Structuring and extracting knowledge for the support of hypothesis generation in molecular biology

PubMed Central

Roos, Marco; Marshall, M Scott; Gibson, Andrew P; Schuemie, Martijn; Meij, Edgar; Katrenko, Sophia; van Hage, Willem Robert; Krommydas, Konstantinos; Adriaans, Pieter W

2009-01-01

Background Hypothesis generation in molecular and cellular biology is an empirical process in which knowledge derived from prior experiments is distilled into a comprehensible model. The requirement of automated support is exemplified by the difficulty of considering all relevant facts that are contained in the millions of documents available from PubMed. Semantic Web provides tools for sharing prior knowledge, while information retrieval and information extraction techniques enable its extraction from literature. Their combination makes prior knowledge available for computational analysis and inference. While some tools provide complete solutions that limit the control over the modeling and extraction processes, we seek a methodology that supports control by the experimenter over these critical processes. Results We describe progress towards automated support for the generation of biomolecular hypotheses. Semantic Web technologies are used to structure and store knowledge, while a workflow extracts knowledge from text. We designed minimal proto-ontologies in OWL for capturing different aspects of a text mining experiment: the biological hypothesis, text and documents, text mining, and workflow provenance. The models fit a methodology that allows focus on the requirements of a single experiment while supporting reuse and posterior analysis of extracted knowledge from multiple experiments. Our workflow is composed of services from the 'Adaptive Information Disclosure Application' (AIDA) toolkit as well as a few others. The output is a semantic model with putative biological relations, with each relation linked to the corresponding evidence. Conclusion We demonstrated a 'do-it-yourself' approach for structuring and extracting knowledge in the context of experimental research on biomolecular mechanisms. The methodology can be used to bootstrap the construction of semantically rich biological models using the results of knowledge extraction processes. Models specific to particular experiments can be constructed that, in turn, link with other semantic models, creating a web of knowledge that spans experiments. Mapping mechanisms can link to other knowledge resources such as OBO ontologies or SKOS vocabularies. AIDA Web Services can be used to design personalized knowledge extraction procedures. In our example experiment, we found three proteins (NF-Kappa B, p21, and Bax) potentially playing a role in the interplay between nutrients and epigenetic gene regulation. PMID:19796406

Automated microfluidic devices integrating solid-phase extraction, fluorescent labeling, and microchip electrophoresis for preterm birth biomarker analysis.

PubMed

Sahore, Vishal; Sonker, Mukul; Nielsen, Anna V; Knob, Radim; Kumar, Suresh; Woolley, Adam T

2018-01-01

We have developed multichannel integrated microfluidic devices for automated preconcentration, labeling, purification, and separation of preterm birth (PTB) biomarkers. We fabricated multilayer poly(dimethylsiloxane)-cyclic olefin copolymer (PDMS-COC) devices that perform solid-phase extraction (SPE) and microchip electrophoresis (μCE) for automated PTB biomarker analysis. The PDMS control layer had a peristaltic pump and pneumatic valves for flow control, while the PDMS fluidic layer had five input reservoirs connected to microchannels and a μCE system. The COC layers had a reversed-phase octyl methacrylate porous polymer monolith for SPE and fluorescent labeling of PTB biomarkers. We determined μCE conditions for two PTB biomarkers, ferritin (Fer) and corticotropin-releasing factor (CRF). We used these integrated microfluidic devices to preconcentrate and purify off-chip-labeled Fer and CRF in an automated fashion. Finally, we performed a fully automated on-chip analysis of unlabeled PTB biomarkers, involving SPE, labeling, and μCE separation with 1 h total analysis time. These integrated systems have strong potential to be combined with upstream immunoaffinity extraction, offering a compact sample-to-answer biomarker analysis platform. Graphical abstract Pressure-actuated integrated microfluidic devices have been developed for automated solid-phase extraction, fluorescent labeling, and microchip electrophoresis of preterm birth biomarkers.

Text mining, a race against time? An attempt to quantify possible variations in text corpora of medical publications throughout the years.

PubMed

Wagner, Mathias; Vicinus, Benjamin; Muthra, Sherieda T; Richards, Tereza A; Linder, Roland; Frick, Vilma Oliveira; Groh, Andreas; Rubie, Claudia; Weichert, Frank

2016-06-01

The continuous growth of medical sciences literature indicates the need for automated text analysis. Scientific writing which is neither unitary, transcending social situation nor defined by a timeless idea is subject to constant change as it develops in response to evolving knowledge, aims at different goals, and embodies different assumptions about nature and communication. The objective of this study was to evaluate whether publication dates should be considered when performing text mining. A search of PUBMED for combined references to chemokine identifiers and particular cancer related terms was conducted to detect changes over the past 36 years. Text analyses were performed using freeware available from the World Wide Web. TOEFL Scores of territories hosting institutional affiliations as well as various readability indices were investigated. Further assessment was conducted using Principal Component Analysis. Laboratory examination was performed to evaluate the quality of attempts to extract content from the examined linguistic features. The PUBMED search yielded a total of 14,420 abstracts (3,190,219 words). The range of findings in laboratory experimentation were coherent with the variability of the results described in the analyzed body of literature. Increased concurrence of chemokine identifiers together with cancer related terms was found at the abstract and sentence level, whereas complexity of sentences remained fairly stable. The findings of the present study indicate that concurrent references to chemokines and cancer increased over time whereas text complexity remained stable. Copyright © 2016 Elsevier Ltd. All rights reserved.

Tactical Intelligence Applications Experimentation (TIAX) Report. Intelligence Preparation of the Battlefield (IPB)-An Automated Approach to Terrain and Mobility Corridor Analysis

DTIC Science & Technology

1978-10-20

Preparation of the Battlefield (IPB) - Phase A An Automated Approach to Terrain and Mobility Cocridor Analysis Prepared For The ;*ttlefield Systems... the Battlefield (IPB) - Phase A An Automated Approach to Terrain and Mobility Corridcr Analysis, Prepared For The Battlefield Systems Integration... series of snapshots developed for Option A. The situation snapshots would be deteloped in like manner for each option, and stored in an

Progress on the development of automated data analysis algorithms and software for ultrasonic inspection of composites

NASA Astrophysics Data System (ADS)

Aldrin, John C.; Coughlin, Chris; Forsyth, David S.; Welter, John T.

2014-02-01

Progress is presented on the development and implementation of automated data analysis (ADA) software to address the burden in interpreting ultrasonic inspection data for large composite structures. The automated data analysis algorithm is presented in detail, which follows standard procedures for analyzing signals for time-of-flight indications and backwall amplitude dropout. ADA processing results are presented for test specimens that include inserted materials and discontinuities produced under poor manufacturing conditions.

Validity of automated measurement of left ventricular ejection fraction and volume using the Philips EPIQ system.

PubMed

Hovnanians, Ninel; Win, Theresa; Makkiya, Mohammed; Zheng, Qi; Taub, Cynthia

2017-11-01

To assess the efficiency and reproducibility of automated measurements of left ventricular (LV) volumes and LV ejection fraction (LVEF) in comparison to manually traced biplane Simpson's method. This is a single-center prospective study. Apical four- and two-chamber views were acquired in patients in sinus rhythm. Two operators independently measured LV volumes and LVEF using biplane Simpson's method. In addition, the image analysis software a2DQ on the Philips EPIQ system was applied to automatically assess the LV volumes and LVEF. Time spent on each analysis, using both methods, was documented. Concordance of echocardiographic measures was evaluated using intraclass correlation (ICC) and Bland-Altman analysis. Manual tracing and automated measurement of LV volumes and LVEF were performed in 184 patients with a mean age of 67.3 ± 17.3 years and BMI 28.0 ± 6.8 kg/m 2 . ICC and Bland-Altman analysis showed good agreements between manual and automated methods measuring LVEF, end-systolic, and end-diastolic volumes. The average analysis time was significantly less using the automated method than manual tracing (116 vs 217 seconds/patient, P < .0001). Automated measurement using the novel image analysis software a2DQ on the Philips EPIQ system produced accurate, efficient, and reproducible assessment of LV volumes and LVEF compared with manual measurement. © 2017, Wiley Periodicals, Inc.

Functional MRI Preprocessing in Lesioned Brains: Manual Versus Automated Region of Interest Analysis

PubMed Central

Garrison, Kathleen A.; Rogalsky, Corianne; Sheng, Tong; Liu, Brent; Damasio, Hanna; Winstein, Carolee J.; Aziz-Zadeh, Lisa S.

2015-01-01

Functional magnetic resonance imaging (fMRI) has significant potential in the study and treatment of neurological disorders and stroke. Region of interest (ROI) analysis in such studies allows for testing of strong a priori clinical hypotheses with improved statistical power. A commonly used automated approach to ROI analysis is to spatially normalize each participant’s structural brain image to a template brain image and define ROIs using an atlas. However, in studies of individuals with structural brain lesions, such as stroke, the gold standard approach may be to manually hand-draw ROIs on each participant’s non-normalized structural brain image. Automated approaches to ROI analysis are faster and more standardized, yet are susceptible to preprocessing error (e.g., normalization error) that can be greater in lesioned brains. The manual approach to ROI analysis has high demand for time and expertise, but may provide a more accurate estimate of brain response. In this study, commonly used automated and manual approaches to ROI analysis were directly compared by reanalyzing data from a previously published hypothesis-driven cognitive fMRI study, involving individuals with stroke. The ROI evaluated is the pars opercularis of the inferior frontal gyrus. Significant differences were identified in task-related effect size and percent-activated voxels in this ROI between the automated and manual approaches to ROI analysis. Task interactions, however, were consistent across ROI analysis approaches. These findings support the use of automated approaches to ROI analysis in studies of lesioned brains, provided they employ a task interaction design. PMID:26441816

Why people download the freeware AIDA v4.3a diabetes software program: a proof-of-concept semi-automated analysis.

PubMed

Lehmann, Eldon D

2003-01-01

AIDA is a diabetes-computing program freely available at www.2aida.org on the Web. The software is intended to serve as an educational support tool and can be used by anyone who has an interest in diabetes, whether they be patients, relatives, health-care professionals, or students. In previous "Diabetes Information Technology & WebWatch" columns various indicators of usage of the AIDA program have been reviewed, and various comments from users of the software have been documented. The purpose of this column is to overview a proof-of-concept semi-automated analysis about why people are downloading the latest version of the AIDA educational diabetes program. AIDA permits the interactive simulation of plasma insulin and blood glucose profiles for teaching, demonstration, self-learning, and research purposes. It has been made freely available, without charge, on the Internet as a noncommercial contribution to continuing diabetes education. Since its launch in 1996 over 300,000 visits have been logged at the main AIDA Website-www.2aida.org-and over 60,000 copies of the AIDA program have been downloaded free-of-charge. This column documents the results of a semi-automated analysis of comments left by Website visitors while they were downloading the AIDA software, before they had a chance to use the program. The Internet-based survey methodology and semi-automated analysis were both found to be robust and reliable. Over a 5-month period (from October 3, 2001 to February 28, 2002) 400 responses were received. During the corresponding period 1,770 actual visits were made to the Website survey page-giving a response rate to this proof-of-concept study of 22.6%. Responses were received from participants in over 54 countries-with nearly half of these (n = 194; 48.5%) originating from the United States, United Kingdom, and Canada; 208 responses (52.0%) were received from patients with diabetes, 50 (12.5%) from doctors, 49 (12.3%) from relatives of patients, with fewer responses from students, diabetes educators, nurses, pharmacists, and other end users. The semi-automated analysis adopted for this study has re-affirmed the feasibility of using the Internet to obtain free-text comments, at no real cost, from a substantial number of medical software downloaders/users. The survey has also offered some insight into why members of the public continue to turn to the Internet for medical information. Furthermore it has provided useful information about why people are actually downloading the AIDA v4.3a interactive educational "virtual diabetes patient" simulator.

Automated Sensitivity Analysis of Interplanetary Trajectories for Optimal Mission Design

NASA Technical Reports Server (NTRS)

Knittel, Jeremy; Hughes, Kyle; Englander, Jacob; Sarli, Bruno

2017-01-01

This work describes a suite of Python tools known as the Python EMTG Automated Trade Study Application (PEATSA). PEATSA was written to automate the operation of trajectory optimization software, simplify the process of performing sensitivity analysis, and was ultimately found to out-perform a human trajectory designer in unexpected ways. These benefits will be discussed and demonstrated on sample mission designs.

PleurAlert: an augmented chest drainage system with electronic sensing, automated alerts and internet connectivity.

PubMed

Leeson, Cory E; Weaver, Robert A; Bissell, Taylor; Hoyer, Rachel; McClain, Corinne; Nelson, Douglas A; Samosky, Joseph T

2012-01-01

We have enhanced a common medical device, the chest tube drainage container, with electronic sensing of fluid volume, automated detection of critical alarm conditions and the ability to automatically send alert text messages to a nurse's cell phone. The PleurAlert system provides a simple touch-screen interface and can graphically display chest tube output over time. Our design augments a device whose basic function dates back 50 years by adding technology to automate and optimize a monitoring process that can be time consuming and inconvenient for nurses. The system may also enhance detection of emergency conditions and speed response time.

Automated Assignment of MS/MS Cleavable Cross-Links in Protein 3D-Structure Analysis

NASA Astrophysics Data System (ADS)

Götze, Michael; Pettelkau, Jens; Fritzsche, Romy; Ihling, Christian H.; Schäfer, Mathias; Sinz, Andrea

2015-01-01

CID-MS/MS cleavable cross-linkers hold an enormous potential for an automated analysis of cross-linked products, which is essential for conducting structural proteomics studies. The created characteristic fragment ion patterns can easily be used for an automated assignment and discrimination of cross-linked products. To date, there are only a few software solutions available that make use of these properties, but none allows for an automated analysis of cleavable cross-linked products. The MeroX software fills this gap and presents a powerful tool for protein 3D-structure analysis in combination with MS/MS cleavable cross-linkers. We show that MeroX allows an automatic screening of characteristic fragment ions, considering static and variable peptide modifications, and effectively scores different types of cross-links. No manual input is required for a correct assignment of cross-links and false discovery rates are calculated. The self-explanatory graphical user interface of MeroX provides easy access for an automated cross-link search platform that is compatible with commonly used data file formats, enabling analysis of data originating from different instruments. The combination of an MS/MS cleavable cross-linker with a dedicated software tool for data analysis provides an automated workflow for 3D-structure analysis of proteins. MeroX is available at www.StavroX.com .

Design and operational energy studies in a new high-rise office building. Volume 4. Building automation analysis

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

Not Available

1984-03-01

The objectives of the analysis are to evaluate the application of a number of building automation system capabilities using the Park Plaza Building as a case study. The study looks at the energy and cost effectiveness of some energy management strategies of the building automation system as well as some energy management strategies that are not currently a part of the building automation system. The strategies are also evaluated in terms of their reliability and usefulness in this building.

Retina Image Analysis and Ocular Telehealth: The Oak Ridge National Laboratory-Hamilton Eye Institute Case Study

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

Karnowski, Thomas Paul; Giancardo, Luca; Li, Yaquin

2013-01-01

Automated retina image analysis has reached a high level of maturity in recent years, and thus the question of how validation is performed in these systems is beginning to grow in importance. One application of retina image analysis is in telemedicine, where an automated system could enable the automated detection of diabetic retinopathy and other eye diseases as a low-cost method for broad-based screening. In this work we discuss our experiences in developing a telemedical network for retina image analysis, including our progression from a manual diagnosis network to a more fully automated one. We pay special attention to howmore » validations of our algorithm steps are performed, both using data from the telemedicine network and other public databases.« less

Effective use of latent semantic indexing and computational linguistics in biological and biomedical applications.

PubMed

Chen, Hongyu; Martin, Bronwen; Daimon, Caitlin M; Maudsley, Stuart

2013-01-01

Text mining is rapidly becoming an essential technique for the annotation and analysis of large biological data sets. Biomedical literature currently increases at a rate of several thousand papers per week, making automated information retrieval methods the only feasible method of managing this expanding corpus. With the increasing prevalence of open-access journals and constant growth of publicly-available repositories of biomedical literature, literature mining has become much more effective with respect to the extraction of biomedically-relevant data. In recent years, text mining of popular databases such as MEDLINE has evolved from basic term-searches to more sophisticated natural language processing techniques, indexing and retrieval methods, structural analysis and integration of literature with associated metadata. In this review, we will focus on Latent Semantic Indexing (LSI), a computational linguistics technique increasingly used for a variety of biological purposes. It is noted for its ability to consistently outperform benchmark Boolean text searches and co-occurrence models at information retrieval and its power to extract indirect relationships within a data set. LSI has been used successfully to formulate new hypotheses, generate novel connections from existing data, and validate empirical data.

Automated tumor analysis for molecular profiling in lung cancer

PubMed Central

Boyd, Clinton; James, Jacqueline A.; Loughrey, Maurice B.; Hougton, Joseph P.; Boyle, David P.; Kelly, Paul; Maxwell, Perry; McCleary, David; Diamond, James; McArt, Darragh G.; Tunstall, Jonathon; Bankhead, Peter; Salto-Tellez, Manuel

2015-01-01

The discovery and clinical application of molecular biomarkers in solid tumors, increasingly relies on nucleic acid extraction from FFPE tissue sections and subsequent molecular profiling. This in turn requires the pathological review of haematoxylin & eosin (H&E) stained slides, to ensure sample quality, tumor DNA sufficiency by visually estimating the percentage tumor nuclei and tumor annotation for manual macrodissection. In this study on NSCLC, we demonstrate considerable variation in tumor nuclei percentage between pathologists, potentially undermining the precision of NSCLC molecular evaluation and emphasising the need for quantitative tumor evaluation. We subsequently describe the development and validation of a system called TissueMark for automated tumor annotation and percentage tumor nuclei measurement in NSCLC using computerized image analysis. Evaluation of 245 NSCLC slides showed precise automated tumor annotation of cases using Tissuemark, strong concordance with manually drawn boundaries and identical EGFR mutational status, following manual macrodissection from the image analysis generated tumor boundaries. Automated analysis of cell counts for % tumor measurements by Tissuemark showed reduced variability and significant correlation (p < 0.001) with benchmark tumor cell counts. This study demonstrates a robust image analysis technology that can facilitate the automated quantitative analysis of tissue samples for molecular profiling in discovery and diagnostics. PMID:26317646

Enforced Sparse Non-Negative Matrix Factorization

DTIC Science & Technology

2016-01-23

documents to find interesting pieces of information. With limited resources, analysts often employ automated text - mining tools that highlight common...represented as an undirected bipartite graph. It has become a common method for generating topic models of text data because it is known to produce good results...model and the convergence rate of the underlying algorithm. I. Introduction A common analyst challenge is searching through large quantities of text

Helping Students Select Appropriately Challenging Text: Application to a Test of Second Language Reading Ability. Research Report. ETS RR-17-33

ERIC Educational Resources Information Center

Sheehan, Kathleen M.

2017-01-01

A model-based approach for matching language learners to texts of appropriate difficulty is described. Results are communicated to test takers via a targeted reading range expressed on the reporting scale of an automated text complexity measurement tool (ATCMT). Test takers can use this feedback to select reading materials that are well matched to…

Using collaborative technologies in remote lab delivery systems for topics in automation

NASA Astrophysics Data System (ADS)

Ashby, Joe E.

Lab exercises are a pedagogically essential component of engineering and technology education. Distance education remote labs are being developed which enable students to access lab facilities via the Internet. Collaboration, students working in teams, enhances learning activity through the development of communication skills, sharing observations and problem solving. Web meeting communication tools are currently used in remote labs. The problem identified for investigation was that no standards of practice or paradigms exist to guide remote lab designers in the selection of collaboration tools that best support learning achievement. The goal of this work was to add to the body of knowledge involving the selection and use of remote lab collaboration tools. Experimental research was conducted where the participants were randomly assigned to three communication treatments and learning achievement was measured via assessments at the completion of each of six remote lab based lessons. Quantitative instruments used for assessing learning achievement were implemented, along with a survey to correlate user preference with collaboration treatments. A total of 53 undergraduate technology students worked in two-person teams, where each team was assigned one of the treatments, namely (a) text messaging chat, (b) voice chat, or (c) webcam video with voice chat. Each had little experience with the subject matter involving automation, but possessed the necessary technical background. Analysis of the assessment score data included mean and standard deviation, confirmation of the homogeneity of variance, a one-way ANOVA test and post hoc comparisons. The quantitative and qualitative data indicated that text messaging chat negatively impacted learning achievement and that text messaging chat was not preferred. The data also suggested that the subjects were equally divided on preference to voice chat verses webcam video with voice chat. To the end of designing collaborative communication tools for remote labs involving automation equipment, the results of this work points to making voice chat the default method of communication; but the webcam video with voice chat option should be included. Standards are only beginning to be developed for the design of remote lab systems. Research, design and innovation involving collaboration and presence should be included.

Automated X-ray image analysis for cargo security: Critical review and future promise.

PubMed

Rogers, Thomas W; Jaccard, Nicolas; Morton, Edward J; Griffin, Lewis D

2017-01-01

We review the relatively immature field of automated image analysis for X-ray cargo imagery. There is increasing demand for automated analysis methods that can assist in the inspection and selection of containers, due to the ever-growing volumes of traded cargo and the increasing concerns that customs- and security-related threats are being smuggled across borders by organised crime and terrorist networks. We split the field into the classical pipeline of image preprocessing and image understanding. Preprocessing includes: image manipulation; quality improvement; Threat Image Projection (TIP); and material discrimination and segmentation. Image understanding includes: Automated Threat Detection (ATD); and Automated Contents Verification (ACV). We identify several gaps in the literature that need to be addressed and propose ideas for future research. Where the current literature is sparse we borrow from the single-view, multi-view, and CT X-ray baggage domains, which have some characteristics in common with X-ray cargo.

An automated, broad-based, near real-time public health surveillance system using presentations to hospital Emergency Departments in New South Wales, Australia

PubMed Central

Muscatello, David J; Churches, Tim; Kaldor, Jill; Zheng, Wei; Chiu, Clayton; Correll, Patricia; Jorm, Louisa

2005-01-01

Background In a climate of concern over bioterrorism threats and emergent diseases, public health authorities are trialling more timely surveillance systems. The 2003 Rugby World Cup (RWC) provided an opportunity to test the viability of a near real-time syndromic surveillance system in metropolitan Sydney, Australia. We describe the development and early results of this largely automated system that used data routinely collected in Emergency Departments (EDs). Methods Twelve of 49 EDs in the Sydney metropolitan area automatically transmitted surveillance data from their existing information systems to a central database in near real-time. Information captured for each ED visit included patient demographic details, presenting problem and nursing assessment entered as free-text at triage time, physician-assigned provisional diagnosis codes, and status at departure from the ED. Both diagnoses from the EDs and triage text were used to assign syndrome categories. The text information was automatically classified into one or more of 26 syndrome categories using automated "naïve Bayes" text categorisation techniques. Automated processes were used to analyse both diagnosis and free text-based syndrome data and to produce web-based statistical summaries for daily review. An adjusted cumulative sum (cusum) was used to assess the statistical significance of trends. Results During the RWC the system did not identify any major public health threats associated with the tournament, mass gatherings or the influx of visitors. This was consistent with evidence from other sources, although two known outbreaks were already in progress before the tournament. Limited baseline in early monitoring prevented the system from automatically identifying these ongoing outbreaks. Data capture was invisible to clinical staff in EDs and did not add to their workload. Conclusion We have demonstrated the feasibility and potential utility of syndromic surveillance using routinely collected data from ED information systems. Key features of our system are its nil impact on clinical staff, and its use of statistical methods to assign syndrome categories based on clinical free text information. The system is ongoing, and has expanded to cover 30 EDs. Results of formal evaluations of both the technical efficiency and the public health impacts of the system will be described subsequently. PMID:16372902

Development of a personalized bidirectional text messaging tool for HIV adherence assessment and intervention among substance abusers.

PubMed

Ingersoll, Karen; Dillingham, Rebecca; Reynolds, George; Hettema, Jennifer; Freeman, Jason; Hosseinbor, Sharzad; Winstead-Derlega, Chris

2014-01-01

We describe the development of a two-way text messaging intervention tool for substance users who are non-adherent with HIV medications, and examine message flow data for feasibility and acceptability. The assessment and intervention tool, TxText, is fully automated, sending participants mood, substance use, and medication adherence queries by text message. Participants respond, the tool recognizes the category of response, and sends the personalized intervention message that participants designed in return. In 10months, the tool sent 16,547 messages (half initial, half follow-up) to 31 participants assigned to the TxText condition, who sent 6711 messages in response to the initial messages. Response rates to substance use (n=2370), medication (n=2918) and mood (n=4639) queries were 67, 69, and 64%, respectively. Responses indicating medication adherence, abstinence from substances, and good moods were more common than negative responses. The TxText tool can send messages daily over a 3month period, receive responses, and decode them to deliver personalized affirming or intervention messages. While we await the outcomes of a pilot randomized trial, the process analysis shows that TxText is acceptable and feasible for substance abusers with HIV, and may serve as a complement to HIV medical care. © 2013.

Development of a Personalized Bidirectional Text Messaging Tool for HIV Adherence Assessment and Intervention among Substance Abusers

PubMed Central

Ingersoll, Karen; Dillingham, Rebecca; Reynolds, George; Hettema, Jennifer; Freeman, Jason; Hosseinbor, Sharzad; Winstead-Derlega, Chris

2013-01-01

We describe the development of a two-way text messaging intervention tool for substance users who are non-adherent with HIV medications, and examine message flow data for feasibility and acceptability. The assessment and intervention tool, TxText, is fully automated, sending participants mood, substance use, and medication adherence queries by text message. Participants respond, the tool recognizes the category of response, and sends the personalized intervention message that participants designed in return. In 10 months, the tool sent 16,547 messages (half initial, half follow-up) to 31 participants assigned to the TxText condition, who sent 6711 messages in response to the initial messages. Response rates to substance use (n=2370), medication (n=2918) and mood (n=4639) queries were 67%, 69%, and 64%, respectively. Responses indicating medication adherence, abstinence from substances, and good moods were more common than negative responses. The TxText tool can send messages daily over a 3 month period, receive responses, and decode them to deliver personalized affirming or intervention messages. While we await the outcomes of a pilot randomized trial, the process analysis shows that TxText is acceptable and feasible for substance abusers with HIV, and may serve as a complement to HIV medical care. PMID:24029625

Fully automated corneal endothelial morphometry of images captured by clinical specular microscopy

NASA Astrophysics Data System (ADS)

Bucht, Curry; Söderberg, Per; Manneberg, Göran

2009-02-01

The corneal endothelium serves as the posterior barrier of the cornea. Factors such as clarity and refractive properties of the cornea are in direct relationship to the quality of the endothelium. The endothelial cell density is considered the most important morphological factor. Morphometry of the corneal endothelium is presently done by semi-automated analysis of pictures captured by a Clinical Specular Microscope (CSM). Because of the occasional need of operator involvement, this process can be tedious, having a negative impact on sampling size. This study was dedicated to the development of fully automated analysis of images of the corneal endothelium, captured by CSM, using Fourier analysis. Software was developed in the mathematical programming language Matlab. Pictures of the corneal endothelium, captured by CSM, were read into the analysis software. The software automatically performed digital enhancement of the images. The digitally enhanced images of the corneal endothelium were transformed, using the fast Fourier transform (FFT). Tools were developed and applied for identification and analysis of relevant characteristics of the Fourier transformed images. The data obtained from each Fourier transformed image was used to calculate the mean cell density of its corresponding corneal endothelium. The calculation was based on well known diffraction theory. Results in form of estimated cell density of the corneal endothelium were obtained, using fully automated analysis software on images captured by CSM. The cell density obtained by the fully automated analysis was compared to the cell density obtained from classical, semi-automated analysis and a relatively large correlation was found.

CANEapp: a user-friendly application for automated next generation transcriptomic data analysis.

PubMed

Velmeshev, Dmitry; Lally, Patrick; Magistri, Marco; Faghihi, Mohammad Ali

2016-01-13

Next generation sequencing (NGS) technologies are indispensable for molecular biology research, but data analysis represents the bottleneck in their application. Users need to be familiar with computer terminal commands, the Linux environment, and various software tools and scripts. Analysis workflows have to be optimized and experimentally validated to extract biologically meaningful data. Moreover, as larger datasets are being generated, their analysis requires use of high-performance servers. To address these needs, we developed CANEapp (application for Comprehensive automated Analysis of Next-generation sequencing Experiments), a unique suite that combines a Graphical User Interface (GUI) and an automated server-side analysis pipeline that is platform-independent, making it suitable for any server architecture. The GUI runs on a PC or Mac and seamlessly connects to the server to provide full GUI control of RNA-sequencing (RNA-seq) project analysis. The server-side analysis pipeline contains a framework that is implemented on a Linux server through completely automated installation of software components and reference files. Analysis with CANEapp is also fully automated and performs differential gene expression analysis and novel noncoding RNA discovery through alternative workflows (Cuffdiff and R packages edgeR and DESeq2). We compared CANEapp to other similar tools, and it significantly improves on previous developments. We experimentally validated CANEapp's performance by applying it to data derived from different experimental paradigms and confirming the results with quantitative real-time PCR (qRT-PCR). CANEapp adapts to any server architecture by effectively using available resources and thus handles large amounts of data efficiently. CANEapp performance has been experimentally validated on various biological datasets. CANEapp is available free of charge at http://psychiatry.med.miami.edu/research/laboratory-of-translational-rna-genomics/CANE-app . We believe that CANEapp will serve both biologists with no computational experience and bioinformaticians as a simple, timesaving but accurate and powerful tool to analyze large RNA-seq datasets and will provide foundations for future development of integrated and automated high-throughput genomics data analysis tools. Due to its inherently standardized pipeline and combination of automated analysis and platform-independence, CANEapp is an ideal for large-scale collaborative RNA-seq projects between different institutions and research groups.

Using statistical text classification to identify health information technology incidents

PubMed Central

Chai, Kevin E K; Anthony, Stephen; Coiera, Enrico; Magrabi, Farah

2013-01-01

Objective To examine the feasibility of using statistical text classification to automatically identify health information technology (HIT) incidents in the USA Food and Drug Administration (FDA) Manufacturer and User Facility Device Experience (MAUDE) database. Design We used a subset of 570 272 incidents including 1534 HIT incidents reported to MAUDE between 1 January 2008 and 1 July 2010. Text classifiers using regularized logistic regression were evaluated with both ‘balanced’ (50% HIT) and ‘stratified’ (0.297% HIT) datasets for training, validation, and testing. Dataset preparation, feature extraction, feature selection, cross-validation, classification, performance evaluation, and error analysis were performed iteratively to further improve the classifiers. Feature-selection techniques such as removing short words and stop words, stemming, lemmatization, and principal component analysis were examined. Measurements κ statistic, F1 score, precision and recall. Results Classification performance was similar on both the stratified (0.954 F1 score) and balanced (0.995 F1 score) datasets. Stemming was the most effective technique, reducing the feature set size to 79% while maintaining comparable performance. Training with balanced datasets improved recall (0.989) but reduced precision (0.165). Conclusions Statistical text classification appears to be a feasible method for identifying HIT reports within large databases of incidents. Automated identification should enable more HIT problems to be detected, analyzed, and addressed in a timely manner. Semi-supervised learning may be necessary when applying machine learning to big data analysis of patient safety incidents and requires further investigation. PMID:23666777

AUTOMATED ANALYSIS OF AQUEOUS SAMPLES CONTAINING PESTICIDES, ACIDIC/BASIC/NEUTRAL SEMIVOLATILES AND VOLATILE ORGANIC COMPOUNDS BY SOLID PHASE EXTRACTION COUPLED IN-LINE TO LARGE VOLUME INJECTION GC/MS

EPA Science Inventory

Data is presented on the development of a new automated system combining solid phase extraction (SPE) with GC/MS spectrometry for the single-run analysis of water samples containing a broad range of organic compounds. The system uses commercially available automated in-line 10-m...

Computer-Based Automation of Discrete Product Manufacture: A preliminary Discussion of Feasibility and Impact

DTIC Science & Technology

1974-07-01

automated manufacturing processes and a rough technoeconomic evaluation of those concepts. Our evaluation is largely based on estimates; therefore, the...must be subjected to thorough analysis and experimental verification before they can be considered definitive. They are being published at this time...hardware and sensor technology, manufacturing engineering, automation, and economic analysis . Members of this team inspected over thirty manufacturing

Identifying sports videos using replay, text, and camera motion features

NASA Astrophysics Data System (ADS)

Kobla, Vikrant; DeMenthon, Daniel; Doermann, David S.

1999-12-01

Automated classification of digital video is emerging as an important piece of the puzzle in the design of content management systems for digital libraries. The ability to classify videos into various classes such as sports, news, movies, or documentaries, increases the efficiency of indexing, browsing, and retrieval of video in large databases. In this paper, we discuss the extraction of features that enable identification of sports videos directly from the compressed domain of MPEG video. These features include detecting the presence of action replays, determining the amount of scene text in vide, and calculating various statistics on camera and/or object motion. The features are derived from the macroblock, motion,and bit-rate information that is readily accessible from MPEG video with very minimal decoding, leading to substantial gains in processing speeds. Full-decoding of selective frames is required only for text analysis. A decision tree classifier built using these features is able to identify sports clips with an accuracy of about 93 percent.

Model-centric distribution automation: Capacity, reliability, and efficiency

DOE PAGES

Onen, Ahmet; Jung, Jaesung; Dilek, Murat; ...

2016-02-26

A series of analyses along with field validations that evaluate efficiency, reliability, and capacity improvements of model-centric distribution automation are presented. With model-centric distribution automation, the same model is used from design to real-time control calculations. A 14-feeder system with 7 substations is considered. The analyses involve hourly time-varying loads and annual load growth factors. Phase balancing and capacitor redesign modifications are used to better prepare the system for distribution automation, where the designs are performed considering time-varying loads. Coordinated control of load tap changing transformers, line regulators, and switched capacitor banks is considered. In evaluating distribution automation versus traditionalmore » system design and operation, quasi-steady-state power flow analysis is used. In evaluating distribution automation performance for substation transformer failures, reconfiguration for restoration analysis is performed. In evaluating distribution automation for storm conditions, Monte Carlo simulations coupled with reconfiguration for restoration calculations are used. As a result, the evaluations demonstrate that model-centric distribution automation has positive effects on system efficiency, capacity, and reliability.« less

Model-centric distribution automation: Capacity, reliability, and efficiency

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

Onen, Ahmet; Jung, Jaesung; Dilek, Murat

A series of analyses along with field validations that evaluate efficiency, reliability, and capacity improvements of model-centric distribution automation are presented. With model-centric distribution automation, the same model is used from design to real-time control calculations. A 14-feeder system with 7 substations is considered. The analyses involve hourly time-varying loads and annual load growth factors. Phase balancing and capacitor redesign modifications are used to better prepare the system for distribution automation, where the designs are performed considering time-varying loads. Coordinated control of load tap changing transformers, line regulators, and switched capacitor banks is considered. In evaluating distribution automation versus traditionalmore » system design and operation, quasi-steady-state power flow analysis is used. In evaluating distribution automation performance for substation transformer failures, reconfiguration for restoration analysis is performed. In evaluating distribution automation for storm conditions, Monte Carlo simulations coupled with reconfiguration for restoration calculations are used. As a result, the evaluations demonstrate that model-centric distribution automation has positive effects on system efficiency, capacity, and reliability.« less

Automated RTOP Management System

NASA Technical Reports Server (NTRS)

Hayes, P.

1984-01-01

The structure of NASA's Office of Aeronautics and Space Technology electronic information system network from 1983 to 1985 is illustrated. The RTOP automated system takes advantage of existing hardware, software, and expertise, and provides: (1) computerized cover sheet and resources forms; (2) electronic signature and transmission; (3) a data-based information system; (4) graphics; (5) intercenter communications; (6) management information; and (7) text editing. The system is coordinated with Headquarters efforts in codes R,E, and T.

Cervical screening programmes: can automation help? Evidence from systematic reviews, an economic analysis and a simulation modelling exercise applied to the UK.

PubMed

Willis, B H; Barton, P; Pearmain, P; Bryan, S; Hyde, C

2005-03-01

To assess the effectiveness and cost-effectiveness of adding automated image analysis to cervical screening programmes. Searching of all major electronic databases to the end of 2000 was supplemented by a detailed survey for unpublished UK literature. Four systematic reviews were conducted according to recognised guidance. The review of 'clinical effectiveness' included studies assessing reproducibility and impact on health outcomes and processes in addition to evaluations of test accuracy. A discrete event simulation model was developed, although the economic evaluation ultimately relied on a cost-minimisation analysis. The predominant finding from the systematic reviews was the very limited amount of rigorous primary research. None of the included studies refers to the only commercially available automated image analysis device in 2002, the AutoPap Guided Screening (GS) System. The results of the included studies were debatably most compatible with automated image analysis being equivalent in test performance to manual screening. Concerning process, there was evidence that automation does lead to reductions in average slide processing times. In the PRISMATIC trial this was reduced from 10.4 to 3.9 minutes, a statistically significant and practically important difference. The economic evaluation tentatively suggested that the AutoPap GS System may be efficient. The key proviso is that credible data become available to support that the AutoPap GS System has test performance and processing times equivalent to those obtained for PAPNET. The available evidence is still insufficient to recommend implementation of automated image analysis systems. The priority for action remains further research, particularly the 'clinical effectiveness' of the AutoPap GS System. Assessing the cost-effectiveness of introducing automation alongside other approaches is also a priority.

Advancing haemostasis automation--successful implementation of robotic centrifugation and sample processing in a tertiary service hospital.

PubMed

Sédille-Mostafaie, Nazanin; Engler, Hanna; Lutz, Susanne; Korte, Wolfgang

2013-06-01

Laboratories today face increasing pressure to automate operations due to increasing workloads and the need to reduce expenditure. Few studies to date have focussed on the laboratory automation of preanalytical coagulation specimen processing. In the present study, we examined whether a clinical chemistry automation protocol meets the preanalytical requirements for the analyses of coagulation. During the implementation of laboratory automation, we began to operate a pre- and postanalytical automation system. The preanalytical unit processes blood specimens for chemistry, immunology and coagulation by automated specimen processing. As the production of platelet-poor plasma is highly dependent on optimal centrifugation, we examined specimen handling under different centrifugation conditions in order to produce optimal platelet deficient plasma specimens. To this end, manually processed models centrifuged at 1500 g for 5 and 20 min were compared to an automated centrifugation model at 3000 g for 7 min. For analytical assays that are performed frequently enough to be targets for full automation, Passing-Bablok regression analysis showed close agreement between different centrifugation methods, with a correlation coefficient between 0.98 and 0.99 and a bias between -5% and +6%. For seldom performed assays that do not mandate full automation, the Passing-Bablok regression analysis showed acceptable to poor agreement between different centrifugation methods. A full automation solution is suitable and can be recommended for frequent haemostasis testing.

Combined process automation for large-scale EEG analysis.

PubMed

Sfondouris, John L; Quebedeaux, Tabitha M; Holdgraf, Chris; Musto, Alberto E

2012-01-01

Epileptogenesis is a dynamic process producing increased seizure susceptibility. Electroencephalography (EEG) data provides information critical in understanding the evolution of epileptiform changes throughout epileptic foci. We designed an algorithm to facilitate efficient large-scale EEG analysis via linked automation of multiple data processing steps. Using EEG recordings obtained from electrical stimulation studies, the following steps of EEG analysis were automated: (1) alignment and isolation of pre- and post-stimulation intervals, (2) generation of user-defined band frequency waveforms, (3) spike-sorting, (4) quantification of spike and burst data and (5) power spectral density analysis. This algorithm allows for quicker, more efficient EEG analysis. Copyright © 2011 Elsevier Ltd. All rights reserved.

The registry case finding engine: an automated tool to identify cancer cases from unstructured, free-text pathology reports and clinical notes.

PubMed

Hanauer, David A; Miela, Gretchen; Chinnaiyan, Arul M; Chang, Alfred E; Blayney, Douglas W

2007-11-01

The American College of Surgeons mandates the maintenance of a cancer registry for hospitals seeking accreditation. At the University of Michigan Health System, more than 90% of all registry patients are identified by manual review, a method common to many institutions. We hypothesized that an automated computer system could accurately perform this time- and labor-intensive task. We created a tool to automatically scan free-text medical documents for terms relevant to cancer. We developed custom-made lists containing approximately 2,500 terms and phrases and 800 SNOMED codes. Text is processed by the Case Finding Engine (CaFE), and relevant terms are highlighted for review by a registrar and used to populate the registry database. We tested our system by comparing results from the CaFE to those by trained registrars who read through 2,200 pathology reports and marked relevant cases for the registry. The clinical documentation (eg, electronic chart notes) of an additional 476 patients was also reviewed by registrars and compared with the automated process by the CaFE. For pathology reports, the sensitivity for automated case identification was 100%, but specificity was 85.0%. For clinical documentation, sensitivity was 100% and specificity was 73.7%. Types of errors made by the CaFE were categorized to direct additional improvements. Use of the CaFE has resulted in a considerable increase in the number of cases added to the registry each month. The system has been well accepted by our registrars. CaFE can improve the accuracy and efficiency of tumor registry personnel and helps ensure that cancer cases are not overlooked.

Automated urinalysis: first experiences and a comparison between the Iris iQ200 urine microscopy system, the Sysmex UF-100 flow cytometer and manual microscopic particle counting.

PubMed

Shayanfar, Noushin; Tobler, Ulrich; von Eckardstein, Arnold; Bestmann, Lukas

2007-01-01

Automated analysis of insoluble urine components can reduce the workload of conventional microscopic examination of urine sediment and is possibly helpful for standardization. We compared the diagnostic performance of two automated urine sediment analyzers and combined dipstick/automated urine analysis with that of the traditional dipstick/microscopy algorithm. A total of 332 specimens were collected and analyzed for insoluble urine components by microscopy and automated analyzers, namely the Iris iQ200 (Iris Diagnostics) and the UF-100 flow cytometer (Sysmex). The coefficients of variation for day-to-day quality control of the iQ200 and UF-100 analyzers were 6.5% and 5.5%, respectively, for red blood cells. We reached accuracy ranging from 68% (bacteria) to 97% (yeast) for the iQ200 and from 42% (bacteria) to 93% (yeast) for the UF-100. The combination of dipstick and automated urine sediment analysis increased the sensitivity of screening to approximately 98%. We conclude that automated urine sediment analysis is sufficiently precise and improves the workflow in a routine laboratory. In addition, it allows sediment analysis of all urine samples and thereby helps to detect pathological samples that would have been missed in the conventional two-step procedure according to the European guidelines. Although it is not a substitute for microscopic sediment examination, it can, when combined with dipstick testing, reduce the number of specimens submitted to microscopy. Visual microscopy is still required for some samples, namely, dysmorphic erythrocytes, yeasts, Trichomonas, oval fat bodies, differentiation of casts and certain crystals.

Manual versus Automated Narrative Analysis of Agrammatic Production Patterns: The Northwestern Narrative Language Analysis and Computerized Language Analysis

ERIC Educational Resources Information Center

Hsu, Chien-Ju; Thompson, Cynthia K.

2018-01-01

Purpose: The purpose of this study is to compare the outcomes of the manually coded Northwestern Narrative Language Analysis (NNLA) system, which was developed for characterizing agrammatic production patterns, and the automated Computerized Language Analysis (CLAN) system, which has recently been adopted to analyze speech samples of individuals…

Analysis of Trinity Power Metrics for Automated Monitoring

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

Michalenko, Ashley Christine

This is a presentation from Los Alamos National Laboraotyr (LANL) about the analysis of trinity power metrics for automated monitoring. The following topics are covered: current monitoring efforts, motivation for analysis, tools used, the methodology, work performed during the summer, and future work planned.

Automatic de-identification of textual documents in the electronic health record: a review of recent research

PubMed Central

2010-01-01

Background In the United States, the Health Insurance Portability and Accountability Act (HIPAA) protects the confidentiality of patient data and requires the informed consent of the patient and approval of the Internal Review Board to use data for research purposes, but these requirements can be waived if data is de-identified. For clinical data to be considered de-identified, the HIPAA "Safe Harbor" technique requires 18 data elements (called PHI: Protected Health Information) to be removed. The de-identification of narrative text documents is often realized manually, and requires significant resources. Well aware of these issues, several authors have investigated automated de-identification of narrative text documents from the electronic health record, and a review of recent research in this domain is presented here. Methods This review focuses on recently published research (after 1995), and includes relevant publications from bibliographic queries in PubMed, conference proceedings, the ACM Digital Library, and interesting publications referenced in already included papers. Results The literature search returned more than 200 publications. The majority focused only on structured data de-identification instead of narrative text, on image de-identification, or described manual de-identification, and were therefore excluded. Finally, 18 publications describing automated text de-identification were selected for detailed analysis of the architecture and methods used, the types of PHI detected and removed, the external resources used, and the types of clinical documents targeted. All text de-identification systems aimed to identify and remove person names, and many included other types of PHI. Most systems used only one or two specific clinical document types, and were mostly based on two different groups of methodologies: pattern matching and machine learning. Many systems combined both approaches for different types of PHI, but the majority relied only on pattern matching, rules, and dictionaries. Conclusions In general, methods based on dictionaries performed better with PHI that is rarely mentioned in clinical text, but are more difficult to generalize. Methods based on machine learning tend to perform better, especially with PHI that is not mentioned in the dictionaries used. Finally, the issues of anonymization, sufficient performance, and "over-scrubbing" are discussed in this publication. PMID:20678228

Automatic de-identification of textual documents in the electronic health record: a review of recent research.

PubMed

Meystre, Stephane M; Friedlin, F Jeffrey; South, Brett R; Shen, Shuying; Samore, Matthew H

2010-08-02

In the United States, the Health Insurance Portability and Accountability Act (HIPAA) protects the confidentiality of patient data and requires the informed consent of the patient and approval of the Internal Review Board to use data for research purposes, but these requirements can be waived if data is de-identified. For clinical data to be considered de-identified, the HIPAA "Safe Harbor" technique requires 18 data elements (called PHI: Protected Health Information) to be removed. The de-identification of narrative text documents is often realized manually, and requires significant resources. Well aware of these issues, several authors have investigated automated de-identification of narrative text documents from the electronic health record, and a review of recent research in this domain is presented here. This review focuses on recently published research (after 1995), and includes relevant publications from bibliographic queries in PubMed, conference proceedings, the ACM Digital Library, and interesting publications referenced in already included papers. The literature search returned more than 200 publications. The majority focused only on structured data de-identification instead of narrative text, on image de-identification, or described manual de-identification, and were therefore excluded. Finally, 18 publications describing automated text de-identification were selected for detailed analysis of the architecture and methods used, the types of PHI detected and removed, the external resources used, and the types of clinical documents targeted. All text de-identification systems aimed to identify and remove person names, and many included other types of PHI. Most systems used only one or two specific clinical document types, and were mostly based on two different groups of methodologies: pattern matching and machine learning. Many systems combined both approaches for different types of PHI, but the majority relied only on pattern matching, rules, and dictionaries. In general, methods based on dictionaries performed better with PHI that is rarely mentioned in clinical text, but are more difficult to generalize. Methods based on machine learning tend to perform better, especially with PHI that is not mentioned in the dictionaries used. Finally, the issues of anonymization, sufficient performance, and "over-scrubbing" are discussed in this publication.

Automation of the longwall mining system

NASA Technical Reports Server (NTRS)

Zimmerman, W.; Aster, R. W.; Harris, J.; High, J.

1982-01-01

Cost effective, safe, and technologically sound applications of automation technology to underground coal mining were identified. The longwall analysis commenced with a general search for government and industry experience of mining automation technology. A brief industry survey was conducted to identify longwall operational, safety, and design problems. The prime automation candidates resulting from the industry experience and survey were: (1) the shearer operation, (2) shield and conveyor pan line advance, (3) a management information system to allow improved mine logistics support, and (4) component fault isolation and diagnostics to reduce untimely maintenance delays. A system network analysis indicated that a 40% improvement in productivity was feasible if system delays associated with all of the above four areas were removed. A technology assessment and conceptual system design of each of the four automation candidate areas showed that state of the art digital computer, servomechanism, and actuator technologies could be applied to automate the longwall system.

Language Muse: Automated Linguistic Activity Generation for English Language Learners

ERIC Educational Resources Information Center

Madnani, Nitin; Burstein, Jill; Sabatini, John; Biggers, Kietha; Andreyev, Slava

2016-01-01

Current education standards in the U.S. require school students to read and understand complex texts from different subject areas (e.g., social studies). However, such texts usually contain figurative language, complex phrases and sentences, as well as unfamiliar discourse relations. This may present an obstacle to students whose native language…

Automated Tetrahedral Mesh Generation for CFD Analysis of Aircraft in Conceptual Design

NASA Technical Reports Server (NTRS)

Ordaz, Irian; Li, Wu; Campbell, Richard L.

2014-01-01

The paper introduces an automation process of generating a tetrahedral mesh for computational fluid dynamics (CFD) analysis of aircraft configurations in early conceptual design. The method was developed for CFD-based sonic boom analysis of supersonic configurations, but can be applied to aerodynamic analysis of aircraft configurations in any flight regime.

A Meta-Analysis of Factors Influencing the Development of Trust in Automation: Implications for Human-Robot Interaction

DTIC Science & Technology

2014-07-01

Submoderating factors were examined and reported for human-related (i.e., age, cognitive factors, emotive factors) and automation- related (i.e., features and...capabilities) effects. Analyses were also conducted for type of automated aid: cognitive, control, and perceptual automation aids. Automated cognitive...operator, user) action. Perceptual aids are used to assist the operator or user by providing warnings or to assist with pattern recognition. All

Automatic Analysis of Critical Incident Reports: Requirements and Use Cases.

PubMed

Denecke, Kerstin

2016-01-01

Increasingly, critical incident reports are used as a means to increase patient safety and quality of care. The entire potential of these sources of experiential knowledge remains often unconsidered since retrieval and analysis is difficult and time-consuming, and the reporting systems often do not provide support for these tasks. The objective of this paper is to identify potential use cases for automatic methods that analyse critical incident reports. In more detail, we will describe how faceted search could offer an intuitive retrieval of critical incident reports and how text mining could support in analysing relations among events. To realise an automated analysis, natural language processing needs to be applied. Therefore, we analyse the language of critical incident reports and derive requirements towards automatic processing methods. We learned that there is a huge potential for an automatic analysis of incident reports, but there are still challenges to be solved.

Content-specific network analysis of peer-to-peer communication in an online community for smoking cessation.

PubMed

Myneni, Sahiti; Cobb, Nathan K; Cohen, Trevor

2016-01-01

Analysis of user interactions in online communities could improve our understanding of health-related behaviors and inform the design of technological solutions that support behavior change. However, to achieve this we would need methods that provide granular perspective, yet are scalable. In this paper, we present a methodology for high-throughput semantic and network analysis of large social media datasets, combining semi-automated text categorization with social network analytics. We apply this method to derive content-specific network visualizations of 16,492 user interactions in an online community for smoking cessation. Performance of the categorization system was reasonable (average F-measure of 0.74, with system-rater reliability approaching rater-rater reliability). The resulting semantically specific network analysis of user interactions reveals content- and behavior-specific network topologies. Implications for socio-behavioral health and wellness platforms are also discussed.

Automated daily quality control analysis for mammography in a multi-unit imaging center.

PubMed

Sundell, Veli-Matti; Mäkelä, Teemu; Meaney, Alexander; Kaasalainen, Touko; Savolainen, Sauli

2018-01-01

Background The high requirements for mammography image quality necessitate a systematic quality assurance process. Digital imaging allows automation of the image quality analysis, which can potentially improve repeatability and objectivity compared to a visual evaluation made by the users. Purpose To develop an automatic image quality analysis software for daily mammography quality control in a multi-unit imaging center. Material and Methods An automated image quality analysis software using the discrete wavelet transform and multiresolution analysis was developed for the American College of Radiology accreditation phantom. The software was validated by analyzing 60 randomly selected phantom images from six mammography systems and 20 phantom images with different dose levels from one mammography system. The results were compared to a visual analysis made by four reviewers. Additionally, long-term image quality trends of a full-field digital mammography system and a computed radiography mammography system were investigated. Results The automated software produced feature detection levels comparable to visual analysis. The agreement was good in the case of fibers, while the software detected somewhat more microcalcifications and characteristic masses. Long-term follow-up via a quality assurance web portal demonstrated the feasibility of using the software for monitoring the performance of mammography systems in a multi-unit imaging center. Conclusion Automated image quality analysis enables monitoring the performance of digital mammography systems in an efficient, centralized manner.

Video to Text (V2T) in Wide Area Motion Imagery

DTIC Science & Technology

2015-09-01

microtext) or a document (e.g., using Sphinx or Apache NLP ) as an automated approach [102]. Previous work in natural language full-text searching...language processing ( NLP ) based module. The heart of the structured text processing module includes the following seven key word banks...Features Tracker MHT Multiple Hypothesis Tracking MIL Multiple Instance Learning NLP Natural Language Processing OAB Online AdaBoost OF Optic Flow

Comprehensive automation of the solid phase extraction gas chromatographic mass spectrometric analysis (SPE-GC/MS) of opioids, cocaine, and metabolites from serum and other matrices.

PubMed

Lerch, Oliver; Temme, Oliver; Daldrup, Thomas

2014-07-01

The analysis of opioids, cocaine, and metabolites from blood serum is a routine task in forensic laboratories. Commonly, the employed methods include many manual or partly automated steps like protein precipitation, dilution, solid phase extraction, evaporation, and derivatization preceding a gas chromatography (GC)/mass spectrometry (MS) or liquid chromatography (LC)/MS analysis. In this study, a comprehensively automated method was developed from a validated, partly automated routine method. This was possible by replicating method parameters on the automated system. Only marginal optimization of parameters was necessary. The automation relying on an x-y-z robot after manual protein precipitation includes the solid phase extraction, evaporation of the eluate, derivatization (silylation with N-methyl-N-trimethylsilyltrifluoroacetamide, MSTFA), and injection into a GC/MS. A quantitative analysis of almost 170 authentic serum samples and more than 50 authentic samples of other matrices like urine, different tissues, and heart blood on cocaine, benzoylecgonine, methadone, morphine, codeine, 6-monoacetylmorphine, dihydrocodeine, and 7-aminoflunitrazepam was conducted with both methods proving that the analytical results are equivalent even near the limits of quantification (low ng/ml range). To our best knowledge, this application is the first one reported in the literature employing this sample preparation system.

Clinical laboratory urine analysis: comparison of the UriSed automated microscopic analyzer and the manual microscopy.

PubMed

Ma, Junlong; Wang, Chengbin; Yue, Jiaxin; Li, Mianyang; Zhang, Hongrui; Ma, Xiaojing; Li, Xincui; Xue, Dandan; Qing, Xiaoyan; Wang, Shengjiang; Xiang, Daijun; Cong, Yulong

2013-01-01

Several automated urine sediment analyzers have been introduced to clinical laboratories. Automated microscopic pattern recognition is a new technique for urine particle analysis. We evaluated the analytical and diagnostic performance of the UriSed automated microscopic analyzer and compared with manual microscopy for urine sediment analysis. Precision, linearity, carry-over, and method comparison were carried out. A total of 600 urine samples sent for urinalysis were assessed using the UriSed automated microscopic analyzer and manual microscopy. Within-run and between-run precision of the UriSed for red blood cells (RBC) and white blood cells (WBC) were acceptable at all levels (CV < 20%). Within-run and between-run imprecision of the UriSed testing for cast, squamous epithelial cells (EPI), and bacteria (BAC) were good at middle level and high level (CV < 20%). The linearity analysis revealed substantial agreement between the measured value and the theoretical value of the UriSed for RBC, WBC, cast, EPI, and BAC (r > 0.95). There was no carry-over. RBC, WBC, and squamous epithelial cells with sensitivities and specificities were more than 80% in this study. There is substantial agreement between the UriSed automated microscopic analyzer and the manual microscopy methods. The UriSed provides for a rapid turnaround time.

Quantitative analysis of cardiovascular MR images.

PubMed

van der Geest, R J; de Roos, A; van der Wall, E E; Reiber, J H

1997-06-01

The diagnosis of cardiovascular disease requires the precise assessment of both morphology and function. Nearly all aspects of cardiovascular function and flow can be quantified nowadays with fast magnetic resonance (MR) imaging techniques. Conventional and breath-hold cine MR imaging allow the precise and highly reproducible assessment of global and regional left ventricular function. During the same examination, velocity encoded cine (VEC) MR imaging provides measurements of blood flow in the heart and great vessels. Quantitative image analysis often still relies on manual tracing of contours in the images. Reliable automated or semi-automated image analysis software would be very helpful to overcome the limitations associated with the manual and tedious processing of the images. Recent progress in MR imaging of the coronary arteries and myocardial perfusion imaging with contrast media, along with the further development of faster imaging sequences, suggest that MR imaging could evolve into a single technique ('one stop shop') for the evaluation of many aspects of heart disease. As a result, it is very likely that the need for automated image segmentation and analysis software algorithms will further increase. In this paper the developments directed towards the automated image analysis and semi-automated contour detection for cardiovascular MR imaging are presented.

Digital pathology: elementary, rapid and reliable automated image analysis.

PubMed

Bouzin, Caroline; Saini, Monika L; Khaing, Kyi-Kyi; Ambroise, Jérôme; Marbaix, Etienne; Grégoire, Vincent; Bol, Vanesa

2016-05-01

Slide digitalization has brought pathology to a new era, including powerful image analysis possibilities. However, while being a powerful prognostic tool, immunostaining automated analysis on digital images is still not implemented worldwide in routine clinical practice. Digitalized biopsy sections from two independent cohorts of patients, immunostained for membrane or nuclear markers, were quantified with two automated methods. The first was based on stained cell counting through tissue segmentation, while the second relied upon stained area proportion within tissue sections. Different steps of image preparation, such as automated tissue detection, folds exclusion and scanning magnification, were also assessed and validated. Quantification of either stained cells or the stained area was found to be correlated highly for all tested markers. Both methods were also correlated with visual scoring performed by a pathologist. For an equivalent reliability, quantification of the stained area is, however, faster and easier to fine-tune and is therefore more compatible with time constraints for prognosis. This work provides an incentive for the implementation of automated immunostaining analysis with a stained area method in routine laboratory practice. © 2015 John Wiley & Sons Ltd.

An experiment in using open-text comments from the Australian Rural Mental Health Study on health service priorities.

PubMed

Rich, Jane; Handley, Tonelle; Inder, Kerry; Perkins, David

2018-02-01

Conducting research in rural and remote areas is compounded by challenges associated with accessing relatively small populations spread over large geographical areas. Open-ended questions provided in a postal survey format are an advantageous way of including rural and remote residents in research studies. This method means that it is possible to ask for in-depth perspectives, from a large sample, in a relatively resource-efficient way. Such questions are frequently included in population-based surveys; however, they are rarely analysed. The aim of this article is to explore word cloud analysis, to evaluate the utility of automated programs to supplement the analysis of open-ended survey responses. Participants from the Australian Rural Mental Health Study completed the open-ended question 'What health services would you like to see the local health district providing that are currently not available in your area?' A word cloud analysis was then undertaken using the program Wordle; the size of the word in the cloud illustrates how many times, in proportion to other words, a word has appeared in responses, and provides an easily interpretable visual illustration of research results. In total, 388 participants provided a response to the free-text question. Using the word cloud as a visual guide, key words were identified and used to locate relevant quotes from the full open-text responses. \\'Mental health\\' was the most frequent request, cited by 81 people (20.8%). Following mental health, requests for more \\'specialists\\' (n=59) and \\'services\\' (n=53) were the second and third most frequent responses respectively. Visiting specialists were requested by multiple respondents (n=14). Less frequent requests illustrated in the word cloud are important when considering representatives from smaller population groups such as those with specific health needs or conditions including \\'maternity\\' services (n=13), \\'cancer\\' (n=10), \\'drug and alcohol\\' services (n=8), and \\'aged care\\' (n=7) services are all core services even though they were being called for by fewer people. This lesser frequency may suggest that these services are already considered as available in some rural and remote communities. This research aimed to determine whether meaningful and informative data could be obtained from short responses from open-ended survey questions using an automated data analysis technique to supplement a more in-depth analysis. The findings showed that, while not as detailed as interview responses, the open-ended survey questions provided sufficient information to develop a broad overview of the health service priorities identified by this large rural sample. Such automated data analysis techniques are rarely employed; however, the current research provides valuable support for their utility in rural and remote health research. This research has implications for researchers interested in engaging rural and remote residents, demonstrating that meaningful information can be extracted from short survey response data, contributing a resource-efficient supplement to a more detailed analysis. Open-ended questions are often asked in population-based studies yet they are rarely analysed, posing both an opportunity and a challenge for researchers using such participant-driven responses. The lessons learned from the methodology applied can be transferred to other population-based survey studies more widely.

Accuracy of patient-specific organ dose estimates obtained using an automated image segmentation algorithm.

PubMed

Schmidt, Taly Gilat; Wang, Adam S; Coradi, Thomas; Haas, Benjamin; Star-Lack, Josh

2016-10-01

The overall goal of this work is to develop a rapid, accurate, and automated software tool to estimate patient-specific organ doses from computed tomography (CT) scans using simulations to generate dose maps combined with automated segmentation algorithms. This work quantified the accuracy of organ dose estimates obtained by an automated segmentation algorithm. We hypothesized that the autosegmentation algorithm is sufficiently accurate to provide organ dose estimates, since small errors delineating organ boundaries will have minimal effect when computing mean organ dose. A leave-one-out validation study of the automated algorithm was performed with 20 head-neck CT scans expertly segmented into nine regions. Mean organ doses of the automatically and expertly segmented regions were computed from Monte Carlo-generated dose maps and compared. The automated segmentation algorithm estimated the mean organ dose to be within 10% of the expert segmentation for regions other than the spinal canal, with the median error for each organ region below 2%. In the spinal canal region, the median error was [Formula: see text], with a maximum absolute error of 28% for the single-atlas approach and 11% for the multiatlas approach. The results demonstrate that the automated segmentation algorithm can provide accurate organ dose estimates despite some segmentation errors.

Performance analysis of automated evaluation of Crithidia luciliae-based indirect immunofluorescence tests in a routine setting - strengths and weaknesses.

PubMed

Hormann, Wymke; Hahn, Melanie; Gerlach, Stefan; Hochstrate, Nicola; Affeldt, Kai; Giesen, Joyce; Fechner, Kai; Damoiseaux, Jan G M C

2017-11-27

Antibodies directed against dsDNA are a highly specific diagnostic marker for the presence of systemic lupus erythematosus and of particular importance in its diagnosis. To assess anti-dsDNA antibodies, the Crithidia luciliae-based indirect immunofluorescence test (CLIFT) is one of the assays considered to be the best choice. To overcome the drawback of subjective result interpretation that inheres indirect immunofluorescence assays in general, automated systems have been introduced into the market during the last years. Among these systems is the EUROPattern Suite, an advanced automated fluorescence microscope equipped with different software packages, capable of automated pattern interpretation and result suggestion for ANA, ANCA and CLIFT analysis. We analyzed the performance of the EUROPattern Suite with its automated fluorescence interpretation for CLIFT in a routine setting, reflecting the everyday life of a diagnostic laboratory. Three hundred and twelve consecutive samples were collected, sent to the Central Diagnostic Laboratory of the Maastricht University Medical Centre with a request for anti-dsDNA analysis over a period of 7 months. Agreement between EUROPattern assay analysis and the visual read was 93.3%. Sensitivity and specificity were 94.1% and 93.2%, respectively. The EUROPattern Suite performed reliably and greatly supported result interpretation. Automated image acquisition is readily performed and automated image classification gives a reliable recommendation for assay evaluation to the operator. The EUROPattern Suite optimizes workflow and contributes to standardization between different operators or laboratories.

Text-mining analysis of mHealth research.

PubMed

Ozaydin, Bunyamin; Zengul, Ferhat; Oner, Nurettin; Delen, Dursun

2017-01-01

In recent years, because of the advancements in communication and networking technologies, mobile technologies have been developing at an unprecedented rate. mHealth, the use of mobile technologies in medicine, and the related research has also surged parallel to these technological advancements. Although there have been several attempts to review mHealth research through manual processes such as systematic reviews, the sheer magnitude of the number of studies published in recent years makes this task very challenging. The most recent developments in machine learning and text mining offer some potential solutions to address this challenge by allowing analyses of large volumes of texts through semi-automated processes. The objective of this study is to analyze the evolution of mHealth research by utilizing text-mining and natural language processing (NLP) analyses. The study sample included abstracts of 5,644 mHealth research articles, which were gathered from five academic search engines by using search terms such as mobile health, and mHealth. The analysis used the Text Explorer module of JMP Pro 13 and an iterative semi-automated process involving tokenizing, phrasing, and terming. After developing the document term matrix (DTM) analyses such as single value decomposition (SVD), topic, and hierarchical document clustering were performed, along with the topic-informed document clustering approach. The results were presented in the form of word-clouds and trend analyses. There were several major findings regarding research clusters and trends. First, our results confirmed time-dependent nature of terminology use in mHealth research. For example, in earlier versus recent years the use of terminology changed from "mobile phone" to "smartphone" and from "applications" to "apps". Second, ten clusters for mHealth research were identified including (I) Clinical Research on Lifestyle Management, (II) Community Health, (III) Literature Review, (IV) Medical Interventions, (V) Research Design, (VI) Infrastructure, (VII) Applications, (VIII) Research and Innovation in Health Technologies, (IX) Sensor-based Devices and Measurement Algorithms, (X) Survey-based Research. Third, the trend analyses indicated the infrastructure cluster as the highest percentage researched area until 2014. The Research and Innovation in Health Technologies cluster experienced the largest increase in numbers of publications in recent years, especially after 2014. This study is unique because it is the only known study utilizing text-mining analyses to reveal the streams and trends for mHealth research. The fast growth in mobile technologies is expected to lead to higher numbers of studies focusing on mHealth and its implications for various healthcare outcomes. Findings of this study can be utilized by researchers in identifying areas for future studies.

Text-mining analysis of mHealth research

PubMed Central

Zengul, Ferhat; Oner, Nurettin; Delen, Dursun

2017-01-01

In recent years, because of the advancements in communication and networking technologies, mobile technologies have been developing at an unprecedented rate. mHealth, the use of mobile technologies in medicine, and the related research has also surged parallel to these technological advancements. Although there have been several attempts to review mHealth research through manual processes such as systematic reviews, the sheer magnitude of the number of studies published in recent years makes this task very challenging. The most recent developments in machine learning and text mining offer some potential solutions to address this challenge by allowing analyses of large volumes of texts through semi-automated processes. The objective of this study is to analyze the evolution of mHealth research by utilizing text-mining and natural language processing (NLP) analyses. The study sample included abstracts of 5,644 mHealth research articles, which were gathered from five academic search engines by using search terms such as mobile health, and mHealth. The analysis used the Text Explorer module of JMP Pro 13 and an iterative semi-automated process involving tokenizing, phrasing, and terming. After developing the document term matrix (DTM) analyses such as single value decomposition (SVD), topic, and hierarchical document clustering were performed, along with the topic-informed document clustering approach. The results were presented in the form of word-clouds and trend analyses. There were several major findings regarding research clusters and trends. First, our results confirmed time-dependent nature of terminology use in mHealth research. For example, in earlier versus recent years the use of terminology changed from “mobile phone” to “smartphone” and from “applications” to “apps”. Second, ten clusters for mHealth research were identified including (I) Clinical Research on Lifestyle Management, (II) Community Health, (III) Literature Review, (IV) Medical Interventions, (V) Research Design, (VI) Infrastructure, (VII) Applications, (VIII) Research and Innovation in Health Technologies, (IX) Sensor-based Devices and Measurement Algorithms, (X) Survey-based Research. Third, the trend analyses indicated the infrastructure cluster as the highest percentage researched area until 2014. The Research and Innovation in Health Technologies cluster experienced the largest increase in numbers of publications in recent years, especially after 2014. This study is unique because it is the only known study utilizing text-mining analyses to reveal the streams and trends for mHealth research. The fast growth in mobile technologies is expected to lead to higher numbers of studies focusing on mHealth and its implications for various healthcare outcomes. Findings of this study can be utilized by researchers in identifying areas for future studies. PMID:29430456

Cost-benefit analysis on deployment of automated highway systems

DOT National Transportation Integrated Search

1997-01-01

The optimal ranges of traffic flow and capacity will be determined for selected scenarios, in which different proportions of automated and conventional traffic will operate simultaneously in an automated highway system (AHS). It is found that there w...

Small Business Innovations (Automated Information)

NASA Technical Reports Server (NTRS)

1992-01-01

Bruce G. Jackson & Associates Document Director is an automated tool that combines word processing and database management technologies to offer the flexibility and convenience of text processing with the linking capability of database management. Originally developed for NASA, it provides a means to collect and manage information associated with requirements development. The software system was used by NASA in the design of the Assured Crew Return Vehicle, as well as by other government and commercial organizations including the Southwest Research Institute.

Research of the application of the new communication technologies for distribution automation

NASA Astrophysics Data System (ADS)

Zhong, Guoxin; Wang, Hao

2018-03-01

Communication network is a key factor of distribution automation. In recent years, new communication technologies for distribution automation have a rapid development in China. This paper introduces the traditional communication technologies of distribution automation and analyse the defects of these traditional technologies. Then this paper gives a detailed analysis on some new communication technologies for distribution automation including wired communication and wireless communication and then gives an application suggestion of these new technologies.

Comparison of manual versus automated data collection method for an evidence-based nursing practice study.

PubMed

Byrne, M D; Jordan, T R; Welle, T

2013-01-01

The objective of this study was to investigate and improve the use of automated data collection procedures for nursing research and quality assurance. A descriptive, correlational study analyzed 44 orthopedic surgical patients who were part of an evidence-based practice (EBP) project examining post-operative oxygen therapy at a Midwestern hospital. The automation work attempted to replicate a manually-collected data set from the EBP project. Automation was successful in replicating data collection for study data elements that were available in the clinical data repository. The automation procedures identified 32 "false negative" patients who met the inclusion criteria described in the EBP project but were not selected during the manual data collection. Automating data collection for certain data elements, such as oxygen saturation, proved challenging because of workflow and practice variations and the reliance on disparate sources for data abstraction. Automation also revealed instances of human error including computational and transcription errors as well as incomplete selection of eligible patients. Automated data collection for analysis of nursing-specific phenomenon is potentially superior to manual data collection methods. Creation of automated reports and analysis may require initial up-front investment with collaboration between clinicians, researchers and information technology specialists who can manage the ambiguities and challenges of research and quality assurance work in healthcare.

A systematic literature review of automated clinical coding and classification systems

PubMed Central

Williams, Margaret; Fenton, Susan H; Jenders, Robert A; Hersh, William R

2010-01-01

Clinical coding and classification processes transform natural language descriptions in clinical text into data that can subsequently be used for clinical care, research, and other purposes. This systematic literature review examined studies that evaluated all types of automated coding and classification systems to determine the performance of such systems. Studies indexed in Medline or other relevant databases prior to March 2009 were considered. The 113 studies included in this review show that automated tools exist for a variety of coding and classification purposes, focus on various healthcare specialties, and handle a wide variety of clinical document types. Automated coding and classification systems themselves are not generalizable, nor are the results of the studies evaluating them. Published research shows these systems hold promise, but these data must be considered in context, with performance relative to the complexity of the task and the desired outcome. PMID:20962126

A systematic literature review of automated clinical coding and classification systems.

PubMed

Stanfill, Mary H; Williams, Margaret; Fenton, Susan H; Jenders, Robert A; Hersh, William R

2010-01-01

Clinical coding and classification processes transform natural language descriptions in clinical text into data that can subsequently be used for clinical care, research, and other purposes. This systematic literature review examined studies that evaluated all types of automated coding and classification systems to determine the performance of such systems. Studies indexed in Medline or other relevant databases prior to March 2009 were considered. The 113 studies included in this review show that automated tools exist for a variety of coding and classification purposes, focus on various healthcare specialties, and handle a wide variety of clinical document types. Automated coding and classification systems themselves are not generalizable, nor are the results of the studies evaluating them. Published research shows these systems hold promise, but these data must be considered in context, with performance relative to the complexity of the task and the desired outcome.

Clinical Laboratory Automation: A Case Study

PubMed Central

Archetti, Claudia; Montanelli, Alessandro; Finazzi, Dario; Caimi, Luigi; Garrafa, Emirena

2017-01-01

Background This paper presents a case study of an automated clinical laboratory in a large urban academic teaching hospital in the North of Italy, the Spedali Civili in Brescia, where four laboratories were merged in a unique laboratory through the introduction of laboratory automation. Materials and Methods The analysis compares the preautomation situation and the new setting from a cost perspective, by considering direct and indirect costs. It also presents an analysis of the turnaround time (TAT). The study considers equipment, staff and indirect costs. Results The introduction of automation led to a slight increase in equipment costs which is highly compensated by a remarkable decrease in staff costs. Consequently, total costs decreased by 12.55%. The analysis of the TAT shows an improvement of nonemergency exams while emergency exams are still validated within the maximum time imposed by the hospital. Conclusions The strategy adopted by the management, which was based on re-using the available equipment and staff when merging the pre-existing laboratories, has reached its goal: introducing automation while minimizing the costs. Significance for public health Automation is an emerging trend in modern clinical laboratories with a positive impact on service level to patients and on staff safety as shown by different studies. In fact, it allows process standardization which, in turn, decreases the frequency of outliers and errors. In addition, it induces faster processing times, thus improving the service level. On the other side, automation decreases the staff exposition to accidents strongly improving staff safety. In this study, we analyse a further potential benefit of automation, that is economic convenience. We study the case of the automated laboratory of one of the biggest hospital in Italy and compare the cost related to the pre and post automation situation. Introducing automation lead to a cost decrease without affecting the service level to patients. This was a key goal of the hospital which, as public health entities in general, is constantly struggling with budget constraints. PMID:28660178

Tests of Spectral Cloud Classification Using DMSP Fine Mode Satellite Data.

DTIC Science & Technology

1980-06-02

processing techniques of potential value. Fourier spectral analysis was identified as the most promising technique to upgrade automated processing of...these measurements on the Earth’s surface is 0. 3 n mi. 3. Pickett, R.M., and Blackman, E.S. (1976) Automated Processing of Satellite Imagery Data at Air...and Pickett. R. Al. (1977) Automated Processing of Satellite Imagery Data at the Air Force Global Weather Central: Demonstrations of Spectral Analysis

Microbiology of beef carcasses before and after slaughterline automation.

PubMed Central

Whelehan, O. P.; Hudson, W. R.; Roberts, T. A.

1986-01-01

The bacterial status of beef carcasses at a commercial abattoir was monitored before and after slaughterline automation. Bacterial counts did not differ significantly overall (P greater than 0.05) between the original manual line and the automated line for either morning or afternoon slaughter. On the manual line counts in the morning were lower than those from carcasses slaughtered in the afternoon, but on the automated line there was no difference between morning and afternoon counts. Due to highly significant line X sample site interaction for both morning and afternoon counts, overall differences among sample sites were not found by analysis of variance. However, principal components analysis revealed a significant shift in bacterial contamination among some sites due to slaughterline changes. The incidence of Enterobacteriaceae increased marginally following automation. PMID:3701039

Clinical Laboratory Automation: A Case Study.

PubMed

Archetti, Claudia; Montanelli, Alessandro; Finazzi, Dario; Caimi, Luigi; Garrafa, Emirena

2017-04-13

This paper presents a case study of an automated clinical laboratory in a large urban academic teaching hospital in the North of Italy, the Spedali Civili in Brescia, where four laboratories were merged in a unique laboratory through the introduction of laboratory automation. The analysis compares the preautomation situation and the new setting from a cost perspective, by considering direct and indirect costs. It also presents an analysis of the turnaround time (TAT). The study considers equipment, staff and indirect costs. The introduction of automation led to a slight increase in equipment costs which is highly compensated by a remarkable decrease in staff costs. Consequently, total costs decreased by 12.55%. The analysis of the TAT shows an improvement of nonemergency exams while emergency exams are still validated within the maximum time imposed by the hospital. The strategy adopted by the management, which was based on re-using the available equipment and staff when merging the pre-existing laboratories, has reached its goal: introducing automation while minimizing the costs.

Application of automation and information systems to forensic genetic specimen processing.

PubMed

Leclair, Benoît; Scholl, Tom

2005-03-01

During the last 10 years, the introduction of PCR-based DNA typing technologies in forensic applications has been highly successful. This technology has become pervasive throughout forensic laboratories and it continues to grow in prevalence. For many criminal cases, it provides the most probative evidence. Criminal genotype data banking and victim identification initiatives that follow mass-fatality incidents have benefited the most from the introduction of automation for sample processing and data analysis. Attributes of offender specimens including large numbers, high quality and identical collection and processing are ideal for the application of laboratory automation. The magnitude of kinship analysis required by mass-fatality incidents necessitates the application of computing solutions to automate the task. More recently, the development activities of many forensic laboratories are focused on leveraging experience from these two applications to casework sample processing. The trend toward increased prevalence of forensic genetic analysis will continue to drive additional innovations in high-throughput laboratory automation and information systems.

On the Automation of the MarkIII Data Analysis System.

NASA Astrophysics Data System (ADS)

Schwegmann, W.; Schuh, H.

1999-03-01

A faster and semiautomatic data analysis is an important contribution to the acceleration of the VLBI procedure. A concept for the automation of one of the most widely used VLBI software packages the MarkIII Data Analysis System was developed. Then, the program PWXCB, which extracts weather and cable calibration data from the station log-files, was automated supplementing the existing Fortran77 program-code. The new program XLOG and its results will be presented. Most of the tasks in the VLBI data analysis are very complex and their automation requires typical knowledge-based techniques. Thus, a knowledge-based system (KBS) for support and guidance of the analyst is being developed using the AI-workbench BABYLON, which is based on methods of artificial intelligence (AI). The advantages of a KBS for the MarkIII Data Analysis System and the required steps to build a KBS will be demonstrated. Examples about the current status of the project will be given, too.

Contrasting models of driver behaviour in emergencies using retrospective verbalisations and network analysis.

PubMed

Banks, Victoria A; Stanton, Neville A

2015-01-01

Automated assistance in driving emergencies aims to improve the safety of our roads by avoiding or mitigating the effects of accidents. However, the behavioural implications of such systems remain unknown. This paper introduces the driver decision-making in emergencies (DDMiEs) framework to investigate how the level and type of automation may affect driver decision-making and subsequent responses to critical braking events using network analysis to interrogate retrospective verbalisations. Four DDMiE models were constructed to represent different levels of automation within the driving task and its effects on driver decision-making. Findings suggest that whilst automation does not alter the decision-making pathway (e.g. the processes between hazard detection and response remain similar), it does appear to significantly weaken the links between information-processing nodes. This reflects an unintended yet emergent property within the task network that could mean that we may not be improving safety in the way we expect. This paper contrasts models of driver decision-making in emergencies at varying levels of automation using the Southampton University Driving Simulator. Network analysis of retrospective verbalisations indicates that increasing the level of automation in driving emergencies weakens the link between information-processing nodes essential for effective decision-making.

Automated Diatom Analysis Applied to Traditional Light Microscopy: A Proof-of-Concept Study

NASA Astrophysics Data System (ADS)

Little, Z. H. L.; Bishop, I.; Spaulding, S. A.; Nelson, H.; Mahoney, C.

2017-12-01

Diatom identification and enumeration by high resolution light microscopy is required for many areas of research and water quality assessment. Such analyses, however, are both expertise and labor-intensive. These challenges motivate the need for an automated process to efficiently and accurately identify and enumerate diatoms. Improvements in particle analysis software have increased the likelihood that diatom enumeration can be automated. VisualSpreadsheet software provides a possible solution for automated particle analysis of high-resolution light microscope diatom images. We applied the software, independent of its complementary FlowCam hardware, to automated analysis of light microscope images containing diatoms. Through numerous trials, we arrived at threshold settings to correctly segment 67% of the total possible diatom valves and fragments from broad fields of view. (183 light microscope images were examined containing 255 diatom particles. Of the 255 diatom particles present, 216 diatoms valves and fragments of valves were processed, with 170 properly analyzed and focused upon by the software). Manual analysis of the images yielded 255 particles in 400 seconds, whereas the software yielded a total of 216 particles in 68 seconds, thus highlighting that the software has an approximate five-fold efficiency advantage in particle analysis time. As in past efforts, incomplete or incorrect recognition was found for images with multiple valves in contact or valves with little contrast. The software has potential to be an effective tool in assisting taxonomists with diatom enumeration by completing a large portion of analyses. Benefits and limitations of the approach are presented to allow for development of future work in image analysis and automated enumeration of traditional light microscope images containing diatoms.

Adaptive automation of human-machine system information-processing functions.

PubMed

Kaber, David B; Wright, Melanie C; Prinzel, Lawrence J; Clamann, Michael P

2005-01-01

The goal of this research was to describe the ability of human operators to interact with adaptive automation (AA) applied to various stages of complex systems information processing, defined in a model of human-automation interaction. Forty participants operated a simulation of an air traffic control task. Automated assistance was adaptively applied to information acquisition, information analysis, decision making, and action implementation aspects of the task based on operator workload states, which were measured using a secondary task. The differential effects of the forms of automation were determined and compared with a manual control condition. Results of two 20-min trials of AA or manual control revealed a significant effect of the type of automation on performance, particularly during manual control periods as part of the adaptive conditions. Humans appear to better adapt to AA applied to sensory and psychomotor information-processing functions (action implementation) than to AA applied to cognitive functions (information analysis and decision making), and AA is superior to completely manual control. Potential applications of this research include the design of automation to support air traffic controller information processing.

Description of texts of auxiliary programs for processing video information. Part 2: SUODH program of automated separation of quasihomogeneous formations

NASA Technical Reports Server (NTRS)

Borisenko, V. I.; Chesalin, L. S.

1980-01-01

The algorithm, block diagram, complete text, and instructions are given for the use of a computer program to separate formations whose spectral characteristics are constant on the average. The initial material for operating the computer program presented is video information in a standard color-superposition format.

Humans: still vital after all these years of automation.

PubMed

Parasuraman, Raja; Wickens, Christopher D

2008-06-01

The authors discuss empirical studies of human-automation interaction and their implications for automation design. Automation is prevalent in safety-critical systems and increasingly in everyday life. Many studies of human performance in automated systems have been conducted over the past 30 years. Developments in three areas are examined: levels and stages of automation, reliance on and compliance with automation, and adaptive automation. Automation applied to information analysis or decision-making functions leads to differential system performance benefits and costs that must be considered in choosing appropriate levels and stages of automation. Human user dependence on automated alerts and advisories reflects two components of operator trust, reliance and compliance, which are in turn determined by the threshold designers use to balance automation misses and false alarms. Finally, adaptive automation can provide additional benefits in balancing workload and maintaining the user's situation awareness, although more research is required to identify when adaptation should be user controlled or system driven. The past three decades of empirical research on humans and automation has provided a strong science base that can be used to guide the design of automated systems. This research can be applied to most current and future automated systems.

Risk Assessment for Parents Who Suspect Their Child Has Autism Spectrum Disorder: Machine Learning Approach.

PubMed

Ben-Sasson, Ayelet; Robins, Diana L; Yom-Tov, Elad

2018-04-24

Parents are likely to seek Web-based communities to verify their suspicions of autism spectrum disorder markers in their child. Automated tools support human decisions in many domains and could therefore potentially support concerned parents. The objective of this study was to test the feasibility of assessing autism spectrum disorder risk in parental concerns from Web-based sources, using automated text analysis tools and minimal standard questioning. Participants were 115 parents with concerns regarding their child's social-communication development. Children were 16- to 30-months old, and 57.4% (66/115) had a family history of autism spectrum disorder. Parents reported their concerns online, and completed an autism spectrum disorder-specific screener, the Modified Checklist for Autism in Toddlers-Revised, with Follow-up (M-CHAT-R/F), and a broad developmental screener, the Ages and Stages Questionnaire (ASQ). An algorithm predicted autism spectrum disorder risk using a combination of the parent's text and a single screening question, selected by the algorithm to enhance prediction accuracy. Screening measures identified 58% (67/115) to 88% (101/115) of children at risk for autism spectrum disorder. Children with a family history of autism spectrum disorder were 3 times more likely to show autism spectrum disorder risk on screening measures. The prediction of a child's risk on the ASQ or M-CHAT-R was significantly more accurate when predicted from text combined with an M-CHAT-R question selected (automatically) than from the text alone. The frequently automatically selected M-CHAT-R questions that predicted risk were: following a point, make-believe play, and concern about deafness. The internet can be harnessed to prescreen for autism spectrum disorder using parental concerns by administering a few standardized screening questions to augment this process. ©Ayelet Ben-Sasson, Diana L Robins, Elad Yom-Tov. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 24.04.2018.

Development Status: Automation Advanced Development Space Station Freedom Electric Power System

NASA Technical Reports Server (NTRS)

Dolce, James L.; Kish, James A.; Mellor, Pamela A.

1990-01-01

Electric power system automation for Space Station Freedom is intended to operate in a loop. Data from the power system is used for diagnosis and security analysis to generate Operations Management System (OMS) requests, which are sent to an arbiter, which sends a plan to a commander generator connected to the electric power system. This viewgraph presentation profiles automation software for diagnosis, scheduling, and constraint interfaces, and simulation to support automation development. The automation development process is diagrammed, and the process of creating Ada and ART versions of the automation software is described.

Development of a User Interface for a Regression Analysis Software Tool

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred; Volden, Thomas R.

2010-01-01

An easy-to -use user interface was implemented in a highly automated regression analysis tool. The user interface was developed from the start to run on computers that use the Windows, Macintosh, Linux, or UNIX operating system. Many user interface features were specifically designed such that a novice or inexperienced user can apply the regression analysis tool with confidence. Therefore, the user interface s design minimizes interactive input from the user. In addition, reasonable default combinations are assigned to those analysis settings that influence the outcome of the regression analysis. These default combinations will lead to a successful regression analysis result for most experimental data sets. The user interface comes in two versions. The text user interface version is used for the ongoing development of the regression analysis tool. The official release of the regression analysis tool, on the other hand, has a graphical user interface that is more efficient to use. This graphical user interface displays all input file names, output file names, and analysis settings for a specific software application mode on a single screen which makes it easier to generate reliable analysis results and to perform input parameter studies. An object-oriented approach was used for the development of the graphical user interface. This choice keeps future software maintenance costs to a reasonable limit. Examples of both the text user interface and graphical user interface are discussed in order to illustrate the user interface s overall design approach.

Effects of imperfect automation on decision making in a simulated command and control task.

PubMed

Rovira, Ericka; McGarry, Kathleen; Parasuraman, Raja

2007-02-01

Effects of four types of automation support and two levels of automation reliability were examined. The objective was to examine the differential impact of information and decision automation and to investigate the costs of automation unreliability. Research has shown that imperfect automation can lead to differential effects of stages and levels of automation on human performance. Eighteen participants performed a "sensor to shooter" targeting simulation of command and control. Dependent variables included accuracy and response time of target engagement decisions, secondary task performance, and subjective ratings of mental work-load, trust, and self-confidence. Compared with manual performance, reliable automation significantly reduced decision times. Unreliable automation led to greater cost in decision-making accuracy under the higher automation reliability condition for three different forms of decision automation relative to information automation. At low automation reliability, however, there was a cost in performance for both information and decision automation. The results are consistent with a model of human-automation interaction that requires evaluation of the different stages of information processing to which automation support can be applied. If fully reliable decision automation cannot be guaranteed, designers should provide users with information automation support or other tools that allow for inspection and analysis of raw data.

Toward designing for trust in database automation

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

Duez, P. P.; Jamieson, G. A.

Appropriate reliance on system automation is imperative for safe and productive work, especially in safety-critical systems. It is unsafe to rely on automation beyond its designed use; conversely, it can be both unproductive and unsafe to manually perform tasks that are better relegated to automated tools. Operator trust in automated tools mediates reliance, and trust appears to affect how operators use technology. As automated agents become more complex, the question of trust in automation is increasingly important. In order to achieve proper use of automation, we must engender an appropriate degree of trust that is sensitive to changes in operatingmore » functions and context. In this paper, we present research concerning trust in automation in the domain of automated tools for relational databases. Lee and See have provided models of trust in automation. One model developed by Lee and See identifies three key categories of information about the automation that lie along a continuum of attributional abstraction. Purpose-, process-and performance-related information serve, both individually and through inferences between them, to describe automation in such a way as to engender r properly-calibrated trust. Thus, one can look at information from different levels of attributional abstraction as a general requirements analysis for information key to appropriate trust in automation. The model of information necessary to engender appropriate trust in automation [1] is a general one. Although it describes categories of information, it does not provide insight on how to determine the specific information elements required for a given automated tool. We have applied the Abstraction Hierarchy (AH) to this problem in the domain of relational databases. The AH serves as a formal description of the automation at several levels of abstraction, ranging from a very abstract purpose-oriented description to a more concrete description of the resources involved in the automated process. The connection between an AH for an automated tool and a list of information elements at the three levels of attributional abstraction is then direct, providing a method for satisfying information requirements for appropriate trust in automation. In this paper, we will present our method for developing specific information requirements for an automated tool, based on a formal analysis of that tool and the models presented by Lee and See. We will show an example of the application of the AH to automation, in the domain of relational database automation, and the resulting set of specific information elements for appropriate trust in the automated tool. Finally, we will comment on the applicability of this approach to the domain of nuclear plant instrumentation. (authors)« less

Computer-assisted liver graft steatosis assessment via learning-based texture analysis.

PubMed

Moccia, Sara; Mattos, Leonardo S; Patrini, Ilaria; Ruperti, Michela; Poté, Nicolas; Dondero, Federica; Cauchy, François; Sepulveda, Ailton; Soubrane, Olivier; De Momi, Elena; Diaspro, Alberto; Cesaretti, Manuela

2018-05-23

Fast and accurate graft hepatic steatosis (HS) assessment is of primary importance for lowering liver dysfunction risks after transplantation. Histopathological analysis of biopsied liver is the gold standard for assessing HS, despite being invasive and time consuming. Due to the short time availability between liver procurement and transplantation, surgeons perform HS assessment through clinical evaluation (medical history, blood tests) and liver texture visual analysis. Despite visual analysis being recognized as challenging in the clinical literature, few efforts have been invested to develop computer-assisted solutions for HS assessment. The objective of this paper is to investigate the automatic analysis of liver texture with machine learning algorithms to automate the HS assessment process and offer support for the surgeon decision process. Forty RGB images of forty different donors were analyzed. The images were captured with an RGB smartphone camera in the operating room (OR). Twenty images refer to livers that were accepted and 20 to discarded livers. Fifteen randomly selected liver patches were extracted from each image. Patch size was [Formula: see text]. This way, a balanced dataset of 600 patches was obtained. Intensity-based features (INT), histogram of local binary pattern ([Formula: see text]), and gray-level co-occurrence matrix ([Formula: see text]) were investigated. Blood-sample features (Blo) were included in the analysis, too. Supervised and semisupervised learning approaches were investigated for feature classification. The leave-one-patient-out cross-validation was performed to estimate the classification performance. With the best-performing feature set ([Formula: see text]) and semisupervised learning, the achieved classification sensitivity, specificity, and accuracy were 95, 81, and 88%, respectively. This research represents the first attempt to use machine learning and automatic texture analysis of RGB images from ubiquitous smartphone cameras for the task of graft HS assessment. The results suggest that is a promising strategy to develop a fully automatic solution to assist surgeons in HS assessment inside the OR.

SureChEMBL: a large-scale, chemically annotated patent document database.

PubMed

Papadatos, George; Davies, Mark; Dedman, Nathan; Chambers, Jon; Gaulton, Anna; Siddle, James; Koks, Richard; Irvine, Sean A; Pettersson, Joe; Goncharoff, Nicko; Hersey, Anne; Overington, John P

2016-01-04

SureChEMBL is a publicly available large-scale resource containing compounds extracted from the full text, images and attachments of patent documents. The data are extracted from the patent literature according to an automated text and image-mining pipeline on a daily basis. SureChEMBL provides access to a previously unavailable, open and timely set of annotated compound-patent associations, complemented with sophisticated combined structure and keyword-based search capabilities against the compound repository and patent document corpus; given the wealth of knowledge hidden in patent documents, analysis of SureChEMBL data has immediate applications in drug discovery, medicinal chemistry and other commercial areas of chemical science. Currently, the database contains 17 million compounds extracted from 14 million patent documents. Access is available through a dedicated web-based interface and data downloads at: https://www.surechembl.org/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

SureChEMBL: a large-scale, chemically annotated patent document database

PubMed Central

Papadatos, George; Davies, Mark; Dedman, Nathan; Chambers, Jon; Gaulton, Anna; Siddle, James; Koks, Richard; Irvine, Sean A.; Pettersson, Joe; Goncharoff, Nicko; Hersey, Anne; Overington, John P.

2016-01-01

SureChEMBL is a publicly available large-scale resource containing compounds extracted from the full text, images and attachments of patent documents. The data are extracted from the patent literature according to an automated text and image-mining pipeline on a daily basis. SureChEMBL provides access to a previously unavailable, open and timely set of annotated compound-patent associations, complemented with sophisticated combined structure and keyword-based search capabilities against the compound repository and patent document corpus; given the wealth of knowledge hidden in patent documents, analysis of SureChEMBL data has immediate applications in drug discovery, medicinal chemistry and other commercial areas of chemical science. Currently, the database contains 17 million compounds extracted from 14 million patent documents. Access is available through a dedicated web-based interface and data downloads at: https://www.surechembl.org/. PMID:26582922

Arc-An OAI Service Provider for Digital Library Federation; Kepler-An OAI Data/Service Provider for the Individual; Information Objects and Rights Management: A Mediation-Based Approach to DRM Interoperability; Automated Name Authority Control and Enhanced Searching in the Levy Collection; Renardus Project Developments and the Wider Digital Library Context.

ERIC Educational Resources Information Center

Liu, Xiaoming; Maly, Kurt; Zubair, Mohammad; Nelson, Michael L.; Erickson, John S.; DiLauro, Tim; Choudhury, G. Sayeed; Patton, Mark; Warner, James W.; Brown, Elizabeth W.; Heery, Rachel; Carpenter, Leona; Day, Michael

2001-01-01

Includes five articles that discuss the OAI (Open Archive Initiative), an interface between data providers and service providers; information objects and digital rights management interoperability; digitizing library collections, including automated name authority control, metadata, and text searching engines; and building digital library services…

Automated processing of endoscopic surgical instruments.

PubMed

Roth, K; Sieber, J P; Schrimm, H; Heeg, P; Buess, G

1994-10-01

This paper deals with the requirements for automated processing of endoscopic surgical instruments. After a brief analysis of the current problems, solutions are discussed. Test-procedures have been developed to validate the automated processing, so that the cleaning results are guaranteed and reproducable. Also a device for testing and cleaning was designed together with Netzsch Newamatic and PCI, called TC-MIC, to automate processing and reduce manual work.

Space Station Initial Operational Concept (IOC) operations and safety view - Automation and robotics for Space Station

NASA Technical Reports Server (NTRS)

Bates, William V., Jr.

1989-01-01

The automation and robotics requirements for the Space Station Initial Operational Concept (IOC) are discussed. The amount of tasks to be performed by an eight-person crew, the need for an automated or directed fault analysis capability, and ground support requirements are considered. Issues important in determining the role of automation for the IOC are listed.

Evaluation of automated sample preparation, retention time locked gas chromatography-mass spectrometry and data analysis methods for the metabolomic study of Arabidopsis species.

PubMed

Gu, Qun; David, Frank; Lynen, Frédéric; Rumpel, Klaus; Dugardeyn, Jasper; Van Der Straeten, Dominique; Xu, Guowang; Sandra, Pat

2011-05-27

In this paper, automated sample preparation, retention time locked gas chromatography-mass spectrometry (GC-MS) and data analysis methods for the metabolomics study were evaluated. A miniaturized and automated derivatisation method using sequential oximation and silylation was applied to a polar extract of 4 types (2 types×2 ages) of Arabidopsis thaliana, a popular model organism often used in plant sciences and genetics. Automation of the derivatisation process offers excellent repeatability, and the time between sample preparation and analysis was short and constant, reducing artifact formation. Retention time locked (RTL) gas chromatography-mass spectrometry was used, resulting in reproducible retention times and GC-MS profiles. Two approaches were used for data analysis. XCMS followed by principal component analysis (approach 1) and AMDIS deconvolution combined with a commercially available program (Mass Profiler Professional) followed by principal component analysis (approach 2) were compared. Several features that were up- or down-regulated in the different types were detected. Copyright © 2011 Elsevier B.V. All rights reserved.

A precursor system analysis of automated construction, maintenance, and operational requirements : resource materials

DOT National Transportation Integrated Search

1995-03-01

This report documents work performed by the University of California at Davis in collaboration with the California Department of Transportation (Caltrans) in relationship to a Precursor System Analysis dealing with a study of automated construction, ...

An approach to standardization of urine sediment analysis via suggestion of a common manual protocol.

PubMed

Ko, Dae-Hyun; Ji, Misuk; Kim, Sollip; Cho, Eun-Jung; Lee, Woochang; Yun, Yeo-Min; Chun, Sail; Min, Won-Ki

2016-01-01

The results of urine sediment analysis have been reported semiquantitatively. However, as recent guidelines recommend quantitative reporting of urine sediment, and with the development of automated urine sediment analyzers, there is an increasing need for quantitative analysis of urine sediment. Here, we developed a protocol for urine sediment analysis and quantified the results. Based on questionnaires, various reports, guidelines, and experimental results, we developed a protocol for urine sediment analysis. The results of this new protocol were compared with those obtained with a standardized chamber and an automated sediment analyzer. Reference intervals were also estimated using new protocol. We developed a protocol with centrifugation at 400 g for 5 min, with the average concentration factor of 30. The correlation between quantitative results of urine sediment analysis, the standardized chamber, and the automated sediment analyzer were generally good. The conversion factor derived from the new protocol showed a better fit with the results of manual count than the default conversion factor in the automated sediment analyzer. We developed a protocol for manual urine sediment analysis to quantitatively report the results. This protocol may provide a mean for standardization of urine sediment analysis.

Automated clinical system for chromosome analysis

NASA Technical Reports Server (NTRS)

Castleman, K. R.; Friedan, H. J.; Johnson, E. T.; Rennie, P. A.; Wall, R. J. (Inventor)

1978-01-01

An automatic chromosome analysis system is provided wherein a suitably prepared slide with chromosome spreads thereon is placed on the stage of an automated microscope. The automated microscope stage is computer operated to move the slide to enable detection of chromosome spreads on the slide. The X and Y location of each chromosome spread that is detected is stored. The computer measures the chromosomes in a spread, classifies them by group or by type and also prepares a digital karyotype image. The computer system can also prepare a patient report summarizing the result of the analysis and listing suspected abnormalities.

Automated condition-invariable neurite segmentation and synapse classification using textural analysis-based machine-learning algorithms

PubMed Central

Kandaswamy, Umasankar; Rotman, Ziv; Watt, Dana; Schillebeeckx, Ian; Cavalli, Valeria; Klyachko, Vitaly

2013-01-01

High-resolution live-cell imaging studies of neuronal structure and function are characterized by large variability in image acquisition conditions due to background and sample variations as well as low signal-to-noise ratio. The lack of automated image analysis tools that can be generalized for varying image acquisition conditions represents one of the main challenges in the field of biomedical image analysis. Specifically, segmentation of the axonal/dendritic arborizations in brightfield or fluorescence imaging studies is extremely labor-intensive and still performed mostly manually. Here we describe a fully automated machine-learning approach based on textural analysis algorithms for segmenting neuronal arborizations in high-resolution brightfield images of live cultured neurons. We compare performance of our algorithm to manual segmentation and show that it combines 90% accuracy, with similarly high levels of specificity and sensitivity. Moreover, the algorithm maintains high performance levels under a wide range of image acquisition conditions indicating that it is largely condition-invariable. We further describe an application of this algorithm to fully automated synapse localization and classification in fluorescence imaging studies based on synaptic activity. Textural analysis-based machine-learning approach thus offers a high performance condition-invariable tool for automated neurite segmentation. PMID:23261652

Harnessing Technology to Improve Formative Assessment of Student Conceptions in STEM: Forging a National Network

PubMed Central

Haudek, Kevin C.; Kaplan, Jennifer J.; Knight, Jennifer; Long, Tammy; Merrill, John; Munn, Alan; Nehm, Ross; Smith, Michelle; Urban-Lurain, Mark

2011-01-01

Concept inventories, consisting of multiple-choice questions designed around common student misconceptions, are designed to reveal student thinking. However, students often have complex, heterogeneous ideas about scientific concepts. Constructed-response assessments, in which students must create their own answer, may better reveal students’ thinking, but are time- and resource-intensive to evaluate. This report describes the initial meeting of a National Science Foundation–funded cross-institutional collaboration of interdisciplinary science, technology, engineering, and mathematics (STEM) education researchers interested in exploring the use of automated text analysis to evaluate constructed-response assessments. Participants at the meeting shared existing work on lexical analysis and concept inventories, participated in technology demonstrations and workshops, and discussed research goals. We are seeking interested collaborators to join our research community. PMID:21633063

Harnessing technology to improve formative assessment of student conceptions in STEM: forging a national network.

PubMed

Haudek, Kevin C; Kaplan, Jennifer J; Knight, Jennifer; Long, Tammy; Merrill, John; Munn, Alan; Nehm, Ross; Smith, Michelle; Urban-Lurain, Mark

2011-01-01

Concept inventories, consisting of multiple-choice questions designed around common student misconceptions, are designed to reveal student thinking. However, students often have complex, heterogeneous ideas about scientific concepts. Constructed-response assessments, in which students must create their own answer, may better reveal students' thinking, but are time- and resource-intensive to evaluate. This report describes the initial meeting of a National Science Foundation-funded cross-institutional collaboration of interdisciplinary science, technology, engineering, and mathematics (STEM) education researchers interested in exploring the use of automated text analysis to evaluate constructed-response assessments. Participants at the meeting shared existing work on lexical analysis and concept inventories, participated in technology demonstrations and workshops, and discussed research goals. We are seeking interested collaborators to join our research community.

An automated Y-maze based on a reduced instruction set computer (RISC) microcontroller for the assessment of continuous spontaneous alternation in rats.

PubMed

Heredia-López, Francisco J; Álvarez-Cervera, Fernando J; Collí-Alfaro, José G; Bata-García, José L; Arankowsky-Sandoval, Gloria; Góngora-Alfaro, José L

2016-12-01

Continuous spontaneous alternation behavior (SAB) in a Y-maze is used for evaluating working memory in rodents. Here, the design of an automated Y-maze equipped with three infrared optocouplers per arm, and commanded by a reduced instruction set computer (RISC) microcontroller is described. The software was devised for recording only true entries and exits to the arms. Experimental settings are programmed via a keyboard with three buttons and a display. The sequence of arm entries and the time spent in each arm and the neutral zone (NZ) are saved as a text file in a non-volatile memory for later transfer to a USB flash memory. Data files are analyzed with a program developed under LabVIEW® environment, and the results are exported to an Excel® spreadsheet file. Variables measured are: latency to exit the starting arm, sequence and number of arm entries, number of alternations, alternation percentage, and cumulative times spent in each arm and NZ. The automated Y-maze accurately detected the SAB decrease produced in rats by the muscarinic antagonist trihexyphenidyl, and its reversal by caffeine, having 100 % concordance with the alternation percentages calculated by two trained observers who independently watched videos of the same experiments. Although the values of time spent in the arms and NZ measured by the automated system had small discrepancies with those calculated by the observers, Bland-Altman analysis showed 95 % concordance in three pairs of comparisons, while in one it was 90 %, indicating that this system is a reliable and inexpensive alternative for the study of continuous SAB in rodents.

External Validity of Electronic Sniffers for Automated Recognition of Acute Respiratory Distress Syndrome.

PubMed

McKown, Andrew C; Brown, Ryan M; Ware, Lorraine B; Wanderer, Jonathan P

2017-01-01

Automated electronic sniffers may be useful for early detection of acute respiratory distress syndrome (ARDS) for institution of treatment or clinical trial screening. In a prospective cohort of 2929 critically ill patients, we retrospectively applied published sniffer algorithms for automated detection of acute lung injury to assess their utility in diagnosis of ARDS in the first 4 ICU days. Radiographic full-text reports were searched for "edema" OR ("bilateral" AND "infiltrate") and a more detailed algorithm for descriptions consistent with ARDS. Patients were flagged as possible ARDS if a radiograph met search criteria and had a PaO 2 /FiO 2 or SpO 2 /FiO 2 of 300 or 315, respectively. Test characteristics of the electronic sniffers and clinical suspicion of ARDS were compared to a gold standard of 2-physician adjudicated ARDS. Thirty percent of 2841 patients included in the analysis had gold standard diagnosis of ARDS. The simpler algorithm had sensitivity for ARDS of 78.9%, specificity of 52%, positive predictive value (PPV) of 41%, and negative predictive value (NPV) of 85.3% over the 4-day study period. The more detailed algorithm had sensitivity of 88.2%, specificity of 55.4%, PPV of 45.6%, and NPV of 91.7%. Both algorithms were more sensitive but less specific than clinician suspicion, which had sensitivity of 40.7%, specificity of 94.8%, PPV of 78.2%, and NPV of 77.7%. Published electronic sniffer algorithms for ARDS may be useful automated screening tools for ARDS and improve on clinical recognition, but they are limited to screening rather than diagnosis because their specificity is poor.

Modeling strategic behavior in human-automation interaction - Why an 'aid' can (and should) go unused

NASA Technical Reports Server (NTRS)

Kirlik, Alex

1993-01-01

Task-offload aids (e.g., an autopilot, an 'intelligent' assistant) can be selectively engaged by the human operator to dynamically delegate tasks to automation. Introducing such aids eliminates some task demands but creates new ones associated with programming, engaging, and disengaging the aiding device via an interface. The burdens associated with managing automation can sometimes outweigh the potential benefits of automation to improved system performance. Aid design parameters and features of the overall multitask context combine to determine whether or not a task-offload aid will effectively support the operator. A modeling and sensitivity analysis approach is presented that identifies effective strategies for human-automation interaction as a function of three task-context parameters and three aid design parameters. The analysis and modeling approaches provide resources for predicting how a well-adapted operator will use a given task-offload aid, and for specifying aid design features that ensure that automation will provide effective operator support in a multitask environment.

HPV-QUEST: A highly customized system for automated HPV sequence analysis capable of processing Next Generation sequencing data set.

PubMed

Yin, Li; Yao, Jiqiang; Gardner, Brent P; Chang, Kaifen; Yu, Fahong; Goodenow, Maureen M

2012-01-01

Next Generation sequencing (NGS) applied to human papilloma viruses (HPV) can provide sensitive methods to investigate the molecular epidemiology of multiple type HPV infection. Currently a genotyping system with a comprehensive collection of updated HPV reference sequences and a capacity to handle NGS data sets is lacking. HPV-QUEST was developed as an automated and rapid HPV genotyping system. The web-based HPV-QUEST subtyping algorithm was developed using HTML, PHP, Perl scripting language, and MYSQL as the database backend. HPV-QUEST includes a database of annotated HPV reference sequences with updated nomenclature covering 5 genuses, 14 species and 150 mucosal and cutaneous types to genotype blasted query sequences. HPV-QUEST processes up to 10 megabases of sequences within 1 to 2 minutes. Results are reported in html, text and excel formats and display e-value, blast score, and local and coverage identities; provide genus, species, type, infection site and risk for the best matched reference HPV sequence; and produce results ready for additional analyses.

Automated quantitative cytological analysis using portable microfluidic microscopy.

PubMed

Jagannadh, Veerendra Kalyan; Murthy, Rashmi Sreeramachandra; Srinivasan, Rajesh; Gorthi, Sai Siva

2016-06-01

In this article, a portable microfluidic microscopy based approach for automated cytological investigations is presented. Inexpensive optical and electronic components have been used to construct a simple microfluidic microscopy system. In contrast to the conventional slide-based methods, the presented method employs microfluidics to enable automated sample handling and image acquisition. The approach involves the use of simple in-suspension staining and automated image acquisition to enable quantitative cytological analysis of samples. The applicability of the presented approach to research in cellular biology is shown by performing an automated cell viability assessment on a given population of yeast cells. Further, the relevance of the presented approach to clinical diagnosis and prognosis has been demonstrated by performing detection and differential assessment of malaria infection in a given sample. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Automated data acquisition technology development:Automated modeling and control development

NASA Technical Reports Server (NTRS)

Romine, Peter L.

1995-01-01

This report documents the completion of, and improvements made to, the software developed for automated data acquisition and automated modeling and control development on the Texas Micro rackmounted PC's. This research was initiated because a need was identified by the Metal Processing Branch of NASA Marshall Space Flight Center for a mobile data acquisition and data analysis system, customized for welding measurement and calibration. Several hardware configurations were evaluated and a PC based system was chosen. The Welding Measurement System (WMS), is a dedicated instrument strickly for use of data acquisition and data analysis. In addition to the data acquisition functions described in this thesis, WMS also supports many functions associated with process control. The hardware and software requirements for an automated acquisition system for welding process parameters, welding equipment checkout, and welding process modeling were determined in 1992. From these recommendations, NASA purchased the necessary hardware and software. The new welding acquisition system is designed to collect welding parameter data and perform analysis to determine the voltage versus current arc-length relationship for VPPA welding. Once the results of this analysis are obtained, they can then be used to develop a RAIL function to control welding startup and shutdown without torch crashing.

Semi-automatic object geometry estimation for image personalization

NASA Astrophysics Data System (ADS)

Ding, Hengzhou; Bala, Raja; Fan, Zhigang; Eschbach, Reiner; Bouman, Charles A.; Allebach, Jan P.

2010-01-01

Digital printing brings about a host of benefits, one of which is the ability to create short runs of variable, customized content. One form of customization that is receiving much attention lately is in photofinishing applications, whereby personalized calendars, greeting cards, and photo books are created by inserting text strings into images. It is particularly interesting to estimate the underlying geometry of the surface and incorporate the text into the image content in an intelligent and natural way. Current solutions either allow fixed text insertion schemes into preprocessed images, or provide manual text insertion tools that are time consuming and aimed only at the high-end graphic designer. It would thus be desirable to provide some level of automation in the image personalization process. We propose a semi-automatic image personalization workflow which includes two scenarios: text insertion and text replacement. In both scenarios, the underlying surfaces are assumed to be planar. A 3-D pinhole camera model is used for rendering text, whose parameters are estimated by analyzing existing structures in the image. Techniques in image processing and computer vison such as the Hough transform, the bilateral filter, and connected component analysis are combined, along with necessary user inputs. In particular, the semi-automatic workflow is implemented as an image personalization tool, which is presented in our companion paper.1 Experimental results including personalized images for both scenarios are shown, which demonstrate the effectiveness of our algorithms.

Quantification of Pulmonary Fibrosis in a Bleomycin Mouse Model Using Automated Histological Image Analysis.

PubMed

Gilhodes, Jean-Claude; Julé, Yvon; Kreuz, Sebastian; Stierstorfer, Birgit; Stiller, Detlef; Wollin, Lutz

2017-01-01

Current literature on pulmonary fibrosis induced in animal models highlights the need of an accurate, reliable and reproducible histological quantitative analysis. One of the major limits of histological scoring concerns the fact that it is observer-dependent and consequently subject to variability, which may preclude comparative studies between different laboratories. To achieve a reliable and observer-independent quantification of lung fibrosis we developed an automated software histological image analysis performed from digital image of entire lung sections. This automated analysis was compared to standard evaluation methods with regard to its validation as an end-point measure of fibrosis. Lung fibrosis was induced in mice by intratracheal administration of bleomycin (BLM) at 0.25, 0.5, 0.75 and 1 mg/kg. A detailed characterization of BLM-induced fibrosis was performed 14 days after BLM administration using lung function testing, micro-computed tomography and Ashcroft scoring analysis. Quantification of fibrosis by automated analysis was assessed based on pulmonary tissue density measured from thousands of micro-tiles processed from digital images of entire lung sections. Prior to analysis, large bronchi and vessels were manually excluded from the original images. Measurement of fibrosis has been expressed by two indexes: the mean pulmonary tissue density and the high pulmonary tissue density frequency. We showed that tissue density indexes gave access to a very accurate and reliable quantification of morphological changes induced by BLM even for the lowest concentration used (0.25 mg/kg). A reconstructed 2D-image of the entire lung section at high resolution (3.6 μm/pixel) has been performed from tissue density values allowing the visualization of their distribution throughout fibrotic and non-fibrotic regions. A significant correlation (p<0.0001) was found between automated analysis and the above standard evaluation methods. This correlation establishes automated analysis as a novel end-point measure of BLM-induced lung fibrosis in mice, which will be very valuable for future preclinical drug explorations.

Quantification of Pulmonary Fibrosis in a Bleomycin Mouse Model Using Automated Histological Image Analysis

PubMed Central

Gilhodes, Jean-Claude; Kreuz, Sebastian; Stierstorfer, Birgit; Stiller, Detlef; Wollin, Lutz

2017-01-01

Current literature on pulmonary fibrosis induced in animal models highlights the need of an accurate, reliable and reproducible histological quantitative analysis. One of the major limits of histological scoring concerns the fact that it is observer-dependent and consequently subject to variability, which may preclude comparative studies between different laboratories. To achieve a reliable and observer-independent quantification of lung fibrosis we developed an automated software histological image analysis performed from digital image of entire lung sections. This automated analysis was compared to standard evaluation methods with regard to its validation as an end-point measure of fibrosis. Lung fibrosis was induced in mice by intratracheal administration of bleomycin (BLM) at 0.25, 0.5, 0.75 and 1 mg/kg. A detailed characterization of BLM-induced fibrosis was performed 14 days after BLM administration using lung function testing, micro-computed tomography and Ashcroft scoring analysis. Quantification of fibrosis by automated analysis was assessed based on pulmonary tissue density measured from thousands of micro-tiles processed from digital images of entire lung sections. Prior to analysis, large bronchi and vessels were manually excluded from the original images. Measurement of fibrosis has been expressed by two indexes: the mean pulmonary tissue density and the high pulmonary tissue density frequency. We showed that tissue density indexes gave access to a very accurate and reliable quantification of morphological changes induced by BLM even for the lowest concentration used (0.25 mg/kg). A reconstructed 2D-image of the entire lung section at high resolution (3.6 μm/pixel) has been performed from tissue density values allowing the visualization of their distribution throughout fibrotic and non-fibrotic regions. A significant correlation (p<0.0001) was found between automated analysis and the above standard evaluation methods. This correlation establishes automated analysis as a novel end-point measure of BLM-induced lung fibrosis in mice, which will be very valuable for future preclinical drug explorations. PMID:28107543

Automated analysis of cell migration and nuclear envelope rupture in confined environments.

PubMed

Elacqua, Joshua J; McGregor, Alexandra L; Lammerding, Jan

2018-01-01

Recent in vitro and in vivo studies have highlighted the importance of the cell nucleus in governing migration through confined environments. Microfluidic devices that mimic the narrow interstitial spaces of tissues have emerged as important tools to study cellular dynamics during confined migration, including the consequences of nuclear deformation and nuclear envelope rupture. However, while image acquisition can be automated on motorized microscopes, the analysis of the corresponding time-lapse sequences for nuclear transit through the pores and events such as nuclear envelope rupture currently requires manual analysis. In addition to being highly time-consuming, such manual analysis is susceptible to person-to-person variability. Studies that compare large numbers of cell types and conditions therefore require automated image analysis to achieve sufficiently high throughput. Here, we present an automated image analysis program to register microfluidic constrictions and perform image segmentation to detect individual cell nuclei. The MATLAB program tracks nuclear migration over time and records constriction-transit events, transit times, transit success rates, and nuclear envelope rupture. Such automation reduces the time required to analyze migration experiments from weeks to hours, and removes the variability that arises from different human analysts. Comparison with manual analysis confirmed that both constriction transit and nuclear envelope rupture were detected correctly and reliably, and the automated analysis results closely matched a manual analysis gold standard. Applying the program to specific biological examples, we demonstrate its ability to detect differences in nuclear transit time between cells with different levels of the nuclear envelope proteins lamin A/C, which govern nuclear deformability, and to detect an increase in nuclear envelope rupture duration in cells in which CHMP7, a protein involved in nuclear envelope repair, had been depleted. The program thus presents a versatile tool for the study of confined migration and its effect on the cell nucleus.

SHARP: Automated monitoring of spacecraft health and status

NASA Technical Reports Server (NTRS)

Atkinson, David J.; James, Mark L.; Martin, R. Gaius

1991-01-01

Briefly discussed here are the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory (JPL). Some of the difficulties associated with the existing technology used in mission operations are highlighted. A new automated system based on artificial intelligence technology is described which seeks to overcome many of these limitations. The system, called the Spacecraft Health Automated Reasoning Prototype (SHARP), is designed to automate health and status analysis for multi-mission spacecraft and ground data systems operations. The system has proved to be effective for detecting and analyzing potential spacecraft and ground systems problems by performing real-time analysis of spacecraft and ground data systems engineering telemetry. Telecommunications link analysis of the Voyager 2 spacecraft was the initial focus for evaluation of the system in real-time operations during the Voyager spacecraft encounter with Neptune in August 1989.

SHARP - Automated monitoring of spacecraft health and status

NASA Technical Reports Server (NTRS)

Atkinson, David J.; James, Mark L.; Martin, R. G.

1990-01-01

Briefly discussed here are the spacecraft and ground systems monitoring process at the Jet Propulsion Laboratory (JPL). Some of the difficulties associated with the existing technology used in mission operations are highlighted. A new automated system based on artificial intelligence technology is described which seeks to overcome many of these limitations. The system, called the Spacecraft Health Automated Reasoning Prototype (SHARP), is designed to automate health and status analysis for multi-mission spacecraft and ground data systems operations. The system has proved to be effective for detecting and analyzing potential spacecraft and ground systems problems by performing real-time analysis of spacecraft and ground data systems engineering telemetry. Telecommunications link analysis of the Voyager 2 spacecraft was the initial focus for evaluation of the system in real-time operations during the Voyager spacecraft encounter with Neptune in August 1989.

A rule-based smart automated fertilization and irrigation systems

NASA Astrophysics Data System (ADS)

Yousif, Musab El-Rashid; Ghafar, Khairuddin; Zahari, Rahimi; Lim, Tiong Hoo

2018-04-01

Smart automation in industries has become very important as it can improve the reliability and efficiency of the systems. The use of smart technologies in agriculture have increased over the year to ensure and control the production of crop and address food security. However, it is important to use proper irrigation systems avoid water wastage and overfeeding of the plant. In this paper, a Smart Rule-based Automated Fertilization and Irrigation System is proposed and evaluated. We propose a rule based decision making algorithm to monitor and control the food supply to the plant and the soil quality. A build-in alert system is also used to update the farmer using a text message. The system is developed and evaluated using a real hardware.

A catalog of automated analysis methods for enterprise models.

PubMed

Florez, Hector; Sánchez, Mario; Villalobos, Jorge

2016-01-01

Enterprise models are created for documenting and communicating the structure and state of Business and Information Technologies elements of an enterprise. After models are completed, they are mainly used to support analysis. Model analysis is an activity typically based on human skills and due to the size and complexity of the models, this process can be complicated and omissions or miscalculations are very likely. This situation has fostered the research of automated analysis methods, for supporting analysts in enterprise analysis processes. By reviewing the literature, we found several analysis methods; nevertheless, they are based on specific situations and different metamodels; then, some analysis methods might not be applicable to all enterprise models. This paper presents the work of compilation (literature review), classification, structuring, and characterization of automated analysis methods for enterprise models, expressing them in a standardized modeling language. In addition, we have implemented the analysis methods in our modeling tool.

Text mining for the biocuration workflow

PubMed Central

Hirschman, Lynette; Burns, Gully A. P. C; Krallinger, Martin; Arighi, Cecilia; Cohen, K. Bretonnel; Valencia, Alfonso; Wu, Cathy H.; Chatr-Aryamontri, Andrew; Dowell, Karen G.; Huala, Eva; Lourenço, Anália; Nash, Robert; Veuthey, Anne-Lise; Wiegers, Thomas; Winter, Andrew G.

2012-01-01

Molecular biology has become heavily dependent on biological knowledge encoded in expert curated biological databases. As the volume of biological literature increases, biocurators need help in keeping up with the literature; (semi-) automated aids for biocuration would seem to be an ideal application for natural language processing and text mining. However, to date, there have been few documented successes for improving biocuration throughput using text mining. Our initial investigations took place for the workshop on ‘Text Mining for the BioCuration Workflow’ at the third International Biocuration Conference (Berlin, 2009). We interviewed biocurators to obtain workflows from eight biological databases. This initial study revealed high-level commonalities, including (i) selection of documents for curation; (ii) indexing of documents with biologically relevant entities (e.g. genes); and (iii) detailed curation of specific relations (e.g. interactions); however, the detailed workflows also showed many variabilities. Following the workshop, we conducted a survey of biocurators. The survey identified biocurator priorities, including the handling of full text indexed with biological entities and support for the identification and prioritization of documents for curation. It also indicated that two-thirds of the biocuration teams had experimented with text mining and almost half were using text mining at that time. Analysis of our interviews and survey provide a set of requirements for the integration of text mining into the biocuration workflow. These can guide the identification of common needs across curated databases and encourage joint experimentation involving biocurators, text mining developers and the larger biomedical research community. PMID:22513129

Text mining for the biocuration workflow.

PubMed

Hirschman, Lynette; Burns, Gully A P C; Krallinger, Martin; Arighi, Cecilia; Cohen, K Bretonnel; Valencia, Alfonso; Wu, Cathy H; Chatr-Aryamontri, Andrew; Dowell, Karen G; Huala, Eva; Lourenço, Anália; Nash, Robert; Veuthey, Anne-Lise; Wiegers, Thomas; Winter, Andrew G

2012-01-01

Molecular biology has become heavily dependent on biological knowledge encoded in expert curated biological databases. As the volume of biological literature increases, biocurators need help in keeping up with the literature; (semi-) automated aids for biocuration would seem to be an ideal application for natural language processing and text mining. However, to date, there have been few documented successes for improving biocuration throughput using text mining. Our initial investigations took place for the workshop on 'Text Mining for the BioCuration Workflow' at the third International Biocuration Conference (Berlin, 2009). We interviewed biocurators to obtain workflows from eight biological databases. This initial study revealed high-level commonalities, including (i) selection of documents for curation; (ii) indexing of documents with biologically relevant entities (e.g. genes); and (iii) detailed curation of specific relations (e.g. interactions); however, the detailed workflows also showed many variabilities. Following the workshop, we conducted a survey of biocurators. The survey identified biocurator priorities, including the handling of full text indexed with biological entities and support for the identification and prioritization of documents for curation. It also indicated that two-thirds of the biocuration teams had experimented with text mining and almost half were using text mining at that time. Analysis of our interviews and survey provide a set of requirements for the integration of text mining into the biocuration workflow. These can guide the identification of common needs across curated databases and encourage joint experimentation involving biocurators, text mining developers and the larger biomedical research community.

Comparison of Manual Versus Automated Data Collection Method for an Evidence-Based Nursing Practice Study

PubMed Central

Byrne, M.D.; Jordan, T.R.; Welle, T.

2013-01-01

Objective The objective of this study was to investigate and improve the use of automated data collection procedures for nursing research and quality assurance. Methods A descriptive, correlational study analyzed 44 orthopedic surgical patients who were part of an evidence-based practice (EBP) project examining post-operative oxygen therapy at a Midwestern hospital. The automation work attempted to replicate a manually-collected data set from the EBP project. Results Automation was successful in replicating data collection for study data elements that were available in the clinical data repository. The automation procedures identified 32 “false negative” patients who met the inclusion criteria described in the EBP project but were not selected during the manual data collection. Automating data collection for certain data elements, such as oxygen saturation, proved challenging because of workflow and practice variations and the reliance on disparate sources for data abstraction. Automation also revealed instances of human error including computational and transcription errors as well as incomplete selection of eligible patients. Conclusion Automated data collection for analysis of nursing-specific phenomenon is potentially superior to manual data collection methods. Creation of automated reports and analysis may require initial up-front investment with collaboration between clinicians, researchers and information technology specialists who can manage the ambiguities and challenges of research and quality assurance work in healthcare. PMID:23650488

Comparison of manual & automated analysis methods for corneal endothelial cell density measurements by specular microscopy.

PubMed

Huang, Jianyan; Maram, Jyotsna; Tepelus, Tudor C; Modak, Cristina; Marion, Ken; Sadda, SriniVas R; Chopra, Vikas; Lee, Olivia L

2017-08-07

To determine the reliability of corneal endothelial cell density (ECD) obtained by automated specular microscopy versus that of validated manual methods and factors that predict such reliability. Sharp central images from 94 control and 106 glaucomatous eyes were captured with Konan specular microscope NSP-9900. All images were analyzed by trained graders using Konan CellChek Software, employing the fully- and semi-automated methods as well as Center Method. Images with low cell count (input cells number <100) and/or guttata were compared with the Center and Flex-Center Methods. ECDs were compared and absolute error was used to assess variation. The effect on ECD of age, cell count, cell size, and cell size variation was evaluated. No significant difference was observed between the Center and Flex-Center Methods in corneas with guttata (p=0.48) or low ECD (p=0.11). No difference (p=0.32) was observed in ECD of normal controls <40 yrs old between the fully-automated method and manual Center Method. However, in older controls and glaucomatous eyes, ECD was overestimated by the fully-automated method (p=0.034) and semi-automated method (p=0.025) as compared to manual method. Our findings show that automated analysis significantly overestimates ECD in the eyes with high polymegathism and/or large cell size, compared to the manual method. Therefore, we discourage reliance upon the fully-automated method alone to perform specular microscopy analysis, particularly if an accurate ECD value is imperative. Copyright © 2017. Published by Elsevier España, S.L.U.

Automated Student Aid Processing: The Challenge and Opportunity.

ERIC Educational Resources Information Center

St. John, Edward P.

1985-01-01

To utilize automated technology for student aid processing, it is necessary to work with multi-institutional offices (student aid, admissions, registration, and business) and to develop automated interfaces with external processing systems at state and federal agencies and perhaps at need-analysis organizations and lenders. (MLW)

Automated image analysis of placental villi and syncytial knots in histological sections.

PubMed

Kidron, Debora; Vainer, Ifat; Fisher, Yael; Sharony, Reuven

2017-05-01

Delayed villous maturation and accelerated villous maturation diagnosed in histologic sections are morphologic manifestations of pathophysiological conditions. The inter-observer agreement among pathologists in assessing these conditions is moderate at best. We investigated whether automated image analysis of placental villi and syncytial knots could improve standardization in diagnosing these conditions. Placentas of antepartum fetal death at or near term were diagnosed as normal, delayed or accelerated villous maturation. Histologic sections of 5 cases per group were photographed at ×10 magnification. Automated image analysis of villi and syncytial knots was performed, using ImageJ public domain software. Analysis of hundreds of histologic images was carried out within minutes on a personal computer, using macro commands. Compared to normal placentas, villi from delayed maturation were larger and fewer, with fewer and smaller syncytial knots. Villi from accelerated maturation were smaller. The data were further analyzed according to horizontal placental zones and groups of villous size. Normal placentas can be discriminated from placentas of delayed or accelerated villous maturation using automated image analysis. Automated image analysis of villi and syncytial knots is not equivalent to interpretation by the human eye. Each method has advantages and disadvantages in assessing the 2-dimensional histologic sections representing the complex, 3-dimensional villous tree. Image analysis of placentas provides quantitative data that might help in standardizing and grading of placentas for diagnostic and research purposes. Copyright © 2017 Elsevier Ltd. All rights reserved.

NMR-based automated protein structure determination.

PubMed

Würz, Julia M; Kazemi, Sina; Schmidt, Elena; Bagaria, Anurag; Güntert, Peter

2017-08-15

NMR spectra analysis for protein structure determination can now in many cases be performed by automated computational methods. This overview of the computational methods for NMR protein structure analysis presents recent automated methods for signal identification in multidimensional NMR spectra, sequence-specific resonance assignment, collection of conformational restraints, and structure calculation, as implemented in the CYANA software package. These algorithms are sufficiently reliable and integrated into one software package to enable the fully automated structure determination of proteins starting from NMR spectra without manual interventions or corrections at intermediate steps, with an accuracy of 1-2 Å backbone RMSD in comparison with manually solved reference structures. Copyright © 2017 Elsevier Inc. All rights reserved.

Dynamic CT myocardial perfusion imaging: performance of 3D semi-automated evaluation software.

PubMed

Ebersberger, Ullrich; Marcus, Roy P; Schoepf, U Joseph; Lo, Gladys G; Wang, Yining; Blanke, Philipp; Geyer, Lucas L; Gray, J Cranston; McQuiston, Andrew D; Cho, Young Jun; Scheuering, Michael; Canstein, Christian; Nikolaou, Konstantin; Hoffmann, Ellen; Bamberg, Fabian

2014-01-01

To evaluate the performance of three-dimensional semi-automated evaluation software for the assessment of myocardial blood flow (MBF) and blood volume (MBV) at dynamic myocardial perfusion computed tomography (CT). Volume-based software relying on marginal space learning and probabilistic boosting tree-based contour fitting was applied to CT myocardial perfusion imaging data of 37 subjects. In addition, all image data were analysed manually and both approaches were compared with SPECT findings. Study endpoints included time of analysis and conventional measures of diagnostic accuracy. Of 592 analysable segments, 42 showed perfusion defects on SPECT. Average analysis times for the manual and software-based approaches were 49.1 ± 11.2 and 16.5 ± 3.7 min respectively (P < 0.01). There was strong agreement between the two measures of interest (MBF, ICC = 0.91, and MBV, ICC = 0.88, both P < 0.01) and no significant difference in MBF/MBV with respect to diagnostic accuracy between the two approaches for both MBF and MBV for manual versus software-based approach; respectively; all comparisons P > 0.05. Three-dimensional semi-automated evaluation of dynamic myocardial perfusion CT data provides similar measures and diagnostic accuracy to manual evaluation, albeit with substantially reduced analysis times. This capability may aid the integration of this test into clinical workflows. • Myocardial perfusion CT is attractive for comprehensive coronary heart disease assessment. • Traditional image analysis methods are cumbersome and time-consuming. • Automated 3D perfusion software shortens analysis times. • Automated 3D perfusion software increases standardisation of myocardial perfusion CT. • Automated, standardised analysis fosters myocardial perfusion CT integration into clinical practice.

Modeling Hydraulic Components for Automated FMEA of a Braking System

DTIC Science & Technology

2014-12-23

Modeling Hydraulic Components for Automated FMEA of a Braking System Peter Struss, Alessandro Fraracci Tech. Univ. of Munich, 85748 Garching...Germany struss@in.tum.de ABSTRACT This paper presents work on model-based automation of failure-modes-and-effects analysis ( FMEA ) applied to...the hydraulic part of a vehicle braking system. We describe the FMEA task and the application problem and outline the foundations for automating the

Text Stream Trend Analysis using Multiscale Visual Analytics with Applications to Social Media Systems

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

Steed, Chad A; Beaver, Justin M; BogenII, Paul L.

In this paper, we introduce a new visual analytics system, called Matisse, that allows exploration of global trends in textual information streams with specific application to social media platforms. Despite the potential for real-time situational awareness using these services, interactive analysis of such semi-structured textual information is a challenge due to the high-throughput and high-velocity properties. Matisse addresses these challenges through the following contributions: (1) robust stream data management, (2) automated sen- timent/emotion analytics, (3) inferential temporal, geospatial, and term-frequency visualizations, and (4) a flexible drill-down interaction scheme that progresses from macroscale to microscale views. In addition to describing thesemore » contributions, our work-in-progress paper concludes with a practical case study focused on the analysis of Twitter 1% sample stream information captured during the week of the Boston Marathon bombings.« less

Optimizing the balance between task automation and human manual control in simulated submarine track management.

PubMed

Chen, Stephanie I; Visser, Troy A W; Huf, Samuel; Loft, Shayne

2017-09-01

Automation can improve operator performance and reduce workload, but can also degrade operator situation awareness (SA) and the ability to regain manual control. In 3 experiments, we examined the extent to which automation could be designed to benefit performance while ensuring that individuals maintained SA and could regain manual control. Participants completed a simulated submarine track management task under varying task load. The automation was designed to facilitate information acquisition and analysis, but did not make task decisions. Relative to a condition with no automation, the continuous use of automation improved performance and reduced subjective workload, but degraded SA. Automation that was engaged and disengaged by participants as required (adaptable automation) moderately improved performance and reduced workload relative to no automation, but degraded SA. Automation engaged and disengaged based on task load (adaptive automation) provided no benefit to performance or workload, and degraded SA relative to no automation. Automation never led to significant return-to-manual deficits. However, all types of automation led to degraded performance on a nonautomated task that shared information processing requirements with automated tasks. Given these outcomes, further research is urgently required to establish how to design automation to maximize performance while keeping operators cognitively engaged. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Understanding human management of automation errors

PubMed Central

McBride, Sara E.; Rogers, Wendy A.; Fisk, Arthur D.

2013-01-01

Automation has the potential to aid humans with a diverse set of tasks and support overall system performance. Automated systems are not always reliable, and when automation errs, humans must engage in error management, which is the process of detecting, understanding, and correcting errors. However, this process of error management in the context of human-automation interaction is not well understood. Therefore, we conducted a systematic review of the variables that contribute to error management. We examined relevant research in human-automation interaction and human error to identify critical automation, person, task, and emergent variables. We propose a framework for management of automation errors to incorporate and build upon previous models. Further, our analysis highlights variables that may be addressed through design and training to positively influence error management. Additional efforts to understand the error management process will contribute to automation designed and implemented to support safe and effective system performance. PMID:25383042

Understanding human management of automation errors.

PubMed

McBride, Sara E; Rogers, Wendy A; Fisk, Arthur D

2014-01-01

Automation has the potential to aid humans with a diverse set of tasks and support overall system performance. Automated systems are not always reliable, and when automation errs, humans must engage in error management, which is the process of detecting, understanding, and correcting errors. However, this process of error management in the context of human-automation interaction is not well understood. Therefore, we conducted a systematic review of the variables that contribute to error management. We examined relevant research in human-automation interaction and human error to identify critical automation, person, task, and emergent variables. We propose a framework for management of automation errors to incorporate and build upon previous models. Further, our analysis highlights variables that may be addressed through design and training to positively influence error management. Additional efforts to understand the error management process will contribute to automation designed and implemented to support safe and effective system performance.

Exploratory Study of Web-Based Planning and Mobile Text Reminders in an Overweight Population

PubMed Central

Murray, Peter; Cobain, Mark; Chinapaw, Mai; van Mechelen, Willem; Hurling, Robert

2011-01-01

Background Forming specific health plans can help translate good intentions into action. Mobile text reminders can further enhance the effects of planning on behavior. Objective Our aim was to explore the combined impact of a Web-based, fully automated planning tool and mobile text reminders on intention to change saturated fat intake, self-reported saturated fat intake, and portion size changes over 4 weeks. Methods Of 1013 men and women recruited online, 858 were randomly allocated to 1 of 3 conditions: a planning tool (PT), combined planning tool and text reminders (PTT), and a control group. All outcome measures were assessed by online self-reports. Analysis of covariance was used to analyze the data. Results Participants allocated to the PT (meansat urated fat 3.6, meancopingplanning 3) and PTT (meansaturatedfat 3.5, meancopingplanning 3.1) reported a lower consumption of high-fat foods (F 2,571 = 4.74, P = .009) and higher levels of coping planning (F 2,571 = 7.22, P < .001) than the control group (meansat urated f at 3.9, meancopingplanning 2.8). Participants in the PTT condition also reported smaller portion sizes of high-fat foods (mean 2.8; F 2, 569 = 4.12, P = .0) than the control group (meanportions 3.1). The reduction in portion size was driven primarily by the male participants in the PTT (P = .003). We found no significant group differences in terms of percentage saturated fat intake, intentions, action planning, self-efficacy, or feedback on the intervention. Conclusions These findings support the use of Web-based tools and mobile technologies to change dietary behavior. The combination of a fully automated Web-based planning tool with mobile text reminders led to lower self-reported consumption of high-fat foods and greater reductions in portion sizes than in a control condition. Trial Registration International Standard Randomized Controlled Trial Number (ISRCTN): 61819220; http://www.controlled-trials.com/ISRCTN61819220 (Archived by WebCite at http://www.webcitation.org/63YiSy6R8) PMID:22182483

Effects of Automation Types on Air Traffic Controller Situation Awareness and Performance

NASA Technical Reports Server (NTRS)

Sethumadhavan, A.

2009-01-01

The Joint Planning and Development Office has proposed the introduction of automated systems to help air traffic controllers handle the increasing volume of air traffic in the next two decades (JPDO, 2007). Because fully automated systems leave operators out of the decision-making loop (e.g., Billings, 1991), it is important to determine the right level and type of automation that will keep air traffic controllers in the loop. This study examined the differences in the situation awareness (SA) and collision detection performance of individuals when they worked with information acquisition, information analysis, decision and action selection and action implementation automation to control air traffic (Parasuraman, Sheridan, & Wickens, 2000). When the automation was unreliable, the time taken to detect an upcoming collision was significantly longer for all the automation types compared with the information acquisition automation. This poor performance following automation failure was mediated by SA, with lower SA yielding poor performance. Thus, the costs associated with automation failure are greater when automation is applied to higher order stages of information processing. Results have practical implications for automation design and development of SA training programs.

Influence of Perceived Interactivity of a Sexual Health Text Message Service on Young People's Attitudes, Satisfaction and Repeat Use

ERIC Educational Resources Information Center

Willoughby, Jessica Fitts; L'Engle, Kelly Ladin

2015-01-01

Sexual health text message services are becoming an increasingly popular way to reach young people with sexual health information. A variety of service types exist: some send automated messages on a set schedule; others provide personalized responses to individual questions. Young people's perceptions of interactivity, which is often based on…

SMS for Sexual Health: A Comparison of Service Types and Recommendations for Sexual Health Text Message Service Providers

ERIC Educational Resources Information Center

Willoughby, Jessica Fitts; Muldrow, Adrienne

2017-01-01

Objectives: Text message-based interventions may provide sexual health information to young people through a number of service types, from sending information on a regularly scheduled timeline, to providing an automated menu, to allowing young people to connect directly with health educators. While such service types exist, it is not clear which…

An Approach for Automatic Generation of Adaptive Hypermedia in Education with Multilingual Knowledge Discovery Techniques

ERIC Educational Resources Information Center

Alfonseca, Enrique; Rodriguez, Pilar; Perez, Diana

2007-01-01

This work describes a framework that combines techniques from Adaptive Hypermedia and Natural Language processing in order to create, in a fully automated way, on-line information systems from linear texts in electronic format, such as textbooks. The process is divided into two steps: an "off-line" processing step, which analyses the source text,…

Evaluation of transit operations : data applications of Tri-Met's automated bus dispatching system

DOT National Transportation Integrated Search

2001-02-01

This paper presents an analysis of operating performance for Tri-Met, the transit provider for the Portland, Oregon metropolitan area. The analysis draws on data recovered by Tri-Met's automated Bus Dispatching System (BDS) and focuses on two main su...

Benefit Analysis of the Automated Flow Control Function of the Air Traffic Control Systems Command Center

DOT National Transportation Integrated Search

1977-06-01

This report summarizes the findings of a benefit analysis study of the present and proposed Air Traffic Control Systems Command Center automation systems. The benefits analyzed were those associated with Fuel Advisory Departure and Quota Flow procedu...

Trace-Level Automated Mercury Speciation Analysis

PubMed Central

Taylor, Vivien F.; Carter, Annie; Davies, Colin; Jackson, Brian P.

2011-01-01

An automated system for methyl Hg analysis by purge and trap gas chromatography (GC) was evaluated, with comparison of several different instrument configurations including chromatography columns (packed column or capillary), detector (atomic fluorescence, AFS, or inductively coupled plasma mass spectrometry, ICP-MS, using quadrupole and sector field ICP- MS instruments). Method detection limits (MDL) of 0.042 pg and 0.030 pg for CH3Hg+ were achieved with the automated Hg analysis system configured with AFS and ICPMS detection, respectively. Capillary GC with temperature programming was effective in improving resolution and decreasing retention times of heavier Hg species (in this case C3H7Hg+) although carryover between samples was increased. With capillary GC, the MDL for CH3Hg+ was 0.25 pg for AFS detection and 0.060 pg for ICP-MS detection. The automated system was demonstrated to have high throughput (72 samples analyzed in 8 hours) requiring considerably less analyst time than the manual method for methyl mercury analysis described in EPA 1630. PMID:21572543

A time-series method for automated measurement of changes in mitotic and interphase duration from time-lapse movies.

PubMed

Sigoillot, Frederic D; Huckins, Jeremy F; Li, Fuhai; Zhou, Xiaobo; Wong, Stephen T C; King, Randall W

2011-01-01

Automated time-lapse microscopy can visualize proliferation of large numbers of individual cells, enabling accurate measurement of the frequency of cell division and the duration of interphase and mitosis. However, extraction of quantitative information by manual inspection of time-lapse movies is too time-consuming to be useful for analysis of large experiments. Here we present an automated time-series approach that can measure changes in the duration of mitosis and interphase in individual cells expressing fluorescent histone 2B. The approach requires analysis of only 2 features, nuclear area and average intensity. Compared to supervised learning approaches, this method reduces processing time and does not require generation of training data sets. We demonstrate that this method is as sensitive as manual analysis in identifying small changes in interphase or mitotic duration induced by drug or siRNA treatment. This approach should facilitate automated analysis of high-throughput time-lapse data sets to identify small molecules or gene products that influence timing of cell division.

An entirely automated method to score DSS-induced colitis in mice by digital image analysis of pathology slides

PubMed Central

Kozlowski, Cleopatra; Jeet, Surinder; Beyer, Joseph; Guerrero, Steve; Lesch, Justin; Wang, Xiaoting; DeVoss, Jason; Diehl, Lauri

2013-01-01

SUMMARY The DSS (dextran sulfate sodium) model of colitis is a mouse model of inflammatory bowel disease. Microscopic symptoms include loss of crypt cells from the gut lining and infiltration of inflammatory cells into the colon. An experienced pathologist requires several hours per study to score histological changes in selected regions of the mouse gut. In order to increase the efficiency of scoring, Definiens Developer software was used to devise an entirely automated method to quantify histological changes in the whole H&E slide. When the algorithm was applied to slides from historical drug-discovery studies, automated scores classified 88% of drug candidates in the same way as pathologists’ scores. In addition, another automated image analysis method was developed to quantify colon-infiltrating macrophages, neutrophils, B cells and T cells in immunohistochemical stains of serial sections of the H&E slides. The timing of neutrophil and macrophage infiltration had the highest correlation to pathological changes, whereas T and B cell infiltration occurred later. Thus, automated image analysis enables quantitative comparisons between tissue morphology changes and cell-infiltration dynamics. PMID:23580198

The Nature of Automated Jobs and Their Educational and Training Requirements.

ERIC Educational Resources Information Center

Fine, S.A.

Objective information concerning the impact of automation on educational and training requirements was obtained for 132 employees engaged in electron tube, computer, and steel manufacturing processes through management questionnaire responses, analysis of job functions, and employer interviews before and after the introduction of automation. The…

AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT (AGWA): A GIS-BASED HYDROLOGIC MODELING TOOL FOR WATERSHED ASSESSMENT AND ANALYSIS

EPA Science Inventory

The Automated Geospatial Watershed Assessment tool (AGWA) is a GIS interface jointly developed by the USDA Agricultural Research Service, the U.S. Environmental Protection Agency, the University of Arizona, and the University of Wyoming to automate the parameterization and execu...

AUTOMATED GEOSPATICAL WATERSHED ASSESSMENT (AGWA): A GIS-BASED HYDROLOICAL MODELING TOOL FOR WATERSHED ASSESSMENT AND ANALYSIS

EPA Science Inventory

The Automated Geospatial Watershed Assessment tool (AGWA) is a GIS interface jointly developed by the USDA Agricultural Research Service, the U.S. Environmental Protection Agency, the University of Arizona, and the University of Wyoming to automate the parameterization and execut...

Migration monitoring with automated technology

Treesearch

Rhonda L. Millikin

2005-01-01

Automated technology can supplement ground-based methods of migration monitoring by providing: (1) unbiased and automated sampling; (2) independent validation of current methods; (3) a larger sample area for landscape-level analysis of habitat selection for stopover, and (4) an opportunity to study flight behavior. In particular, radar-acoustic sensor fusion can...

Automated grading system for evaluation of ocular redness associated with dry eye.

PubMed

Rodriguez, John D; Johnston, Patrick R; Ousler, George W; Smith, Lisa M; Abelson, Mark B

2013-01-01

We have observed that dry eye redness is characterized by a prominence of fine horizontal conjunctival vessels in the exposed ocular surface of the interpalpebral fissure, and have incorporated this feature into the grading of redness in clinical studies of dry eye. To develop an automated method of grading dry eye-associated ocular redness in order to expand on the clinical grading system currently used. Ninety nine images from 26 dry eye subjects were evaluated by five graders using a 0-4 (in 0.5 increments) dry eye redness (Ora Calibra™ Dry Eye Redness Scale [OCDER]) scale. For the automated method, the Opencv computer vision library was used to develop software for calculating redness and horizontal conjunctival vessels (noted as "horizontality"). From original photograph, the region of interest (ROI) was selected manually using the open source ImageJ software. Total average redness intensity (Com-Red) was calculated as a single channel 8-bit image as R - 0.83G - 0.17B, where R, G and B were the respective intensities of the red, green and blue channels. The location of vessels was detected by normalizing the blue channel and selecting pixels with an intensity of less than 97% of the mean. The horizontal component (Com-Hor) was calculated by the first order Sobel derivative in the vertical direction and the score was calculated as the average blue channel image intensity of this vertical derivative. Pearson correlation coefficients, accuracy and concordance correlation coefficients (CCC) were calculated after regression and standardized regression of the dataset. The agreement (both Pearson's and CCC) among investigators using the OCDER scale was 0.67, while the agreement of investigator to computer was 0.76. A multiple regression using both redness and horizontality improved the agreement CCC from 0.66 and 0.69 to 0.76, demonstrating the contribution of vessel geometry to the overall grade. Computer analysis of a given image has 100% repeatability and zero variability from session to session. This objective means of grading ocular redness in a unified fashion has potential significance as a new clinical endpoint. In comparisons between computer and investigator, computer grading proved to be more reliable than another investigator using the OCDER scale. The best fitting model based on the present sample, and usable for future studies, was [Formula: see text] is the predicted investigator grade, and [Formula: see text] and [Formula: see text] are logarithmic transformations of the computer calculated parameters COM-Hor and COM-Red. Considering the superior repeatability, computer automated grading might be preferable to investigator grading in multicentered dry eye studies in which the subtle differences in redness incurred by treatment have been historically difficult to define.

Fully automated corneal endothelial morphometry of images captured by clinical specular microscopy

NASA Astrophysics Data System (ADS)

Bucht, Curry; Söderberg, Per; Manneberg, Göran

2010-02-01

The corneal endothelium serves as the posterior barrier of the cornea. Factors such as clarity and refractive properties of the cornea are in direct relationship to the quality of the endothelium. The endothelial cell density is considered the most important morphological factor of the corneal endothelium. Pathological conditions and physical trauma may threaten the endothelial cell density to such an extent that the optical property of the cornea and thus clear eyesight is threatened. Diagnosis of the corneal endothelium through morphometry is an important part of several clinical applications. Morphometry of the corneal endothelium is presently carried out by semi automated analysis of pictures captured by a Clinical Specular Microscope (CSM). Because of the occasional need of operator involvement, this process can be tedious, having a negative impact on sampling size. This study was dedicated to the development and use of fully automated analysis of a very large range of images of the corneal endothelium, captured by CSM, using Fourier analysis. Software was developed in the mathematical programming language Matlab. Pictures of the corneal endothelium, captured by CSM, were read into the analysis software. The software automatically performed digital enhancement of the images, normalizing lights and contrasts. The digitally enhanced images of the corneal endothelium were Fourier transformed, using the fast Fourier transform (FFT) and stored as new images. Tools were developed and applied for identification and analysis of relevant characteristics of the Fourier transformed images. The data obtained from each Fourier transformed image was used to calculate the mean cell density of its corresponding corneal endothelium. The calculation was based on well known diffraction theory. Results in form of estimated cell density of the corneal endothelium were obtained, using fully automated analysis software on 292 images captured by CSM. The cell density obtained by the fully automated analysis was compared to the cell density obtained from classical, semi-automated analysis and a relatively large correlation was found.

Automation of ALK gene rearrangement testing with fluorescence in situ hybridization (FISH): a feasibility study.

PubMed

Zwaenepoel, Karen; Merkle, Dennis; Cabillic, Florian; Berg, Erica; Belaud-Rotureau, Marc-Antoine; Grazioli, Vittorio; Herelle, Olga; Hummel, Michael; Le Calve, Michele; Lenze, Dido; Mende, Stefanie; Pauwels, Patrick; Quilichini, Benoit; Repetti, Elena

2015-02-01

In the past several years we have observed a significant increase in our understanding of molecular mechanisms that drive lung cancer. Specifically in the non-small cell lung cancer sub-types, ALK gene rearrangements represent a sub-group of tumors that are targetable by the tyrosine kinase inhibitor Crizotinib, resulting in significant reductions in tumor burden. Phase II and III clinical trials were performed using an ALK break-apart FISH probe kit, making FISH the gold standard for identifying ALK rearrangements in patients. FISH is often considered a labor and cost intensive molecular technique, and in this study we aimed to demonstrate feasibility for automation of ALK FISH testing, to improve laboratory workflow and ease of testing. This involved automation of the pre-treatment steps of the ALK assay using various protocols on the VP 2000 instrument, and facilitating automated scanning of the fluorescent FISH specimens for simplified enumeration on various backend scanning and analysis systems. The results indicated that ALK FISH can be automated. Significantly, both the Ikoniscope and BioView system of automated FISH scanning and analysis systems provided a robust analysis algorithm to define ALK rearrangements. In addition, the BioView system facilitated consultation of difficult cases via the internet. Copyright © 2015 Elsevier Inc. All rights reserved.

Fully Automated Sample Preparation for Ultrafast N-Glycosylation Analysis of Antibody Therapeutics.

PubMed

Szigeti, Marton; Lew, Clarence; Roby, Keith; Guttman, Andras

2016-04-01

There is a growing demand in the biopharmaceutical industry for high-throughput, large-scale N-glycosylation profiling of therapeutic antibodies in all phases of product development, but especially during clone selection when hundreds of samples should be analyzed in a short period of time to assure their glycosylation-based biological activity. Our group has recently developed a magnetic bead-based protocol for N-glycosylation analysis of glycoproteins to alleviate the hard-to-automate centrifugation and vacuum-centrifugation steps of the currently used protocols. Glycan release, fluorophore labeling, and cleanup were all optimized, resulting in a <4 h magnetic bead-based process with excellent yield and good repeatability. This article demonstrates the next level of this work by automating all steps of the optimized magnetic bead-based protocol from endoglycosidase digestion, through fluorophore labeling and cleanup with high-throughput sample processing in 96-well plate format, using an automated laboratory workstation. Capillary electrophoresis analysis of the fluorophore-labeled glycans was also optimized for rapid (<3 min) separation to accommodate the high-throughput processing of the automated sample preparation workflow. Ultrafast N-glycosylation analyses of several commercially relevant antibody therapeutics are also shown and compared to their biosimilar counterparts, addressing the biological significance of the differences. © 2015 Society for Laboratory Automation and Screening.

Automated single-trial assessment of laser-evoked potentials as an objective functional diagnostic tool for the nociceptive system.

PubMed

Hatem, S M; Hu, L; Ragé, M; Gierasimowicz, A; Plaghki, L; Bouhassira, D; Attal, N; Iannetti, G D; Mouraux, A

2012-12-01

To assess the clinical usefulness of an automated analysis of event-related potentials (ERPs). Nociceptive laser-evoked potentials (LEPs) and non-nociceptive somatosensory electrically-evoked potentials (SEPs) were recorded in 37 patients with syringomyelia and 21 controls. LEP and SEP peak amplitudes and latencies were estimated using a single-trial automated approach based on time-frequency wavelet filtering and multiple linear regression, as well as a conventional approach based on visual inspection. The amplitudes and latencies of normal and abnormal LEP and SEP peaks were identified reliably using both approaches, with similar sensitivity and specificity. Because the automated approach provided an unbiased solution to account for average waveforms where no ERP could be identified visually, it revealed significant differences between patients and controls that were not revealed using the visual approach. The automated analysis of ERPs characterized reliably and objectively LEP and SEP waveforms in patients. The automated single-trial analysis can be used to characterize normal and abnormal ERPs with a similar sensitivity and specificity as visual inspection. While this does not justify its use in a routine clinical setting, the technique could be useful to avoid observer-dependent biases in clinical research. Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Applications of pathology-assisted image analysis of immunohistochemistry-based biomarkers in oncology.

PubMed

Shinde, V; Burke, K E; Chakravarty, A; Fleming, M; McDonald, A A; Berger, A; Ecsedy, J; Blakemore, S J; Tirrell, S M; Bowman, D

2014-01-01

Immunohistochemistry-based biomarkers are commonly used to understand target inhibition in key cancer pathways in preclinical models and clinical studies. Automated slide-scanning and advanced high-throughput image analysis software technologies have evolved into a routine methodology for quantitative analysis of immunohistochemistry-based biomarkers. Alongside the traditional pathology H-score based on physical slides, the pathology world is welcoming digital pathology and advanced quantitative image analysis, which have enabled tissue- and cellular-level analysis. An automated workflow was implemented that includes automated staining, slide-scanning, and image analysis methodologies to explore biomarkers involved in 2 cancer targets: Aurora A and NEDD8-activating enzyme (NAE). The 2 workflows highlight the evolution of our immunohistochemistry laboratory and the different needs and requirements of each biological assay. Skin biopsies obtained from MLN8237 (Aurora A inhibitor) phase 1 clinical trials were evaluated for mitotic and apoptotic index, while mitotic index and defects in chromosome alignment and spindles were assessed in tumor biopsies to demonstrate Aurora A inhibition. Additionally, in both preclinical xenograft models and an acute myeloid leukemia phase 1 trial of the NAE inhibitor MLN4924, development of a novel image algorithm enabled measurement of downstream pathway modulation upon NAE inhibition. In the highlighted studies, developing a biomarker strategy based on automated image analysis solutions enabled project teams to confirm target and pathway inhibition and understand downstream outcomes of target inhibition with increased throughput and quantitative accuracy. These case studies demonstrate a strategy that combines a pathologist's expertise with automated image analysis to support oncology drug discovery and development programs.

An ultraviolet-visible spectrophotometer automation system. Part 3: Program documentation

NASA Astrophysics Data System (ADS)

Roth, G. S.; Teuschler, J. M.; Budde, W. L.

1982-07-01

The Ultraviolet-Visible Spectrophotometer (UVVIS) automation system accomplishes 'on-line' spectrophotometric quality assurance determinations, report generations, plot generations and data reduction for chlorophyll or color analysis. This system also has the capability to process manually entered data for the analysis of chlorophyll or color. For each program of the UVVIS system, this document contains a program description, flowchart, variable dictionary, code listing, and symbol cross-reference table. Also included are descriptions of file structures and of routines common to all automated analyses. The programs are written in Data General extended BASIC, Revision 4.3, under the RDOS operating systems, Revision 6.2. The BASIC code has been enhanced for real-time data acquisition, which is accomplished by CALLS to assembly language subroutines. Two other related publications are 'An Ultraviolet-Visible Spectrophotometer Automation System - Part I Functional Specifications,' and 'An Ultraviolet-Visible Spectrophotometer Automation System - Part II User's Guide.'

Reliability of fully automated versus visually controlled pre- and post-processing of resting-state EEG.

PubMed

Hatz, F; Hardmeier, M; Bousleiman, H; Rüegg, S; Schindler, C; Fuhr, P

2015-02-01

To compare the reliability of a newly developed Matlab® toolbox for the fully automated, pre- and post-processing of resting state EEG (automated analysis, AA) with the reliability of analysis involving visually controlled pre- and post-processing (VA). 34 healthy volunteers (age: median 38.2 (20-49), 82% female) had three consecutive 256-channel resting-state EEG at one year intervals. Results of frequency analysis of AA and VA were compared with Pearson correlation coefficients, and reliability over time was assessed with intraclass correlation coefficients (ICC). Mean correlation coefficient between AA and VA was 0.94±0.07, mean ICC for AA 0.83±0.05 and for VA 0.84±0.07. AA and VA yield very similar results for spectral EEG analysis and are equally reliable. AA is less time-consuming, completely standardized, and independent of raters and their training. Automated processing of EEG facilitates workflow in quantitative EEG analysis. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Automated model-based quantitative analysis of phantoms with spherical inserts in FDG PET scans.

PubMed

Ulrich, Ethan J; Sunderland, John J; Smith, Brian J; Mohiuddin, Imran; Parkhurst, Jessica; Plichta, Kristin A; Buatti, John M; Beichel, Reinhard R

2018-01-01

Quality control plays an increasingly important role in quantitative PET imaging and is typically performed using phantoms. The purpose of this work was to develop and validate a fully automated analysis method for two common PET/CT quality assurance phantoms: the NEMA NU-2 IQ and SNMMI/CTN oncology phantom. The algorithm was designed to only utilize the PET scan to enable the analysis of phantoms with thin-walled inserts. We introduce a model-based method for automated analysis of phantoms with spherical inserts. Models are first constructed for each type of phantom to be analyzed. A robust insert detection algorithm uses the model to locate all inserts inside the phantom. First, candidates for inserts are detected using a scale-space detection approach. Second, candidates are given an initial label using a score-based optimization algorithm. Third, a robust model fitting step aligns the phantom model to the initial labeling and fixes incorrect labels. Finally, the detected insert locations are refined and measurements are taken for each insert and several background regions. In addition, an approach for automated selection of NEMA and CTN phantom models is presented. The method was evaluated on a diverse set of 15 NEMA and 20 CTN phantom PET/CT scans. NEMA phantoms were filled with radioactive tracer solution at 9.7:1 activity ratio over background, and CTN phantoms were filled with 4:1 and 2:1 activity ratio over background. For quantitative evaluation, an independent reference standard was generated by two experts using PET/CT scans of the phantoms. In addition, the automated approach was compared against manual analysis, which represents the current clinical standard approach, of the PET phantom scans by four experts. The automated analysis method successfully detected and measured all inserts in all test phantom scans. It is a deterministic algorithm (zero variability), and the insert detection RMS error (i.e., bias) was 0.97, 1.12, and 1.48 mm for phantom activity ratios 9.7:1, 4:1, and 2:1, respectively. For all phantoms and at all contrast ratios, the average RMS error was found to be significantly lower for the proposed automated method compared to the manual analysis of the phantom scans. The uptake measurements produced by the automated method showed high correlation with the independent reference standard (R 2 ≥ 0.9987). In addition, the average computing time for the automated method was 30.6 s and was found to be significantly lower (P ≪ 0.001) compared to manual analysis (mean: 247.8 s). The proposed automated approach was found to have less error when measured against the independent reference than the manual approach. It can be easily adapted to other phantoms with spherical inserts. In addition, it eliminates inter- and intraoperator variability in PET phantom analysis and is significantly more time efficient, and therefore, represents a promising approach to facilitate and simplify PET standardization and harmonization efforts. © 2017 American Association of Physicists in Medicine.

Automated selected reaction monitoring data analysis workflow for large-scale targeted proteomic studies.

PubMed

Surinova, Silvia; Hüttenhain, Ruth; Chang, Ching-Yun; Espona, Lucia; Vitek, Olga; Aebersold, Ruedi

2013-08-01

Targeted proteomics based on selected reaction monitoring (SRM) mass spectrometry is commonly used for accurate and reproducible quantification of protein analytes in complex biological mixtures. Strictly hypothesis-driven, SRM assays quantify each targeted protein by collecting measurements on its peptide fragment ions, called transitions. To achieve sensitive and accurate quantitative results, experimental design and data analysis must consistently account for the variability of the quantified transitions. This consistency is especially important in large experiments, which increasingly require profiling up to hundreds of proteins over hundreds of samples. Here we describe a robust and automated workflow for the analysis of large quantitative SRM data sets that integrates data processing, statistical protein identification and quantification, and dissemination of the results. The integrated workflow combines three software tools: mProphet for peptide identification via probabilistic scoring; SRMstats for protein significance analysis with linear mixed-effect models; and PASSEL, a public repository for storage, retrieval and query of SRM data. The input requirements for the protocol are files with SRM traces in mzXML format, and a file with a list of transitions in a text tab-separated format. The protocol is especially suited for data with heavy isotope-labeled peptide internal standards. We demonstrate the protocol on a clinical data set in which the abundances of 35 biomarker candidates were profiled in 83 blood plasma samples of subjects with ovarian cancer or benign ovarian tumors. The time frame to realize the protocol is 1-2 weeks, depending on the number of replicates used in the experiment.

SWS: accessing SRS sites contents through Web Services.

PubMed

Romano, Paolo; Marra, Domenico

2008-03-26

Web Services and Workflow Management Systems can support creation and deployment of network systems, able to automate data analysis and retrieval processes in biomedical research. Web Services have been implemented at bioinformatics centres and workflow systems have been proposed for biological data analysis. New databanks are often developed by taking into account these technologies, but many existing databases do not allow a programmatic access. Only a fraction of available databanks can thus be queried through programmatic interfaces. SRS is a well know indexing and search engine for biomedical databanks offering public access to many databanks and analysis tools. Unfortunately, these data are not easily and efficiently accessible through Web Services. We have developed 'SRS by WS' (SWS), a tool that makes information available in SRS sites accessible through Web Services. Information on known sites is maintained in a database, srsdb. SWS consists in a suite of WS that can query both srsdb, for information on sites and databases, and SRS sites. SWS returns results in a text-only format and can be accessed through a WSDL compliant client. SWS enables interoperability between workflow systems and SRS implementations, by also managing access to alternative sites, in order to cope with network and maintenance problems, and selecting the most up-to-date among available systems. Development and implementation of Web Services, allowing to make a programmatic access to an exhaustive set of biomedical databases can significantly improve automation of in-silico analysis. SWS supports this activity by making biological databanks that are managed in public SRS sites available through a programmatic interface.

Automated detection of discourse segment and experimental types from the text of cancer pathway results sections.

PubMed

Burns, Gully A P C; Dasigi, Pradeep; de Waard, Anita; Hovy, Eduard H

2016-01-01

Automated machine-reading biocuration systems typically use sentence-by-sentence information extraction to construct meaning representations for use by curators. This does not directly reflect the typical discourse structure used by scientists to construct an argument from the experimental data available within a article, and is therefore less likely to correspond to representations typically used in biomedical informatics systems (let alone to the mental models that scientists have). In this study, we develop Natural Language Processing methods to locate, extract, and classify the individual passages of text from articles' Results sections that refer to experimental data. In our domain of interest (molecular biology studies of cancer signal transduction pathways), individual articles may contain as many as 30 small-scale individual experiments describing a variety of findings, upon which authors base their overall research conclusions. Our system automatically classifies discourse segments in these texts into seven categories (fact, hypothesis, problem, goal, method, result, implication) with an F-score of 0.68. These segments describe the essential building blocks of scientific discourse to (i) provide context for each experiment, (ii) report experimental details and (iii) explain the data's meaning in context. We evaluate our system on text passages from articles that were curated in molecular biology databases (the Pathway Logic Datum repository, the Molecular Interaction MINT and INTACT databases) linking individual experiments in articles to the type of assay used (coprecipitation, phosphorylation, translocation etc.). We use supervised machine learning techniques on text passages containing unambiguous references to experiments to obtain baseline F1 scores of 0.59 for MINT, 0.71 for INTACT and 0.63 for Pathway Logic. Although preliminary, these results support the notion that targeting information extraction methods to experimental results could provide accurate, automated methods for biocuration. We also suggest the need for finer-grained curation of experimental methods used when constructing molecular biology databases. © The Author(s) 2016. Published by Oxford University Press.

Introducing Explorer of Taxon Concepts with a case study on spider measurement matrix building.

PubMed

Cui, Hong; Xu, Dongfang; Chong, Steven S; Ramirez, Martin; Rodenhausen, Thomas; Macklin, James A; Ludäscher, Bertram; Morris, Robert A; Soto, Eduardo M; Koch, Nicolás Mongiardino

2016-11-17

Taxonomic descriptions are traditionally composed in natural language and published in a format that cannot be directly used by computers. The Exploring Taxon Concepts (ETC) project has been developing a set of web-based software tools that convert morphological descriptions published in telegraphic style to character data that can be reused and repurposed. This paper introduces the first semi-automated pipeline, to our knowledge, that converts morphological descriptions into taxon-character matrices to support systematics and evolutionary biology research. We then demonstrate and evaluate the use of the ETC Input Creation - Text Capture - Matrix Generation pipeline to generate body part measurement matrices from a set of 188 spider morphological descriptions and report the findings. From the given set of spider taxonomic publications, two versions of input (original and normalized) were generated and used by the ETC Text Capture and ETC Matrix Generation tools. The tools produced two corresponding spider body part measurement matrices, and the matrix from the normalized input was found to be much more similar to a gold standard matrix hand-curated by the scientist co-authors. Special conventions utilized in the original descriptions (e.g., the omission of measurement units) were attributed to the lower performance of using the original input. The results show that simple normalization of the description text greatly increased the quality of the machine-generated matrix and reduced edit effort. The machine-generated matrix also helped identify issues in the gold standard matrix. ETC Text Capture and ETC Matrix Generation are low-barrier and effective tools for extracting measurement values from spider taxonomic descriptions and are more effective when the descriptions are self-contained. Special conventions that make the description text less self-contained challenge automated extraction of data from biodiversity descriptions and hinder the automated reuse of the published knowledge. The tools will be updated to support new requirements revealed in this case study.

Automated spectral and timing analysis of AGNs

NASA Astrophysics Data System (ADS)

Munz, F.; Karas, V.; Guainazzi, M.

2006-12-01

% We have developed an autonomous script that helps the user to automate the XMM-Newton data analysis for the purposes of extensive statistical investigations. We test this approach by examining X-ray spectra of bright AGNs pre-selected from the public database. The event lists extracted in this process were studied further by constructing their energy-resolved Fourier power-spectrum density. This analysis combines energy distributions, light-curves, and their power-spectra and it proves useful to assess the variability patterns present is the data. As another example, an automated search was based on the XSPEC package to reveal the emission features in 2-8 keV range.

Automated Forensic Animal Family Identification by Nested PCR and Melt Curve Analysis on an Off-the-Shelf Thermocycler Augmented with a Centrifugal Microfluidic Disk Segment.

PubMed

Keller, Mark; Naue, Jana; Zengerle, Roland; von Stetten, Felix; Schmidt, Ulrike

2015-01-01

Nested PCR remains a labor-intensive and error-prone biomolecular analysis. Laboratory workflow automation by precise control of minute liquid volumes in centrifugal microfluidic Lab-on-a-Chip systems holds great potential for such applications. However, the majority of these systems require costly custom-made processing devices. Our idea is to augment a standard laboratory device, here a centrifugal real-time PCR thermocycler, with inbuilt liquid handling capabilities for automation. We have developed a microfluidic disk segment enabling an automated nested real-time PCR assay for identification of common European animal groups adapted to forensic standards. For the first time we utilize a novel combination of fluidic elements, including pre-storage of reagents, to automate the assay at constant rotational frequency of an off-the-shelf thermocycler. It provides a universal duplex pre-amplification of short fragments of the mitochondrial 12S rRNA and cytochrome b genes, animal-group-specific main-amplifications, and melting curve analysis for differentiation. The system was characterized with respect to assay sensitivity, specificity, risk of cross-contamination, and detection of minor components in mixtures. 92.2% of the performed tests were recognized as fluidically failure-free sample handling and used for evaluation. Altogether, augmentation of the standard real-time thermocycler with a self-contained centrifugal microfluidic disk segment resulted in an accelerated and automated analysis reducing hands-on time, and circumventing the risk of contamination associated with regular nested PCR protocols.

Simultaneous automatic scoring and co-registration of hormone receptors in tumor areas in whole slide images of breast cancer tissue slides.

PubMed

Trahearn, Nicholas; Tsang, Yee Wah; Cree, Ian A; Snead, David; Epstein, David; Rajpoot, Nasir

2017-06-01

Automation of downstream analysis may offer many potential benefits to routine histopathology. One area of interest for automation is in the scoring of multiple immunohistochemical markers to predict the patient's response to targeted therapies. Automated serial slide analysis of this kind requires robust registration to identify common tissue regions across sections. We present an automated method for co-localized scoring of Estrogen Receptor and Progesterone Receptor (ER/PR) in breast cancer core biopsies using whole slide images. Regions of tumor in a series of fifty consecutive breast core biopsies were identified by annotation on H&E whole slide images. Sequentially cut immunohistochemical stained sections were scored manually, before being digitally scanned and then exported into JPEG 2000 format. A two-stage registration process was performed to identify the annotated regions of interest in the immunohistochemistry sections, which were then scored using the Allred system. Overall correlation between manual and automated scoring for ER and PR was 0.944 and 0.883, respectively, with 90% of ER and 80% of PR scores within in one point or less of agreement. This proof of principle study indicates slide registration can be used as a basis for automation of the downstream analysis for clinically relevant biomarkers in the majority of cases. The approach is likely to be improved by implantation of safeguarding analysis steps post registration. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.

Automation of a high risk medication regime algorithm in a home health care population.

PubMed

Olson, Catherine H; Dierich, Mary; Westra, Bonnie L

2014-10-01

Create an automated algorithm for predicting elderly patients' medication-related risks for readmission and validate it by comparing results with a manual analysis of the same patient population. Outcome and Assessment Information Set (OASIS) and medication data were reused from a previous, manual study of 911 patients from 15 Medicare-certified home health care agencies. The medication data was converted into standardized drug codes using APIs managed by the National Library of Medicine (NLM), and then integrated in an automated algorithm that calculates patients' high risk medication regime scores (HRMRs). A comparison of the results between algorithm and manual process was conducted to determine how frequently the HRMR scores were derived which are predictive of readmission. HRMR scores are composed of polypharmacy (number of drugs), Potentially Inappropriate Medications (PIM) (drugs risky to the elderly), and Medication Regimen Complexity Index (MRCI) (complex dose forms, instructions or administration). The algorithm produced polypharmacy, PIM, and MRCI scores that matched with 99%, 87% and 99% of the scores, respectively, from the manual analysis. Imperfect match rates resulted from discrepancies in how drugs were classified and coded by the manual analysis vs. the automated algorithm. HRMR rules lack clarity, resulting in clinical judgments for manual coding that were difficult to replicate in the automated analysis. The high comparison rates for the three measures suggest that an automated clinical tool could use patients' medication records to predict their risks of avoidable readmissions. Copyright © 2014 Elsevier Inc. All rights reserved.

A comparison of two computer-automated semen analysis instruments for the evaluation of sperm motion characteristics in the stallion.

PubMed

Jasko, D J; Lein, D H; Foote, R H

1990-01-01

Two commercially available computer-automate semen analysis instruments (CellSoft Automated Semen Analyzer and HTM-2000 Motion Analyzer) were compared for their ability to report similar results based on the analysis of pre-recorded video tapes of extended, motile stallion semen. The determinations of the percentage of motile cells by these instruments were more similar than the comparisons between subjective estimates and either instrument. However, mean values obtained from the same sample may still differ by as much as 30 percentage units between instruments. Instruments varied with regard to the determinations of mean sperm curvilinear velocity and sperm concentration, but mean sperm linearity determinations were similar between the instruments. We concluded that the determinations of sperm motion characteristics by subjective estimation, CellSoft Automated Semen Analyzer, and HTM-2000 Motility Analyzer are often dissimilar, making direct comparisons of results difficult.

Accuracy and reproducibility of aortic annular measurements obtained from echocardiographic 3D manual and semi-automated software analyses in patients referred for transcatheter aortic valve implantation: implication for prosthesis size selection.

PubMed

Stella, Stefano; Italia, Leonardo; Geremia, Giulia; Rosa, Isabella; Ancona, Francesco; Marini, Claudia; Capogrosso, Cristina; Giglio, Manuela; Montorfano, Matteo; Latib, Azeem; Margonato, Alberto; Colombo, Antonio; Agricola, Eustachio

2018-02-06

A 3D transoesophageal echocardiography (3D-TOE) reconstruction tool has recently been introduced. The system automatically configures a geometric model of the aortic root and performs quantitative analysis of these structures. We compared the measurements of the aortic annulus (AA) obtained by semi-automated 3D-TOE quantitative software and manual analysis vs. multislice computed tomography (MSCT) ones. One hundred and seventy-five patients (mean age 81.3 ± 6.3 years, 77 men) who underwent both MSCT and 3D-TOE for annulus assessment before transcatheter aortic valve implantation were analysed. Hypothetical prosthetic valve sizing was evaluated using the 3D manual, semi-automated measurements using manufacturer-recommended CT-based sizing algorithm as gold standard. Good correlation between 3D-TOE methods vs. MSCT measurements was found, but the semi-automated analysis demonstrated slightly better correlations for AA major diameter (r = 0.89), perimeter (r = 0.89), and area (r = 0.85) (all P < 0.0001) than manual one. Both 3D methods underestimated the MSCT measurements, but semi-automated measurements showed narrower limits of agreement and lesser bias than manual measurements for most of AA parameters. On average, 3D-TOE semi-automated major diameter, area, and perimeter underestimated the respective MSCT measurements by 7.4%, 3.5%, and 4.4%, respectively, whereas minor diameter was overestimated by 0.3%. Moderate agreement for valve sizing for both 3D-TOE techniques was found: Kappa agreement 0.5 for both semi-automated and manual analysis. Interobserver and intraobserver agreements for the AA measurements were excellent for both techniques (intraclass correlation coefficients for all parameters >0.80). The 3D-TOE semi-automated analysis of AA is feasible and reliable and can be used in clinical practice as an alternative to MSCT for AA assessment. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2018. For permissions, please email: journals.permissions@oup.com.

Costs to Automate Demand Response - Taxonomy and Results from Field Studies and Programs

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

Piette, Mary A.; Schetrit, Oren; Kiliccote, Sila

During the past decade, the technology to automate demand response (DR) in buildings and industrial facilities has advanced significantly. Automation allows rapid, repeatable, reliable operation. This study focuses on costs for DR automation in commercial buildings with some discussion on residential buildings and industrial facilities. DR automation technology relies on numerous components, including communication systems, hardware and software gateways, standards-based messaging protocols, controls and integration platforms, and measurement and telemetry systems. This report compares cost data from several DR automation programs and pilot projects, evaluates trends in the cost per unit of DR and kilowatts (kW) available from automated systems,more » and applies a standard naming convention and classification or taxonomy for system elements. Median costs for the 56 installed automated DR systems studied here are about $200/kW. The deviation around this median is large with costs in some cases being an order of magnitude great or less than the median. This wide range is a result of variations in system age, size of load reduction, sophistication, and type of equipment included in cost analysis. The costs to automate fast DR systems for ancillary services are not fully analyzed in this report because additional research is needed to determine the total cost to install, operate, and maintain these systems. However, recent research suggests that they could be developed at costs similar to those of existing hot-summer DR automation systems. This report considers installation and configuration costs and does include the costs of owning and operating DR automation systems. Future analysis of the latter costs should include the costs to the building or facility manager costs as well as utility or third party program manager cost.« less

Computer-Assisted Automated Scoring of Polysomnograms Using the Somnolyzer System.

PubMed

Punjabi, Naresh M; Shifa, Naima; Dorffner, Georg; Patil, Susheel; Pien, Grace; Aurora, Rashmi N

2015-10-01

Manual scoring of polysomnograms is a time-consuming and tedious process. To expedite the scoring of polysomnograms, several computerized algorithms for automated scoring have been developed. The overarching goal of this study was to determine the validity of the Somnolyzer system, an automated system for scoring polysomnograms. The analysis sample comprised of 97 sleep studies. Each polysomnogram was manually scored by certified technologists from four sleep laboratories and concurrently subjected to automated scoring by the Somnolyzer system. Agreement between manual and automated scoring was examined. Sleep staging and scoring of disordered breathing events was conducted using the 2007 American Academy of Sleep Medicine criteria. Clinical sleep laboratories. A high degree of agreement was noted between manual and automated scoring of the apnea-hypopnea index (AHI). The average correlation between the manually scored AHI across the four clinical sites was 0.92 (95% confidence interval: 0.90-0.93). Similarly, the average correlation between the manual and Somnolyzer-scored AHI values was 0.93 (95% confidence interval: 0.91-0.96). Thus, interscorer correlation between the manually scored results was no different than that derived from manual and automated scoring. Substantial concordance in the arousal index, total sleep time, and sleep efficiency between manual and automated scoring was also observed. In contrast, differences were noted between manually and automated scored percentages of sleep stages N1, N2, and N3. Automated analysis of polysomnograms using the Somnolyzer system provides results that are comparable to manual scoring for commonly used metrics in sleep medicine. Although differences exist between manual versus automated scoring for specific sleep stages, the level of agreement between manual and automated scoring is not significantly different than that between any two human scorers. In light of the burden associated with manual scoring, automated scoring platforms provide a viable complement of tools in the diagnostic armamentarium of sleep medicine. © 2015 Associated Professional Sleep Societies, LLC.

MannDB: A microbial annotation database for protein characterization

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

Zhou, C; Lam, M; Smith, J

2006-05-19

MannDB was created to meet a need for rapid, comprehensive automated protein sequence analyses to support selection of proteins suitable as targets for driving the development of reagents for pathogen or protein toxin detection. Because a large number of open-source tools were needed, it was necessary to produce a software system to scale the computations for whole-proteome analysis. Thus, we built a fully automated system for executing software tools and for storage, integration, and display of automated protein sequence analysis and annotation data. MannDB is a relational database that organizes data resulting from fully automated, high-throughput protein-sequence analyses using open-sourcemore » tools. Types of analyses provided include predictions of cleavage, chemical properties, classification, features, functional assignment, post-translational modifications, motifs, antigenicity, and secondary structure. Proteomes (lists of hypothetical and known proteins) are downloaded and parsed from Genbank and then inserted into MannDB, and annotations from SwissProt are downloaded when identifiers are found in the Genbank entry or when identical sequences are identified. Currently 36 open-source tools are run against MannDB protein sequences either on local systems or by means of batch submission to external servers. In addition, BLAST against protein entries in MvirDB, our database of microbial virulence factors, is performed. A web client browser enables viewing of computational results and downloaded annotations, and a query tool enables structured and free-text search capabilities. When available, links to external databases, including MvirDB, are provided. MannDB contains whole-proteome analyses for at least one representative organism from each category of biological threat organism listed by APHIS, CDC, HHS, NIAID, USDA, USFDA, and WHO. MannDB comprises a large number of genomes and comprehensive protein sequence analyses representing organisms listed as high-priority agents on the websites of several governmental organizations concerned with bio-terrorism. MannDB provides the user with a BLAST interface for comparison of native and non-native sequences and a query tool for conveniently selecting proteins of interest. In addition, the user has access to a web-based browser that compiles comprehensive and extensive reports.« less

Systems Operations Studies for Automated Guideway Transit Systems : Quantitative Analysis of Alternative AGT Operational Control Strategies

DOT National Transportation Integrated Search

1981-10-01

The objectives of the Systems Operation Studies (SOS) for automated guideway transit (AGT) systems are to develop models for the analysis of system operations, to evaluate performance and cost, and to establish guidelines for the design and operation...

Automated Analysis of Child Phonetic Production Using Naturalistic Recordings

ERIC Educational Resources Information Center

Xu, Dongxin; Richards, Jeffrey A.; Gilkerson, Jill

2014-01-01

Purpose: Conventional resource-intensive methods for child phonetic development studies are often impractical for sampling and analyzing child vocalizations in sufficient quantity. The purpose of this study was to provide new information on early language development by an automated analysis of child phonetic production using naturalistic…

Automated pattern analysis: A newsilent partner in insect acoustic detection studies

USDA-ARS?s Scientific Manuscript database

This seminar reviews methods that have been developed for automated analysis of field-collected sounds used to estimate pest populations and guide insect pest management decisions. Several examples are presented of successful usage of acoustic technology to map insect distributions in field environ...

Multichannel Mars Organic Analyzer (McMOA): Microfluidic Networks for the Automated In Situ Microchip Electrophoretic Analysis of Organic Biomarkers on Mars

NASA Astrophysics Data System (ADS)

Chiesl, T. N.; Benhabib, M.; Stockton, A. M.; Mathies, R. A.

2010-04-01

We present the Multichannel Mars Organic Analyzer (McMOA) for the analysis of Amino Acids, PAHs, and Oxidized Carbon. Microfluidic architecures integrating automated metering, mixing, on chip reactions, and serial dilutions are also discussed.

Assessing Unmet Information Needs of Breast Cancer Survivors: Exploratory Study of Online Health Forums Using Text Classification and Retrieval.

PubMed

McRoy, Susan; Rastegar-Mojarad, Majid; Wang, Yanshan; Ruddy, Kathryn J; Haddad, Tufia C; Liu, Hongfang

2018-05-15

Patient education materials given to breast cancer survivors may not be a good fit for their information needs. Needs may change over time, be forgotten, or be misreported, for a variety of reasons. An automated content analysis of survivors' postings to online health forums can identify expressed information needs over a span of time and be repeated regularly at low cost. Identifying these unmet needs can guide improvements to existing education materials and the creation of new resources. The primary goals of this project are to assess the unmet information needs of breast cancer survivors from their own perspectives and to identify gaps between information needs and current education materials. This approach employs computational methods for content modeling and supervised text classification to data from online health forums to identify explicit and implicit requests for health-related information. Potential gaps between needs and education materials are identified using techniques from information retrieval. We provide a new taxonomy for the classification of sentences in online health forum data. 260 postings from two online health forums were selected, yielding 4179 sentences for coding. After annotation of data and training alternative one-versus-others classifiers, a random forest-based approach achieved F1 scores from 66% (Other, dataset2) to 90% (Medical, dataset1) on the primary information types. 136 expressions of need were used to generate queries to indexed education materials. Upon examination of the best two pages retrieved for each query, 12% (17/136) of queries were found to have relevant content by all coders, and 33% (45/136) were judged to have relevant content by at least one. Text from online health forums can be analyzed effectively using automated methods. Our analysis confirms that breast cancer survivors have many information needs that are not covered by the written documents they typically receive, as our results suggest that at most a third of breast cancer survivors' questions would be addressed by the materials currently provided to them. ©Susan McRoy, Majid Rastegar-Mojarad, Yanshan Wang, Kathryn J. Ruddy, Tufia C. Haddad, Hongfang Liu. Originally published in JMIR Cancer (http://cancer.jmir.org), 15.05.2018.

Text-based Analytics for Biosurveillance

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

Charles, Lauren E.; Smith, William P.; Rounds, Jeremiah

The ability to prevent, mitigate, or control a biological threat depends on how quickly the threat is identified and characterized. Ensuring the timely delivery of data and analytics is an essential aspect of providing adequate situational awareness in the face of a disease outbreak. This chapter outlines an analytic pipeline for supporting an advanced early warning system that can integrate multiple data sources and provide situational awareness of potential and occurring disease situations. The pipeline, includes real-time automated data analysis founded on natural language processing (NLP), semantic concept matching, and machine learning techniques, to enrich content with metadata related tomore » biosurveillance. Online news articles are presented as an example use case for the pipeline, but the processes can be generalized to any textual data. In this chapter, the mechanics of a streaming pipeline are briefly discussed as well as the major steps required to provide targeted situational awareness. The text-based analytic pipeline includes various processing steps as well as identifying article relevance to biosurveillance (e.g., relevance algorithm) and article feature extraction (who, what, where, why, how, and when). The ability to prevent, mitigate, or control a biological threat depends on how quickly the threat is identified and characterized. Ensuring the timely delivery of data and analytics is an essential aspect of providing adequate situational awareness in the face of a disease outbreak. This chapter outlines an analytic pipeline for supporting an advanced early warning system that can integrate multiple data sources and provide situational awareness of potential and occurring disease situations. The pipeline, includes real-time automated data analysis founded on natural language processing (NLP), semantic concept matching, and machine learning techniques, to enrich content with metadata related to biosurveillance. Online news articles are presented as an example use case for the pipeline, but the processes can be generalized to any textual data. In this chapter, the mechanics of a streaming pipeline are briefly discussed as well as the major steps required to provide targeted situational awareness. The text-based analytic pipeline includes various processing steps as well as identifying article relevance to biosurveillance (e.g., relevance algorithm) and article feature extraction (who, what, where, why, how, and when).« less

Wnt pathway curation using automated natural language processing: combining statistical methods with partial and full parse for knowledge extraction.

PubMed

Santos, Carlos; Eggle, Daniela; States, David J

2005-04-15

Wnt signaling is a very active area of research with highly relevant publications appearing at a rate of more than one per day. Building and maintaining databases describing signal transduction networks is a time-consuming and demanding task that requires careful literature analysis and extensive domain-specific knowledge. For instance, more than 50 factors involved in Wnt signal transduction have been identified as of late 2003. In this work we describe a natural language processing (NLP) system that is able to identify references to biological interaction networks in free text and automatically assembles a protein association and interaction map. A 'gold standard' set of names and assertions was derived by manual scanning of the Wnt genes website (http://www.stanford.edu/~rnusse/wntwindow.html) including 53 interactions involved in Wnt signaling. This system was used to analyze a corpus of peer-reviewed articles related to Wnt signaling including 3369 Pubmed and 1230 full text papers. Names for key Wnt-pathway associated proteins and biological entities are identified using a chi-squared analysis of noun phrases over-represented in the Wnt literature as compared to the general signal transduction literature. Interestingly, we identified several instances where generic terms were used on the website when more specific terms occur in the literature, and one typographic error on the Wnt canonical pathway. Using the named entity list and performing an exhaustive assertion extraction of the corpus, 34 of the 53 interactions in the 'gold standard' Wnt signaling set were successfully identified (64% recall). In addition, the automated extraction found several interactions involving key Wnt-related molecules which were missing or different from those in the canonical diagram, and these were confirmed by manual review of the text. These results suggest that a combination of NLP techniques for information extraction can form a useful first-pass tool for assisting human annotation and maintenance of signal pathway databases. The pipeline software components are freely available on request to the authors. dstates@umich.edu http://stateslab.bioinformatics.med.umich.edu/software.html.

Assessing Unmet Information Needs of Breast Cancer Survivors: Exploratory Study of Online Health Forums Using Text Classification and Retrieval

PubMed Central

Rastegar-Mojarad, Majid; Wang, Yanshan; Ruddy, Kathryn J; Haddad, Tufia C; Liu, Hongfang

2018-01-01

Background Patient education materials given to breast cancer survivors may not be a good fit for their information needs. Needs may change over time, be forgotten, or be misreported, for a variety of reasons. An automated content analysis of survivors' postings to online health forums can identify expressed information needs over a span of time and be repeated regularly at low cost. Identifying these unmet needs can guide improvements to existing education materials and the creation of new resources. Objective The primary goals of this project are to assess the unmet information needs of breast cancer survivors from their own perspectives and to identify gaps between information needs and current education materials. Methods This approach employs computational methods for content modeling and supervised text classification to data from online health forums to identify explicit and implicit requests for health-related information. Potential gaps between needs and education materials are identified using techniques from information retrieval. Results We provide a new taxonomy for the classification of sentences in online health forum data. 260 postings from two online health forums were selected, yielding 4179 sentences for coding. After annotation of data and training alternative one-versus-others classifiers, a random forest-based approach achieved F1 scores from 66% (Other, dataset2) to 90% (Medical, dataset1) on the primary information types. 136 expressions of need were used to generate queries to indexed education materials. Upon examination of the best two pages retrieved for each query, 12% (17/136) of queries were found to have relevant content by all coders, and 33% (45/136) were judged to have relevant content by at least one. Conclusions Text from online health forums can be analyzed effectively using automated methods. Our analysis confirms that breast cancer survivors have many information needs that are not covered by the written documents they typically receive, as our results suggest that at most a third of breast cancer survivors’ questions would be addressed by the materials currently provided to them. PMID:29764801

Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR).

PubMed

Beller, Elaine; Clark, Justin; Tsafnat, Guy; Adams, Clive; Diehl, Heinz; Lund, Hans; Ouzzani, Mourad; Thayer, Kristina; Thomas, James; Turner, Tari; Xia, Jun; Robinson, Karen; Glasziou, Paul

2018-05-19

Systematic reviews (SR) are vital to health care, but have become complicated and time-consuming, due to the rapid expansion of evidence to be synthesised. Fortunately, many tasks of systematic reviews have the potential to be automated or may be assisted by automation. Recent advances in natural language processing, text mining and machine learning have produced new algorithms that can accurately mimic human endeavour in systematic review activity, faster and more cheaply. Automation tools need to be able to work together, to exchange data and results. Therefore, we initiated the International Collaboration for the Automation of Systematic Reviews (ICASR), to successfully put all the parts of automation of systematic review production together. The first meeting was held in Vienna in October 2015. We established a set of principles to enable tools to be developed and integrated into toolkits.This paper sets out the principles devised at that meeting, which cover the need for improvement in efficiency of SR tasks, automation across the spectrum of SR tasks, continuous improvement, adherence to high quality standards, flexibility of use and combining components, the need for a collaboration and varied skills, the desire for open source, shared code and evaluation, and a requirement for replicability through rigorous and open evaluation.Automation has a great potential to improve the speed of systematic reviews. Considerable work is already being done on many of the steps involved in a review. The 'Vienna Principles' set out in this paper aim to guide a more coordinated effort which will allow the integration of work by separate teams and build on the experience, code and evaluations done by the many teams working across the globe.

Innovative strategy for effective critical laboratory result management: end-to-end process using automation and manual call centre.

PubMed

Ti, Lian Kah; Ang, Sophia Bee Leng; Saw, Sharon; Sethi, Sunil Kumar; Yip, James W L

2012-08-01

Timely reporting and acknowledgement are crucial steps in critical laboratory results (CLR) management. The authors previously showed that an automated pathway incorporating short messaging system (SMS) texts, auto-escalation, and manual telephone back-up improved the rate and speed of physician acknowledgement compared with manual telephone calling alone. This study investigated if it also improved the rate and speed of physician intervention to CLR and whether utilising the manual back-up affected intervention rates. Data from seven audits between November 2007 and January 2011 were analysed. These audits were carried out to assess the robustness of CLR reporting process in the authors' institution. Comparisons were made in the rate and speed of acknowledgement and intervention between the audits performed before and after automation. Using the automation audits, the authors compared intervention data between communication with SMS only and when manual intervention was required. 1680 CLR were reported during the audit periods. Automation improved the rate (100% vs 84.2%; p<0.001) and speed (median 12 min vs 23 min; p<0.001) of CLR acknowledgement. It also improved the rate (93.7% vs 84.0%, p<0.001) and speed (median 21 min vs 109 min; p<0.001) of CLR intervention. From the automation audits, the use of SMS only did not improve physician intervention rates. The automated communication pathway improved physician intervention rate and time in tandem with improved acknowledgement rate and time when compared with manual telephone calling. The use of manual intervention to augment automation did not adversely affect physician intervention rate, implying that an end-to-end pathway was more important than automation alone.

Poor health as a potential risk factor for job loss due to automation: the case of Norway.

PubMed

Hessel, Philipp; Christiansen, Solveig; Skirbekk, Vegard

2018-03-01

This study aimed to quantify the extent to which health characteristics of workers are related to the potential risk of experiencing job displacement due to automation. Linking the 2015 Norwegian Statistics on Income and Living Conditions survey (n=6393) with predicted probabilities of automation by occupation, we used Kruskal-Wallis tests and multivariate generalised linear models to assess the association between long-standing illnesses and risk of job automation. Individuals with long-standing illnesses face substantially greater risks of losing their job due to automation. Whereas the average risk of job automation is 57% for men and 49% for women with long-standing illnesses, the risk is only 50% for men and 44% for women with limitations (p<0.001). Controlling for age, having a long-standing illness significantly increases the relative risk of facing job automation among men (risk ratio (RR) 1.13, 95% CI 1.09 to 1.19), as well as women (RR 1.11, 95% CI 1.05 to 1.17). While, among men, the association between long-standing illness and risk of job automation remains significant when controlling for education and income, it becomes insignificant among women. Individuals with poor health are likely to carry the highest burden of technological change in terms of worsening employment prospects because of working in occupations disproportionally more likely to be automated. Although the extent of technology-related job displacement will depend on several factors, given the far-reaching negative consequences of job loss on health and well-being, this process represents a significant challenge for public health and social equity. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Standardizing Flow Cytometry Immunophenotyping Analysis from the Human ImmunoPhenotyping Consortium

PubMed Central

Finak, Greg; Langweiler, Marc; Jaimes, Maria; Malek, Mehrnoush; Taghiyar, Jafar; Korin, Yael; Raddassi, Khadir; Devine, Lesley; Obermoser, Gerlinde; Pekalski, Marcin L.; Pontikos, Nikolas; Diaz, Alain; Heck, Susanne; Villanova, Federica; Terrazzini, Nadia; Kern, Florian; Qian, Yu; Stanton, Rick; Wang, Kui; Brandes, Aaron; Ramey, John; Aghaeepour, Nima; Mosmann, Tim; Scheuermann, Richard H.; Reed, Elaine; Palucka, Karolina; Pascual, Virginia; Blomberg, Bonnie B.; Nestle, Frank; Nussenblatt, Robert B.; Brinkman, Ryan Remy; Gottardo, Raphael; Maecker, Holden; McCoy, J Philip

2016-01-01

Standardization of immunophenotyping requires careful attention to reagents, sample handling, instrument setup, and data analysis, and is essential for successful cross-study and cross-center comparison of data. Experts developed five standardized, eight-color panels for identification of major immune cell subsets in peripheral blood. These were produced as pre-configured, lyophilized, reagents in 96-well plates. We present the results of a coordinated analysis of samples across nine laboratories using these panels with standardized operating procedures (SOPs). Manual gating was performed by each site and by a central site. Automated gating algorithms were developed and tested by the FlowCAP consortium. Centralized manual gating can reduce cross-center variability, and we sought to determine whether automated methods could streamline and standardize the analysis. Within-site variability was low in all experiments, but cross-site variability was lower when central analysis was performed in comparison with site-specific analysis. It was also lower for clearly defined cell subsets than those based on dim markers and for rare populations. Automated gating was able to match the performance of central manual analysis for all tested panels, exhibiting little to no bias and comparable variability. Standardized staining, data collection, and automated gating can increase power, reduce variability, and streamline analysis for immunophenotyping. PMID:26861911

Automated Detection and Analysis of Interplanetary Shocks with Real-Time Application

NASA Astrophysics Data System (ADS)

Vorotnikov, V.; Smith, C. W.; Hu, Q.; Szabo, A.; Skoug, R. M.; Cohen, C. M.

2006-12-01

The ACE real-time data stream provides web-based now-casting capabilities for solar wind conditions upstream of Earth. Our goal is to provide an automated code that finds and analyzes interplanetary shocks as they occur for possible real-time application to space weather nowcasting. Shock analysis algorithms based on the Rankine-Hugoniot jump conditions exist and are in wide-spread use today for the interactive analysis of interplanetary shocks yielding parameters such as shock speed and propagation direction and shock strength in the form of compression ratios. Although these codes can be automated in a reasonable manner to yield solutions not far from those obtained by user-directed interactive analysis, event detection presents an added obstacle and the first step in a fully automated analysis. We present a fully automated Rankine-Hugoniot analysis code that can scan the ACE science data, find shock candidates, analyze the events, obtain solutions in good agreement with those derived from interactive applications, and dismiss false positive shock candidates on the basis of the conservation equations. The intent is to make this code available to NOAA for use in real-time space weather applications. The code has the added advantage of being able to scan spacecraft data sets to provide shock solutions for use outside real-time applications and can easily be applied to science-quality data sets from other missions. Use of the code for this purpose will also be explored.

Regional environmental analysis and management: New techniques for current problems

NASA Technical Reports Server (NTRS)

Honea, R. B.; Paludan, C. T. N.

1974-01-01

Advances in data acquisition and processing procedures for regional environmental analysis are discussed. Automated and semi-automated techniques employing Earth Resources Technology Satellite data and conventional data sources are presented. Experiences are summarized. The ERTS computer compatible tapes provide a very complete and flexible record of earth resources data and represent a viable medium to enhance regional environmental analysis research.

Acceptability, Language, and Structure of Text Message-Based Behavioral Interventions for High-Risk Adolescent Females: A Qualitative Study

PubMed Central

Ranney, Megan L.; Choo, Esther K.; Cunningham, Rebecca M.; Spirito, Anthony; Thorsen, Margaret; Mello, Michael J.; Morrow, Kathleen

2014-01-01

Purpose To elucidate key elements surrounding acceptability/feasibility, language, and structure of a text message-based preventive intervention for high-risk adolescent females. Methods We recruited high-risk 13- to 17-year-old females screening positive for past-year peer violence and depressive symptoms, during emergency department visits for any chief complaint. Participants completed semistructured interviews exploring preferences around text message preventive interventions. Interviews were conducted by trained interviewers, audio-recorded, and transcribed verbatim. A coding structure was iteratively developed using thematic and content analysis. Each transcript was double coded. NVivo 10 was used to facilitate analysis. Results Saturation was reached after 20 interviews (mean age 15.4; 55% white; 40% Hispanic; 85% with cell phone access). (1) Acceptability/feasibility themes: A text-message intervention was felt to support and enhance existing coping strategies. Participants had a few concerns about privacy and cost. Peer endorsement may increase uptake. (2) Language themes: Messages should be simple and positive. Tone should be conversational but not slang filled. (3) Structural themes: Messages may be automated but must be individually tailored on a daily basis. Both predetermined (automatic) and as-needed messages are requested. Dose and timing of content should be varied according to participants’ needs. Multimedia may be helpful but is not necessary. Conclusions High-risk adolescent females seeking emergency department care are enthusiastic about a text message-based preventive intervention. Incorporating thematic results on language and structure can inform development of future text messaging interventions for adolescent girls. Concerns about cost and privacy may be able to be addressed through the process of recruitment and introduction to the intervention. PMID:24559973

Team performance in networked supervisory control of unmanned air vehicles: effects of automation, working memory, and communication content.

PubMed

McKendrick, Ryan; Shaw, Tyler; de Visser, Ewart; Saqer, Haneen; Kidwell, Brian; Parasuraman, Raja

2014-05-01

Assess team performance within a net-worked supervisory control setting while manipulating automated decision aids and monitoring team communication and working memory ability. Networked systems such as multi-unmanned air vehicle (UAV) supervision have complex properties that make prediction of human-system performance difficult. Automated decision aid can provide valuable information to operators, individual abilities can limit or facilitate team performance, and team communication patterns can alter how effectively individuals work together. We hypothesized that reliable automation, higher working memory capacity, and increased communication rates of task-relevant information would offset performance decrements attributed to high task load. Two-person teams performed a simulated air defense task with two levels of task load and three levels of automated aid reliability. Teams communicated and received decision aid messages via chat window text messages. Task Load x Automation effects were significant across all performance measures. Reliable automation limited the decline in team performance with increasing task load. Average team spatial working memory was a stronger predictor than other measures of team working memory. Frequency of team rapport and enemy location communications positively related to team performance, and word count was negatively related to team performance. Reliable decision aiding mitigated team performance decline during increased task load during multi-UAV supervisory control. Team spatial working memory, communication of spatial information, and team rapport predicted team success. An automated decision aid can improve team performance under high task load. Assessment of spatial working memory and the communication of task-relevant information can help in operator and team selection in supervisory control systems.

Automated classification of bone marrow cells in microscopic images for diagnosis of leukemia: a comparison of two classification schemes with respect to the segmentation quality

NASA Astrophysics Data System (ADS)

Krappe, Sebastian; Benz, Michaela; Wittenberg, Thomas; Haferlach, Torsten; Münzenmayer, Christian

2015-03-01

The morphological analysis of bone marrow smears is fundamental for the diagnosis of leukemia. Currently, the counting and classification of the different types of bone marrow cells is done manually with the use of bright field microscope. This is a time consuming, partly subjective and tedious process. Furthermore, repeated examinations of a slide yield intra- and inter-observer variances. For this reason an automation of morphological bone marrow analysis is pursued. This analysis comprises several steps: image acquisition and smear detection, cell localization and segmentation, feature extraction and cell classification. The automated classification of bone marrow cells is depending on the automated cell segmentation and the choice of adequate features extracted from different parts of the cell. In this work we focus on the evaluation of support vector machines (SVMs) and random forests (RFs) for the differentiation of bone marrow cells in 16 different classes, including immature and abnormal cell classes. Data sets of different segmentation quality are used to test the two approaches. Automated solutions for the morphological analysis for bone marrow smears could use such a classifier to pre-classify bone marrow cells and thereby shortening the examination duration.

ARAM: an automated image analysis software to determine rosetting parameters and parasitaemia in Plasmodium samples.

PubMed

Kudella, Patrick Wolfgang; Moll, Kirsten; Wahlgren, Mats; Wixforth, Achim; Westerhausen, Christoph

2016-04-18

Rosetting is associated with severe malaria and a primary cause of death in Plasmodium falciparum infections. Detailed understanding of this adhesive phenomenon may enable the development of new therapies interfering with rosette formation. For this, it is crucial to determine parameters such as rosetting and parasitaemia of laboratory strains or patient isolates, a bottleneck in malaria research due to the time consuming and error prone manual analysis of specimens. Here, the automated, free, stand-alone analysis software automated rosetting analyzer for micrographs (ARAM) to determine rosetting rate, rosette size distribution as well as parasitaemia with a convenient graphical user interface is presented. Automated rosetting analyzer for micrographs is an executable with two operation modes for automated identification of objects on images. The default mode detects red blood cells and fluorescently labelled parasitized red blood cells by combining an intensity-gradient with a threshold filter. The second mode determines object location and size distribution from a single contrast method. The obtained results are compared with standardized manual analysis. Automated rosetting analyzer for micrographs calculates statistical confidence probabilities for rosetting rate and parasitaemia. Automated rosetting analyzer for micrographs analyses 25 cell objects per second reliably delivering identical results compared to manual analysis. For the first time rosette size distribution is determined in a precise and quantitative manner employing ARAM in combination with established inhibition tests. Additionally ARAM measures the essential observables parasitaemia, rosetting rate and size as well as location of all detected objects and provides confidence intervals for the determined observables. No other existing software solution offers this range of function. The second, non-malaria specific, analysis mode of ARAM offers the functionality to detect arbitrary objects. Automated rosetting analyzer for micrographs has the capability to push malaria research to a more quantitative and statistically significant level with increased reliability due to operator independence. As an installation file for Windows © 7, 8.1 and 10 is available for free, ARAM offers a novel open and easy-to-use platform for the malaria community to elucidate resetting. © 7, 8.1 and 10 is available for free, ARAM offers a novel open and easy-to-use platform for the malaria community to elucidate rosetting.

Attitudes on Technological, Social, and Behavioral Economic Strategies to Reduce Cellphone Use While Driving in Teens.

PubMed

Delgado, M Kit; McDonald, Catherine C; Winston, Flaura K; Halpern, Scott D; Buttenheim, Alison M; Setubal, Claudia; Huang, Yanlan; Saulsgiver, Kathryn A; Lee, Yi-Ching

2018-04-13

The majority of U.S. teens admit to handheld cellphone use while driving, an increasingly common cause of crashes. Attitudes towards novel cellphone applications and settings that block use while driving are poorly understood, potentially limiting uptake. We examined teens' willingness to reduce cellphone use while driving and perceptions of potential strategies to limit this behavior. Teen drivers (n = 153) aged 16-17 who owned smartphones and admitted to texting while driving completed an online survey. Survey instruments measured willingness to give up cellphone use and perceptions of technological and behavioral economic strategies to reduce cellphone use while driving. We used Chi-square tests to test the hypothesis that willingness to give up certain types of cellphone use while driving and the perceptions of strategies to reduce cellphone use while driving would differ by self-reported frequency of texting while driving in the past 30 days (low [1-5 days] vs. high [6 or more days]. Most teens were willing or somewhat willing to give up reading texts (90%), sending texts (95%), and social media (99%) while driving. However they were not willing to give up navigation (59%) and music applications (43%). Those who engaged in high-frequency texting while driving were more likely to say they were not willing to give up navigation applications (73% vs. 44%, P <0.001), music applications (54% vs. 32%, P <0.001), and reading texts (15% vs. 4%) (P = 0.029). Overall, the following strategies where rated as likely to be "very effective" for reducing texting while driving: gain-framed financial incentives (75%), loss-framed financial incentives (63%), group-based financial incentives (58%), insurance discounts (53%), automatic phone locking while driving (54%), email notifications to parents (47%), automated responses to incoming texts (42%), peer concern (18%), and parental concern (15%). Those who engaged in high-frequency texting while driving were less likely to say that following strategies would be very effective: automated responses to incoming texts (33% vs. 53%, P = 0.016), peer concern (9% vs. 29%, P = 0.002), and parental concern (9% vs. 22%, P = 0.025). The strongest perceived benefit of cellphone blocking apps was decreasing distraction (86%). The predominant reason for not wanting to use this technology was not wanting parents to monitor their behavior (60%). Promising strategies for increasing acceptance of cellphone blocking technology among teen drivers include automated screen locking and permitting hands-free navigation and music combined with behavioral economic incentives to sustain engagement.

Automating Energy Bandgap Measurements in Semiconductors Using LabVIEW

ERIC Educational Resources Information Center

Garg, Amit; Sharma, Reena; Dhingra, Vishal

2010-01-01

In this paper, we report the development of an automated system for energy bandgap and resistivity measurement of a semiconductor sample using Four-Probe method for use in the undergraduate laboratory of Physics and Electronics students. The automated data acquisition and analysis system has been developed using National Instruments USB-6008 DAQ…

AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT (AGWA): A GIS-BASED HYRDOLOGIC MODELING TOOL FOR WATERSHED ASSESSMENT AND ANALYSIS

EPA Science Inventory

The Automated Geospatial Watershed Assessment tool (AGWA) is a GIS interface jointly

developed by the USDA Agricultural Research Service, the U.S. Environmental Protection

Agency, the University of Arizona, and the University of Wyoming to automate the

parame...

Performance modeling of automated manufacturing systems

NASA Astrophysics Data System (ADS)

Viswanadham, N.; Narahari, Y.

A unified and systematic treatment is presented of modeling methodologies and analysis techniques for performance evaluation of automated manufacturing systems. The book is the first treatment of the mathematical modeling of manufacturing systems. Automated manufacturing systems are surveyed and three principal analytical modeling paradigms are discussed: Markov chains, queues and queueing networks, and Petri nets.

Complacency and bias in human use of automation: an attentional integration.

PubMed

Parasuraman, Raja; Manzey, Dietrich H

2010-06-01

Our aim was to review empirical studies of complacency and bias in human interaction with automated and decision support systems and provide an integrated theoretical model for their explanation. Automation-related complacency and automation bias have typically been considered separately and independently. Studies on complacency and automation bias were analyzed with respect to the cognitive processes involved. Automation complacency occurs under conditions of multiple-task load, when manual tasks compete with the automated task for the operator's attention. Automation complacency is found in both naive and expert participants and cannot be overcome with simple practice. Automation bias results in making both omission and commission errors when decision aids are imperfect. Automation bias occurs in both naive and expert participants, cannot be prevented by training or instructions, and can affect decision making in individuals as well as in teams. While automation bias has been conceived of as a special case of decision bias, our analysis suggests that it also depends on attentional processes similar to those involved in automation-related complacency. Complacency and automation bias represent different manifestations of overlapping automation-induced phenomena, with attention playing a central role. An integrated model of complacency and automation bias shows that they result from the dynamic interaction of personal, situational, and automation-related characteristics. The integrated model and attentional synthesis provides a heuristic framework for further research on complacency and automation bias and design options for mitigating such effects in automated and decision support systems.

Automated detection of follow-up appointments using text mining of discharge records.

PubMed

Ruud, Kari L; Johnson, Matthew G; Liesinger, Juliette T; Grafft, Carrie A; Naessens, James M

2010-06-01

To determine whether text mining can accurately detect specific follow-up appointment criteria in free-text hospital discharge records. Cross-sectional study. Mayo Clinic Rochester hospitals. Inpatients discharged from general medicine services in 2006 (n = 6481). Textual hospital dismissal summaries were manually reviewed to determine whether the records contained specific follow-up appointment arrangement elements: date, time and either physician or location for an appointment. The data set was evaluated for the same criteria using SAS Text Miner software. The two assessments were compared to determine the accuracy of text mining for detecting records containing follow-up appointment arrangements. Agreement of text-mined appointment findings with gold standard (manual abstraction) including sensitivity, specificity, positive predictive and negative predictive values (PPV and NPV). About 55.2% (3576) of discharge records contained all criteria for follow-up appointment arrangements according to the manual review, 3.2% (113) of which were missed through text mining. Text mining incorrectly identified 3.7% (107) follow-up appointments that were not considered valid through manual review. Therefore, the text mining analysis concurred with the manual review in 96.6% of the appointment findings. Overall sensitivity and specificity were 96.8 and 96.3%, respectively; and PPV and NPV were 97.0 and 96.1%, respectively. of individual appointment criteria resulted in accuracy rates of 93.5% for date, 97.4% for time, 97.5% for physician and 82.9% for location. Text mining of unstructured hospital dismissal summaries can accurately detect documentation of follow-up appointment arrangement elements, thus saving considerable resources for performance assessment and quality-related research.

New fully automated software for assessment of brachial artery flow- mediated dilation with advantages of continuous measurement.

PubMed

Ercan, Ertuğrul; Kırılmaz, Bahadır; Kahraman, İsmail; Bayram, Vildan; Doğan, Hüseyin

2012-11-01

Flow-mediated dilation (FMD) is used to evaluate endothelial functions. Computer-assisted analysis utilizing edge detection permits continuous measurements along the vessel wall. We have developed a new fully automated software program to allow accurate and reproducible measurement. FMD has been measured and analyzed in 18 coronary artery disease (CAD) patients and 17 controls both by manually and by the software developed (computer supported) methods. The agreement between methods was assessed by Bland-Altman analysis. The mean age, body mass index and cardiovascular risk factors were higher in CAD group. Automated FMD% measurement for the control subjects was 18.3±8.5 and 6.8±6.5 for the CAD group (p=0.0001). The intraobserver and interobserver correlation for automated measurement was high (r=0.974, r=0.981, r=0.937, r=0.918, respectively). Manual FMD% at 60th second was correlated with automated FMD % (r=0.471, p=0.004). The new fully automated software© can be used to precise measurement of FMD with low intra- and interobserver variability than manual assessment.

Advances in Scientific Investigation and Automation.

ERIC Educational Resources Information Center

Abt, Jeffrey; And Others

1987-01-01

Six articles address: (1) the impact of science on the physical examination and treatment of books; (2) equipment for physical examination of books; (3) research using the cyclotron for historical analysis; (4) scientific analysis of paper and ink in early maps; (5) recent advances in automation; and (6) cataloging standards. (MES)

Performance Analysis of GAME: A Generic Automated Marking Environment

ERIC Educational Resources Information Center

Blumenstein, Michael; Green, Steve; Fogelman, Shoshana; Nguyen, Ann; Muthukkumarasamy, Vallipuram

2008-01-01

This paper describes the Generic Automated Marking Environment (GAME) and provides a detailed analysis of its performance in assessing student programming projects and exercises. GAME has been designed to automatically assess programming assignments written in a variety of languages based on the "structure" of the source code and the correctness…

14 CFR 1261.413 - Analysis of costs; automation; prevention of overpayments, delinquencies, or defaults.

Code of Federal Regulations, 2010 CFR

2010-01-01

... of overpayments, delinquencies, or defaults. 1261.413 Section 1261.413 Aeronautics and Space NATIONAL...) § 1261.413 Analysis of costs; automation; prevention of overpayments, delinquencies, or defaults. The... internal controls to identify causes, if any, of overpayments, delinquencies, and defaults, and establish...

"First generation" automated DNA sequencing technology.

PubMed

Slatko, Barton E; Kieleczawa, Jan; Ju, Jingyue; Gardner, Andrew F; Hendrickson, Cynthia L; Ausubel, Frederick M

2011-10-01

Beginning in the 1980s, automation of DNA sequencing has greatly increased throughput, reduced costs, and enabled large projects to be completed more easily. The development of automation technology paralleled the development of other aspects of DNA sequencing: better enzymes and chemistry, separation and imaging technology, sequencing protocols, robotics, and computational advancements (including base-calling algorithms with quality scores, database developments, and sequence analysis programs). Despite the emergence of high-throughput sequencing platforms, automated Sanger sequencing technology remains useful for many applications. This unit provides background and a description of the "First-Generation" automated DNA sequencing technology. It also includes protocols for using the current Applied Biosystems (ABI) automated DNA sequencing machines. © 2011 by John Wiley & Sons, Inc.

Optical Coherence Tomography in the UK Biobank Study - Rapid Automated Analysis of Retinal Thickness for Large Population-Based Studies.

PubMed

Keane, Pearse A; Grossi, Carlota M; Foster, Paul J; Yang, Qi; Reisman, Charles A; Chan, Kinpui; Peto, Tunde; Thomas, Dhanes; Patel, Praveen J

2016-01-01

To describe an approach to the use of optical coherence tomography (OCT) imaging in large, population-based studies, including methods for OCT image acquisition, storage, and the remote, rapid, automated analysis of retinal thickness. In UK Biobank, OCT images were acquired between 2009 and 2010 using a commercially available "spectral domain" OCT device (3D OCT-1000, Topcon). Images were obtained using a raster scan protocol, 6 mm x 6 mm in area, and consisting of 128 B-scans. OCT image sets were stored on UK Biobank servers in a central repository, adjacent to high performance computers. Rapid, automated analysis of retinal thickness was performed using custom image segmentation software developed by the Topcon Advanced Biomedical Imaging Laboratory (TABIL). This software employs dual-scale gradient information to allow for automated segmentation of nine intraretinal boundaries in a rapid fashion. 67,321 participants (134,642 eyes) in UK Biobank underwent OCT imaging of both eyes as part of the ocular module. 134,611 images were successfully processed with 31 images failing segmentation analysis due to corrupted OCT files or withdrawal of subject consent for UKBB study participation. Average time taken to call up an image from the database and complete segmentation analysis was approximately 120 seconds per data set per login, and analysis of the entire dataset was completed in approximately 28 days. We report an approach to the rapid, automated measurement of retinal thickness from nearly 140,000 OCT image sets from the UK Biobank. In the near future, these measurements will be publically available for utilization by researchers around the world, and thus for correlation with the wealth of other data collected in UK Biobank. The automated analysis approaches we describe may be of utility for future large population-based epidemiological studies, clinical trials, and screening programs that employ OCT imaging.

Optical Coherence Tomography in the UK Biobank Study – Rapid Automated Analysis of Retinal Thickness for Large Population-Based Studies

PubMed Central

Grossi, Carlota M.; Foster, Paul J.; Yang, Qi; Reisman, Charles A.; Chan, Kinpui; Peto, Tunde; Thomas, Dhanes; Patel, Praveen J.

2016-01-01

Purpose To describe an approach to the use of optical coherence tomography (OCT) imaging in large, population-based studies, including methods for OCT image acquisition, storage, and the remote, rapid, automated analysis of retinal thickness. Methods In UK Biobank, OCT images were acquired between 2009 and 2010 using a commercially available “spectral domain” OCT device (3D OCT-1000, Topcon). Images were obtained using a raster scan protocol, 6 mm x 6 mm in area, and consisting of 128 B-scans. OCT image sets were stored on UK Biobank servers in a central repository, adjacent to high performance computers. Rapid, automated analysis of retinal thickness was performed using custom image segmentation software developed by the Topcon Advanced Biomedical Imaging Laboratory (TABIL). This software employs dual-scale gradient information to allow for automated segmentation of nine intraretinal boundaries in a rapid fashion. Results 67,321 participants (134,642 eyes) in UK Biobank underwent OCT imaging of both eyes as part of the ocular module. 134,611 images were successfully processed with 31 images failing segmentation analysis due to corrupted OCT files or withdrawal of subject consent for UKBB study participation. Average time taken to call up an image from the database and complete segmentation analysis was approximately 120 seconds per data set per login, and analysis of the entire dataset was completed in approximately 28 days. Conclusions We report an approach to the rapid, automated measurement of retinal thickness from nearly 140,000 OCT image sets from the UK Biobank. In the near future, these measurements will be publically available for utilization by researchers around the world, and thus for correlation with the wealth of other data collected in UK Biobank. The automated analysis approaches we describe may be of utility for future large population-based epidemiological studies, clinical trials, and screening programs that employ OCT imaging. PMID:27716837

Automated quantification of neuronal networks and single-cell calcium dynamics using calcium imaging

PubMed Central

Patel, Tapan P.; Man, Karen; Firestein, Bonnie L.; Meaney, David F.

2017-01-01

Background Recent advances in genetically engineered calcium and membrane potential indicators provide the potential to estimate the activation dynamics of individual neurons within larger, mesoscale networks (100s–1000 +neurons). However, a fully integrated automated workflow for the analysis and visualization of neural microcircuits from high speed fluorescence imaging data is lacking. New method Here we introduce FluoroSNNAP, Fluorescence Single Neuron and Network Analysis Package. FluoroSNNAP is an open-source, interactive software developed in MATLAB for automated quantification of numerous biologically relevant features of both the calcium dynamics of single-cells and network activity patterns. FluoroSNNAP integrates and improves upon existing tools for spike detection, synchronization analysis, and inference of functional connectivity, making it most useful to experimentalists with little or no programming knowledge. Results We apply FluoroSNNAP to characterize the activity patterns of neuronal microcircuits undergoing developmental maturation in vitro. Separately, we highlight the utility of single-cell analysis for phenotyping a mixed population of neurons expressing a human mutant variant of the microtubule associated protein tau and wild-type tau. Comparison with existing method(s) We show the performance of semi-automated cell segmentation using spatiotemporal independent component analysis and significant improvement in detecting calcium transients using a template-based algorithm in comparison to peak-based or wavelet-based detection methods. Our software further enables automated analysis of microcircuits, which is an improvement over existing methods. Conclusions We expect the dissemination of this software will facilitate a comprehensive analysis of neuronal networks, promoting the rapid interrogation of circuits in health and disease. PMID:25629800

Volumetric analysis of pelvic hematomas after blunt trauma using semi-automated seeded region growing segmentation: a method validation study.

PubMed

Dreizin, David; Bodanapally, Uttam K; Neerchal, Nagaraj; Tirada, Nikki; Patlas, Michael; Herskovits, Edward

2016-11-01

Manually segmented traumatic pelvic hematoma volumes are strongly predictive of active bleeding at conventional angiography, but the method is time intensive, limiting its clinical applicability. We compared volumetric analysis using semi-automated region growing segmentation to manual segmentation and diameter-based size estimates in patients with pelvic hematomas after blunt pelvic trauma. A 14-patient cohort was selected in an anonymous randomized fashion from a dataset of patients with pelvic binders at MDCT, collected retrospectively as part of a HIPAA-compliant IRB-approved study from January 2008 to December 2013. To evaluate intermethod differences, one reader (R1) performed three volume measurements using the manual technique and three volume measurements using the semi-automated technique. To evaluate interobserver differences for semi-automated segmentation, a second reader (R2) performed three semi-automated measurements. One-way analysis of variance was used to compare differences in mean volumes. Time effort was also compared. Correlation between the two methods as well as two shorthand appraisals (greatest diameter, and the ABC/2 method for estimating ellipsoid volumes) was assessed with Spearman's rho (r). Intraobserver variability was lower for semi-automated compared to manual segmentation, with standard deviations ranging between ±5-32 mL and ±17-84 mL, respectively (p = 0.0003). There was no significant difference in mean volumes between the two readers' semi-automated measurements (p = 0.83); however, means were lower for the semi-automated compared with the manual technique (manual: mean and SD 309.6 ± 139 mL; R1 semi-auto: 229.6 ± 88.2 mL, p = 0.004; R2 semi-auto: 243.79 ± 99.7 mL, p = 0.021). Despite differences in means, the correlation between the two methods was very strong and highly significant (r = 0.91, p < 0.001). Correlations with diameter-based methods were only moderate and nonsignificant. Mean semi-automated segmentation time effort was 2 min and 6 s and 2 min and 35 s for R1 and R2, respectively, vs. 22 min and 8 s for manual segmentation. Semi-automated pelvic hematoma volumes correlate strongly with manually segmented volumes. Since semi-automated segmentation can be performed reliably and efficiently, volumetric analysis of traumatic pelvic hematomas is potentially valuable at the point-of-care.

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

Anderson, Mathew; Bowen, Brian; Coles, Dwight

The Middleware Automated Deployment Utilities consists the these three components: MAD: Utility designed to automate the deployment of java applications to multiple java application servers. The product contains a front end web utility and backend deployment scripts. MAR: Web front end to maintain and update the components inside database. MWR-Encrypt: Web utility to convert a text string to an encrypted string that is used by the Oracle Weblogic application server. The encryption is done using the built in functions if the Oracle Weblogic product and is mainly used to create an encrypted version of a database password.

Artificial intelligence in cardiology.

PubMed

Bonderman, Diana

2017-12-01

Decision-making is complex in modern medicine and should ideally be based on available data, structured knowledge and proper interpretation in the context of an individual patient. Automated algorithms, also termed artificial intelligence that are able to extract meaningful patterns from data collections and build decisions upon identified patterns may be useful assistants in clinical decision-making processes. In this article, artificial intelligence-based studies in clinical cardiology are reviewed. The text also touches on the ethical issues and speculates on the future roles of automated algorithms versus clinicians in cardiology and medicine in general.

Automated verification of flight software. User's manual

NASA Technical Reports Server (NTRS)

Saib, S. H.

1982-01-01

(Automated Verification of Flight Software), a collection of tools for analyzing source programs written in FORTRAN and AED is documented. The quality and the reliability of flight software are improved by: (1) indented listings of source programs, (2) static analysis to detect inconsistencies in the use of variables and parameters, (3) automated documentation, (4) instrumentation of source code, (5) retesting guidance, (6) analysis of assertions, (7) symbolic execution, (8) generation of verification conditions, and (9) simplification of verification conditions. Use of AVFS in the verification of flight software is described.

Automation system for neutron activation analysis at the reactor IBR-2, Frank Laboratory of Neutron Physics, Joint Institute for Nuclear Research, Dubna, Russia.

PubMed

Pavlov, Sergey S; Dmitriev, Andrey Yu; Frontasyeva, Marina V

The present status of development of software packages and equipment designed for automation of NAA at the reactor IBR-2 of FLNP, JINR, Dubna, RF, is described. The NAA database, construction of sample changers and software for automation of spectra measurement and calculation of concentrations are presented. Automation of QC procedures is integrated in the software developed. Details of the design are shown.

Text Comprehension in Chinese Children: Relative Contribution of Verbal Working Memory, Pseudoword Reading, Rapid Automated Naming, and Onset-Rime Phonological Segmentation

ERIC Educational Resources Information Center

Leong, Che Kan; Tse, Shek Kam; Loh, Ka Yee; Hau, Kit Tai

2008-01-01

The present study examined the role of verbal working memory (memory span, tongue twister), 2-character Chinese pseudoword reading, rapid automatized naming (letters, numbers), and phonological segmentation (deletion of rimes and onsets) in inferential text comprehension in Chinese in 518 Chinese children in Hong Kong in Grades 3 to 5. It was…

Next Generation Satellite Communications: Automated Doppler Shift Compensation of PSK-31 Via Software-Defined Radio

DTIC Science & Technology

2014-05-09

Interfaces Configuration – Wired Network Connections before Editing Move the cursor to the end of the line that ends with “eth0 inet dhcp ” and type...X”. This will delete text one character back from the cursor. Delete the word “ dhcp ”. Once this is done, type “a” to begin inserting text and add

Intelligent content fitting for digital publishing

NASA Astrophysics Data System (ADS)

Lin, Xiaofan

2006-02-01

One recurring problem in Variable Data Printing (VDP) is that the existing contents cannot satisfy the VDP task as-is. So there is a strong need for content fitting technologies to support high-value digital publishing applications, in which text and image are the two major types of contents. This paper presents meta-Autocrop framework for image fitting and TextFlex technology for text fitting. The meta-Autocrop framework supports multiple modes: fixed aspect-ratio mode, advice mode, and verification mode. The TextFlex technology supports non-rectangular text wrapping and paragraph-based line breaking. We also demonstrate how these content fitting technologies are utilized in the overall automated composition and layout system.

Measuring up: Implementing a dental quality measure in the electronic health record context.

PubMed

Bhardwaj, Aarti; Ramoni, Rachel; Kalenderian, Elsbeth; Neumann, Ana; Hebballi, Nutan B; White, Joel M; McClellan, Lyle; Walji, Muhammad F

2016-01-01

Quality improvement requires using quality measures that can be implemented in a valid manner. Using guidelines set forth by the Meaningful Use portion of the Health Information Technology for Economic and Clinical Health Act, the authors assessed the feasibility and performance of an automated electronic Meaningful Use dental clinical quality measure to determine the percentage of children who received fluoride varnish. The authors defined how to implement the automated measure queries in a dental electronic health record. Within records identified through automated query, the authors manually reviewed a subsample to assess the performance of the query. The automated query results revealed that 71.0% of patients had fluoride varnish compared with the manual chart review results that indicated 77.6% of patients had fluoride varnish. The automated quality measure performance results indicated 90.5% sensitivity, 90.8% specificity, 96.9% positive predictive value, and 75.2% negative predictive value. The authors' findings support the feasibility of using automated dental quality measure queries in the context of sufficient structured data. Information noted only in free text rather than in structured data would require using natural language processing approaches to effectively query electronic health records. To participate in self-directed quality improvement, dental clinicians must embrace the accountability era. Commitment to quality will require enhanced documentation to support near-term automated calculation of quality measures. Copyright © 2016 American Dental Association. Published by Elsevier Inc. All rights reserved.

Finding meaning in social media: content-based social network analysis of QuitNet to identify new opportunities for health promotion.

PubMed

Myneni, Sahiti; Cobb, Nathan K; Cohen, Trevor

2013-01-01

Unhealthy behaviors increase individual health risks and are a socioeconomic burden. Harnessing social influence is perceived as fundamental for interventions to influence health-related behaviors. However, the mechanisms through which social influence occurs are poorly understood. Online social networks provide the opportunity to understand these mechanisms as they digitally archive communication between members. In this paper, we present a methodology for content-based social network analysis, combining qualitative coding, automated text analysis, and formal network analysis such that network structure is determined by the content of messages exchanged between members. We apply this approach to characterize the communication between members of QuitNet, an online social network for smoking cessation. Results indicate that the method identifies meaningful theme-based social sub-networks. Modeling social network data using this method can provide us with theme-specific insights such as the identities of opinion leaders and sub-community clusters. Implications for design of targeted social interventions are discussed.

Automating a Detailed Cognitive Task Analysis for Structuring Curriculum

DTIC Science & Technology

1991-08-01

1991-- ] Aleeo/i ISM’-19# l Title: Automating a Detailed Cognitive Task Analysis for Structuring Curriculum Activities: To date we have completed task...The Institute for Management Sciences. Although the particular application of the modified GOMS cognitive task analysis technique under development is...Laboratories 91 9 23 074 Automnating a Detailed Cognitive Task Analysis For Stucuring Curriculum Research Plan Year 1 Task 1.0 Design Task 1.1 Conduct body

Improvement of Binary Analysis Components in Automated Malware Analysis Framework

DTIC Science & Technology

2017-02-21

analyze malicious software (malware) with minimum human interaction. The system autonomously analyze malware samples by analyzing malware binary program...AFRL-AFOSR-JP-TR-2017-0018 Improvement of Binary Analysis Components in Automated Malware Analysis Framework Keiji Takeda KEIO UNIVERSITY Final...currently valid OMB control number . PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ORGANIZATION. 1. REPORT DATE (DD-MM-YYYY)      21-02-2017 2. REPORT

Data-Driven Surface Traversability Analysis for Mars 2020 Landing Site Selection

NASA Technical Reports Server (NTRS)

Ono, Masahiro; Rothrock, Brandon; Almeida, Eduardo; Ansar, Adnan; Otero, Richard; Huertas, Andres; Heverly, Matthew

2015-01-01

The objective of this paper is three-fold: 1) to describe the engineering challenges in the surface mobility of the Mars 2020 Rover mission that are considered in the landing site selection processs, 2) to introduce new automated traversability analysis capabilities, and 3) to present the preliminary analysis results for top candidate landing sites. The analysis capabilities presented in this paper include automated terrain classification, automated rock detection, digital elevation model (DEM) generation, and multi-ROI (region of interest) route planning. These analysis capabilities enable to fully utilize the vast volume of high-resolution orbiter imagery, quantitatively evaluate surface mobility requirements for each candidate site, and reject subjectivity in the comparison between sites in terms of engineering considerations. The analysis results supported the discussion in the Second Landing Site Workshop held in August 2015, which resulted in selecting eight candidate sites that will be considered in the third workshop.

Development of automation software for neutron activation analysis process in Malaysian nuclear agency

NASA Astrophysics Data System (ADS)

Yussup, N.; Rahman, N. A. A.; Ibrahim, M. M.; Mokhtar, M.; Salim, N. A. A.; Soh@Shaari, S. C.; Azman, A.

2017-01-01

Neutron Activation Analysis (NAA) process has been established in Malaysian Nuclear Agency (Nuclear Malaysia) since 1980s. Most of the procedures established especially from sample registration to sample analysis are performed manually. These manual procedures carried out by the NAA laboratory personnel are time consuming and inefficient. Hence, a software to support the system automation is developed to provide an effective method to replace redundant manual data entries and produce faster sample analysis and calculation process. This paper describes the design and development of automation software for NAA process which consists of three sub-programs. The sub-programs are sample registration, hardware control and data acquisition; and sample analysis. The data flow and connection between the sub-programs will be explained. The software is developed by using National Instrument LabView development package.

Understanding reliance on automation: effects of error type, error distribution, age and experience

PubMed Central

Sanchez, Julian; Rogers, Wendy A.; Fisk, Arthur D.; Rovira, Ericka

2015-01-01

An obstacle detection task supported by “imperfect” automation was used with the goal of understanding the effects of automation error types and age on automation reliance. Sixty younger and sixty older adults interacted with a multi-task simulation of an agricultural vehicle (i.e. a virtual harvesting combine). The simulator included an obstacle detection task and a fully manual tracking task. A micro-level analysis provided insight into the way reliance patterns change over time. The results indicated that there are distinct patterns of reliance that develop as a function of error type. A prevalence of automation false alarms led participants to under-rely on the automation during alarm states while over relying on it during non-alarms states. Conversely, a prevalence of automation misses led participants to over-rely on automated alarms and under-rely on the automation during non-alarm states. Older adults adjusted their behavior according to the characteristics of the automation similarly to younger adults, although it took them longer to do so. The results of this study suggest the relationship between automation reliability and reliance depends on the prevalence of specific errors and on the state of the system. Understanding the effects of automation detection criterion settings on human-automation interaction can help designers of automated systems make predictions about human behavior and system performance as a function of the characteristics of the automation. PMID:25642142

Understanding reliance on automation: effects of error type, error distribution, age and experience.

PubMed

Sanchez, Julian; Rogers, Wendy A; Fisk, Arthur D; Rovira, Ericka

2014-03-01

An obstacle detection task supported by "imperfect" automation was used with the goal of understanding the effects of automation error types and age on automation reliance. Sixty younger and sixty older adults interacted with a multi-task simulation of an agricultural vehicle (i.e. a virtual harvesting combine). The simulator included an obstacle detection task and a fully manual tracking task. A micro-level analysis provided insight into the way reliance patterns change over time. The results indicated that there are distinct patterns of reliance that develop as a function of error type. A prevalence of automation false alarms led participants to under-rely on the automation during alarm states while over relying on it during non-alarms states. Conversely, a prevalence of automation misses led participants to over-rely on automated alarms and under-rely on the automation during non-alarm states. Older adults adjusted their behavior according to the characteristics of the automation similarly to younger adults, although it took them longer to do so. The results of this study suggest the relationship between automation reliability and reliance depends on the prevalence of specific errors and on the state of the system. Understanding the effects of automation detection criterion settings on human-automation interaction can help designers of automated systems make predictions about human behavior and system performance as a function of the characteristics of the automation.

Automated quantification of proliferation with automated hot-spot selection in phosphohistone H3/MART1 dual-stained stage I/II melanoma.

PubMed

Nielsen, Patricia Switten; Riber-Hansen, Rikke; Schmidt, Henrik; Steiniche, Torben

2016-04-09

Staging of melanoma includes quantification of a proliferation index, i.e., presumed melanocytic mitoses of H&E stains are counted manually in hot spots. Yet, its reproducibility and prognostic impact increases by immunohistochemical dual staining for phosphohistone H3 (PHH3) and MART1, which also may enable fully automated quantification by image analysis. To ensure manageable workloads and repeatable measurements in modern pathology, the study aimed to present an automated quantification of proliferation with automated hot-spot selection in PHH3/MART1-stained melanomas. Formalin-fixed, paraffin-embedded tissue from 153 consecutive stage I/II melanoma patients was immunohistochemically dual-stained for PHH3 and MART1. Whole slide images were captured, and the number of PHH3/MART1-positive cells was manually and automatically counted in the global tumor area and in a manually and automatically selected hot spot, i.e., a fixed 1-mm(2) square. Bland-Altman plots and hypothesis tests compared manual and automated procedures, and the Cox proportional hazards model established their prognostic impact. The mean difference between manual and automated global counts was 2.9 cells/mm(2) (P = 0.0071) and 0.23 cells per hot spot (P = 0.96) for automated counts in manually and automatically selected hot spots. In 77 % of cases, manual and automated hot spots overlapped. Fully manual hot-spot counts yielded the highest prognostic performance with an adjusted hazard ratio of 5.5 (95 % CI, 1.3-24, P = 0.024) as opposed to 1.3 (95 % CI, 0.61-2.9, P = 0.47) for automated counts with automated hot spots. The automated index and automated hot-spot selection were highly correlated to their manual counterpart, but altogether their prognostic impact was noticeably reduced. Because correct recognition of only one PHH3/MART1-positive cell seems important, extremely high sensitivity and specificity of the algorithm is required for prognostic purposes. Thus, automated analysis may still aid and improve the pathologists' detection of mitoses in melanoma and possibly other malignancies.

Computer-Assisted Automated Scoring of Polysomnograms Using the Somnolyzer System

PubMed Central

Punjabi, Naresh M.; Shifa, Naima; Dorffner, Georg; Patil, Susheel; Pien, Grace; Aurora, Rashmi N.

2015-01-01

Study Objectives: Manual scoring of polysomnograms is a time-consuming and tedious process. To expedite the scoring of polysomnograms, several computerized algorithms for automated scoring have been developed. The overarching goal of this study was to determine the validity of the Somnolyzer system, an automated system for scoring polysomnograms. Design: The analysis sample comprised of 97 sleep studies. Each polysomnogram was manually scored by certified technologists from four sleep laboratories and concurrently subjected to automated scoring by the Somnolyzer system. Agreement between manual and automated scoring was examined. Sleep staging and scoring of disordered breathing events was conducted using the 2007 American Academy of Sleep Medicine criteria. Setting: Clinical sleep laboratories. Measurements and Results: A high degree of agreement was noted between manual and automated scoring of the apnea-hypopnea index (AHI). The average correlation between the manually scored AHI across the four clinical sites was 0.92 (95% confidence interval: 0.90–0.93). Similarly, the average correlation between the manual and Somnolyzer-scored AHI values was 0.93 (95% confidence interval: 0.91–0.96). Thus, interscorer correlation between the manually scored results was no different than that derived from manual and automated scoring. Substantial concordance in the arousal index, total sleep time, and sleep efficiency between manual and automated scoring was also observed. In contrast, differences were noted between manually and automated scored percentages of sleep stages N1, N2, and N3. Conclusion: Automated analysis of polysomnograms using the Somnolyzer system provides results that are comparable to manual scoring for commonly used metrics in sleep medicine. Although differences exist between manual versus automated scoring for specific sleep stages, the level of agreement between manual and automated scoring is not significantly different than that between any two human scorers. In light of the burden associated with manual scoring, automated scoring platforms provide a viable complement of tools in the diagnostic armamentarium of sleep medicine. Citation: Punjabi NM, Shifa N, Dorffner G, Patil S, Pien G, Aurora RN. Computer-assisted automated scoring of polysomnograms using the Somnolyzer system. SLEEP 2015;38(10):1555–1566. PMID:25902809

CloVR-Comparative: automated, cloud-enabled comparative microbial genome sequence analysis pipeline.

PubMed

Agrawal, Sonia; Arze, Cesar; Adkins, Ricky S; Crabtree, Jonathan; Riley, David; Vangala, Mahesh; Galens, Kevin; Fraser, Claire M; Tettelin, Hervé; White, Owen; Angiuoli, Samuel V; Mahurkar, Anup; Fricke, W Florian

2017-04-27

The benefit of increasing genomic sequence data to the scientific community depends on easy-to-use, scalable bioinformatics support. CloVR-Comparative combines commonly used bioinformatics tools into an intuitive, automated, and cloud-enabled analysis pipeline for comparative microbial genomics. CloVR-Comparative runs on annotated complete or draft genome sequences that are uploaded by the user or selected via a taxonomic tree-based user interface and downloaded from NCBI. CloVR-Comparative runs reference-free multiple whole-genome alignments to determine unique, shared and core coding sequences (CDSs) and single nucleotide polymorphisms (SNPs). Output includes short summary reports and detailed text-based results files, graphical visualizations (phylogenetic trees, circular figures), and a database file linked to the Sybil comparative genome browser. Data up- and download, pipeline configuration and monitoring, and access to Sybil are managed through CloVR-Comparative web interface. CloVR-Comparative and Sybil are distributed as part of the CloVR virtual appliance, which runs on local computers or the Amazon EC2 cloud. Representative datasets (e.g. 40 draft and complete Escherichia coli genomes) are processed in <36 h on a local desktop or at a cost of <$20 on EC2. CloVR-Comparative allows anybody with Internet access to run comparative genomics projects, while eliminating the need for on-site computational resources and expertise.

Towards automated processing of clinical Finnish: sublanguage analysis and a rule-based parser.

PubMed

Laippala, Veronika; Ginter, Filip; Pyysalo, Sampo; Salakoski, Tapio

2009-12-01

In this paper, we present steps taken towards more efficient automated processing of clinical Finnish, focusing on daily nursing notes in a Finnish Intensive Care Unit (ICU). First, we analyze ICU Finnish as a sublanguage, identifying its specific features facilitating, for example, the development of a specialized syntactic analyser. The identified features include frequent omission of finite verbs, limitations in allowed syntactic structures, and domain-specific vocabulary. Second, we develop a formal grammar and a parser for ICU Finnish, thus providing better tools for the development of further applications in the clinical domain. The grammar is implemented in the LKB system in a typed feature structure formalism. The lexicon is automatically generated based on the output of the FinTWOL morphological analyzer adapted to the clinical domain. As an additional experiment, we study the effect of using Finnish constraint grammar to reduce the size of the lexicon. The parser construction thus makes efficient use of existing resources for Finnish. The grammar currently covers 76.6% of ICU Finnish sentences, producing highly accurate best-parse analyzes with F-score of 91.1%. We find that building a parser for the highly specialized domain sublanguage is not only feasible, but also surprisingly efficient, given an existing morphological analyzer with broad vocabulary coverage. The resulting parser enables a deeper analysis of the text than was previously possible.

Completely automated modal analysis procedure based on the combination of different OMA methods

NASA Astrophysics Data System (ADS)

Ripamonti, Francesco; Bussini, Alberto; Resta, Ferruccio

2018-03-01

In this work a completely automated output-only Modal Analysis procedure is presented and all its benefits are listed. Based on the merging of different Operational Modal Analysis methods and a statistical approach, the identification process has been improved becoming more robust and giving as results only the real natural frequencies, damping ratios and mode shapes of the system. The effect of the temperature can be taken into account as well, leading to the creation of a better tool for automated Structural Health Monitoring. The algorithm has been developed and tested on a numerical model of a scaled three-story steel building present in the laboratories of Politecnico di Milano.

Integrated Multi-process Microfluidic Systems for Automating Analysis

PubMed Central

Yang, Weichun; Woolley, Adam T.

2010-01-01

Microfluidic technologies have been applied extensively in rapid sample analysis. Some current challenges for standard microfluidic systems are relatively high detection limits, and reduced resolving power and peak capacity compared to conventional approaches. The integration of multiple functions and components onto a single platform can overcome these separation and detection limitations of microfluidics. Multiplexed systems can greatly increase peak capacity in multidimensional separations and can increase sample throughput by analyzing many samples simultaneously. On-chip sample preparation, including labeling, preconcentration, cleanup and amplification, can all serve to speed up and automate processes in integrated microfluidic systems. This paper summarizes advances in integrated multi-process microfluidic systems for automated analysis, their benefits and areas for needed improvement. PMID:20514343

Preliminary clinical evaluation of automated analysis of the sublingual microcirculation in the assessment of patients with septic shock: Comparison of automated versus semi-automated software.

PubMed

Sharawy, Nivin; Mukhtar, Ahmed; Islam, Sufia; Mahrous, Reham; Mohamed, Hassan; Ali, Mohamed; Hakeem, Amr A; Hossny, Osama; Refaa, Amera; Saka, Ahmed; Cerny, Vladimir; Whynot, Sara; George, Ronald B; Lehmann, Christian

2017-01-01

The outcome of patients in septic shock has been shown to be related to changes within the microcirculation. Modern imaging technologies are available to generate high resolution video recordings of the microcirculation in humans. However, evaluation of the microcirculation is not yet implemented in the routine clinical monitoring of critically ill patients. This is mainly due to large amount of time and user interaction required by the current video analysis software. The aim of this study was to validate a newly developed automated method (CCTools®) for microcirculatory analysis of sublingual capillary perfusion in septic patients in comparison to standard semi-automated software (AVA3®). 204 videos from 47 patients were recorded using incident dark field (IDF) imaging. Total vessel density (TVD), proportion of perfused vessels (PPV), perfused vessel density (PVD), microvascular flow index (MFI) and heterogeneity index (HI) were measured using AVA3® and CCTools®. Significant differences between the numeric results obtained by the two different software packages were observed. The values for TVD, PVD and MFI were statistically related though. The automated software technique successes to show septic shock induced microcirculation alterations in near real time. However, we found wide degrees of agreement between AVA3® and CCTools® values due to several technical factors that should be considered in the future studies.

Web-based automation of green building rating index and life cycle cost analysis

NASA Astrophysics Data System (ADS)

Shahzaib Khan, Jam; Zakaria, Rozana; Aminuddin, Eeydzah; IzieAdiana Abidin, Nur; Sahamir, Shaza Rina; Ahmad, Rosli; Nafis Abas, Darul

2018-04-01

Sudden decline in financial markets and economic meltdown has slow down adaptation and lowered interest of investors towards green certified buildings due to their higher initial costs. Similarly, it is essential to fetch investor’s attention towards more development of green buildings through automated tools for the construction projects. Though, historical dearth is found on the automation of green building rating tools that brings up an essential gap to develop an automated analog computerized programming tool. This paper present a proposed research aim to develop an integrated web-based automated analog computerized programming that applies green building rating assessment tool, green technology and life cycle cost analysis. It also emphasizes to identify variables of MyCrest and LCC to be integrated and developed in a framework then transformed into automated analog computerized programming. A mix methodology of qualitative and quantitative survey and its development portray the planned to carry MyCrest-LCC integration to an automated level. In this study, the preliminary literature review enriches better understanding of Green Building Rating Tools (GBRT) integration to LCC. The outcome of this research is a pave way for future researchers to integrate other efficient tool and parameters that contributes towards green buildings and future agendas.

Towards a characterization of information automation systems on the flight deck

NASA Astrophysics Data System (ADS)

Dudley, Rachel Feddersen

This thesis summarizes research to investigate the characteristics that define information automation systems used on aircraft flight decks and the significant impacts that these characteristics have on pilot performance. Major accomplishments of the work include the development of a set of characteristics that describe information automation systems on the flight deck and an experiment designed to study a subset of these characteristics. Information automation systems on the flight deck are responsible for the collection, processing, analysis, and presentation of data to the flightcrew. These systems pose human factors issues and challenges that must be considered by designers of these systems. Based on a previously developed formal definition of information automation for aircraft flight deck systems, an analysis process was developed and conducted to reach a refined set of information automation characteristics. In this work, characteristics are defined as a set of properties or attributes that describe an information automation system's operation or behavior, which can be used to identify and assess potential human factors issues. Hypotheses were formed for a subset of the characteristics: Automation Visibility, Information Quality, and Display Complexity. An experimental investigation was developed to measure performance impacts related to these characteristics, which showed mixed results of expected and surprising findings, with many interactions. A set of recommendations were then developed based on the experimental observations. Ensuring that the right information is presented to pilots at the right time and in the appropriate manner is the job of flight deck system designers. This work provides a foundation for developing recommendations and guidelines specific to information automation on the flight deck with the goal of improving the design and evaluation of information automation systems before they are implemented.

Astronomical algorithms for automated analysis of tissue protein expression in breast cancer

PubMed Central

Ali, H R; Irwin, M; Morris, L; Dawson, S-J; Blows, F M; Provenzano, E; Mahler-Araujo, B; Pharoah, P D; Walton, N A; Brenton, J D; Caldas, C

2013-01-01

Background: High-throughput evaluation of tissue biomarkers in oncology has been greatly accelerated by the widespread use of tissue microarrays (TMAs) and immunohistochemistry. Although TMAs have the potential to facilitate protein expression profiling on a scale to rival experiments of tumour transcriptomes, the bottleneck and imprecision of manually scoring TMAs has impeded progress. Methods: We report image analysis algorithms adapted from astronomy for the precise automated analysis of IHC in all subcellular compartments. The power of this technique is demonstrated using over 2000 breast tumours and comparing quantitative automated scores against manual assessment by pathologists. Results: All continuous automated scores showed good correlation with their corresponding ordinal manual scores. For oestrogen receptor (ER), the correlation was 0.82, P<0.0001, for BCL2 0.72, P<0.0001 and for HER2 0.62, P<0.0001. Automated scores showed excellent concordance with manual scores for the unsupervised assignment of cases to ‘positive' or ‘negative' categories with agreement rates of up to 96%. Conclusion: The adaptation of astronomical algorithms coupled with their application to large annotated study cohorts, constitutes a powerful tool for the realisation of the enormous potential of digital pathology. PMID:23329232

Automated Slide Scanning and Segmentation in Fluorescently-labeled Tissues Using a Widefield High-content Analysis System.

PubMed

Poon, Candice C; Ebacher, Vincent; Liu, Katherine; Yong, Voon Wee; Kelly, John James Patrick

2018-05-03

Automated slide scanning and segmentation of fluorescently-labeled tissues is the most efficient way to analyze whole slides or large tissue sections. Unfortunately, many researchers spend large amounts of time and resources developing and optimizing workflows that are only relevant to their own experiments. In this article, we describe a protocol that can be used by those with access to a widefield high-content analysis system (WHCAS) to image any slide-mounted tissue, with options for customization within pre-built modules found in the associated software. Not originally intended for slide scanning, the steps detailed in this article make it possible to acquire slide scanning images in the WHCAS which can be imported into the associated software. In this example, the automated segmentation of brain tumor slides is demonstrated, but the automated segmentation of any fluorescently-labeled nuclear or cytoplasmic marker is possible. Furthermore, there are a variety of other quantitative software modules including assays for protein localization/translocation, cellular proliferation/viability/apoptosis, and angiogenesis that can be run. This technique will save researchers time and effort and create an automated protocol for slide analysis.

Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies.

PubMed

Atkinson, Jonathan A; Lobet, Guillaume; Noll, Manuel; Meyer, Patrick E; Griffiths, Marcus; Wells, Darren M

2017-10-01

Genetic analyses of plant root systems require large datasets of extracted architectural traits. To quantify such traits from images of root systems, researchers often have to choose between automated tools (that are prone to error and extract only a limited number of architectural traits) or semi-automated ones (that are highly time consuming). We trained a Random Forest algorithm to infer architectural traits from automatically extracted image descriptors. The training was performed on a subset of the dataset, then applied to its entirety. This strategy allowed us to (i) decrease the image analysis time by 73% and (ii) extract meaningful architectural traits based on image descriptors. We also show that these traits are sufficient to identify the quantitative trait loci that had previously been discovered using a semi-automated method. We have shown that combining semi-automated image analysis with machine learning algorithms has the power to increase the throughput of large-scale root studies. We expect that such an approach will enable the quantification of more complex root systems for genetic studies. We also believe that our approach could be extended to other areas of plant phenotyping. © The Authors 2017. Published by Oxford University Press.

Combining semi-automated image analysis techniques with machine learning algorithms to accelerate large-scale genetic studies

PubMed Central

Atkinson, Jonathan A.; Lobet, Guillaume; Noll, Manuel; Meyer, Patrick E.; Griffiths, Marcus

2017-01-01

Abstract Genetic analyses of plant root systems require large datasets of extracted architectural traits. To quantify such traits from images of root systems, researchers often have to choose between automated tools (that are prone to error and extract only a limited number of architectural traits) or semi-automated ones (that are highly time consuming). We trained a Random Forest algorithm to infer architectural traits from automatically extracted image descriptors. The training was performed on a subset of the dataset, then applied to its entirety. This strategy allowed us to (i) decrease the image analysis time by 73% and (ii) extract meaningful architectural traits based on image descriptors. We also show that these traits are sufficient to identify the quantitative trait loci that had previously been discovered using a semi-automated method. We have shown that combining semi-automated image analysis with machine learning algorithms has the power to increase the throughput of large-scale root studies. We expect that such an approach will enable the quantification of more complex root systems for genetic studies. We also believe that our approach could be extended to other areas of plant phenotyping. PMID:29020748

CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation

PubMed Central

2013-01-01

The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm, the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening. PMID:23938087

CellSegm - a MATLAB toolbox for high-throughput 3D cell segmentation.

PubMed

Hodneland, Erlend; Kögel, Tanja; Frei, Dominik Michael; Gerdes, Hans-Hermann; Lundervold, Arvid

2013-08-09

: The application of fluorescence microscopy in cell biology often generates a huge amount of imaging data. Automated whole cell segmentation of such data enables the detection and analysis of individual cells, where a manual delineation is often time consuming, or practically not feasible. Furthermore, compared to manual analysis, automation normally has a higher degree of reproducibility. CellSegm, the software presented in this work, is a Matlab based command line software toolbox providing an automated whole cell segmentation of images showing surface stained cells, acquired by fluorescence microscopy. It has options for both fully automated and semi-automated cell segmentation. Major algorithmic steps are: (i) smoothing, (ii) Hessian-based ridge enhancement, (iii) marker-controlled watershed segmentation, and (iv) feature-based classfication of cell candidates. Using a wide selection of image recordings and code snippets, we demonstrate that CellSegm has the ability to detect various types of surface stained cells in 3D. After detection and outlining of individual cells, the cell candidates can be subject to software based analysis, specified and programmed by the end-user, or they can be analyzed by other software tools. A segmentation of tissue samples with appropriate characteristics is also shown to be resolvable in CellSegm. The command-line interface of CellSegm facilitates scripting of the separate tools, all implemented in Matlab, offering a high degree of flexibility and tailored workflows for the end-user. The modularity and scripting capabilities of CellSegm enable automated workflows and quantitative analysis of microscopic data, suited for high-throughput image based screening.

Automated Forensic Animal Family Identification by Nested PCR and Melt Curve Analysis on an Off-the-Shelf Thermocycler Augmented with a Centrifugal Microfluidic Disk Segment

PubMed Central

Zengerle, Roland; von Stetten, Felix; Schmidt, Ulrike

2015-01-01

Nested PCR remains a labor-intensive and error-prone biomolecular analysis. Laboratory workflow automation by precise control of minute liquid volumes in centrifugal microfluidic Lab-on-a-Chip systems holds great potential for such applications. However, the majority of these systems require costly custom-made processing devices. Our idea is to augment a standard laboratory device, here a centrifugal real-time PCR thermocycler, with inbuilt liquid handling capabilities for automation. We have developed a microfluidic disk segment enabling an automated nested real-time PCR assay for identification of common European animal groups adapted to forensic standards. For the first time we utilize a novel combination of fluidic elements, including pre-storage of reagents, to automate the assay at constant rotational frequency of an off-the-shelf thermocycler. It provides a universal duplex pre-amplification of short fragments of the mitochondrial 12S rRNA and cytochrome b genes, animal-group-specific main-amplifications, and melting curve analysis for differentiation. The system was characterized with respect to assay sensitivity, specificity, risk of cross-contamination, and detection of minor components in mixtures. 92.2% of the performed tests were recognized as fluidically failure-free sample handling and used for evaluation. Altogether, augmentation of the standard real-time thermocycler with a self-contained centrifugal microfluidic disk segment resulted in an accelerated and automated analysis reducing hands-on time, and circumventing the risk of contamination associated with regular nested PCR protocols. PMID:26147196

Automated Retroillumination Photography Analysis for Objective Assessment of Fuchs Corneal Dystrophy.

PubMed

Eghrari, Allen O; Mumtaz, Aisha A; Garrett, Brian; Rezaei, Mahsa; Akhavan, Mina S; Riazuddin, S Amer; Gottsch, John D

2017-01-01

Retroillumination photography analysis is an objective tool for the assessment of the number and distribution of guttae in eyes affected with Fuchs corneal dystrophy (FCD). Current protocols include manual processing of images; here, we assess validity and interrater reliability of automated analysis across various levels of FCD severity. Retroillumination photographs of 97 FCD-affected corneas were acquired, and total counts of guttae were previously summated manually. For each cornea, a single image was loaded into ImageJ software. We reduced color variability and subtracted background noise. Reflection of light from each gutta was identified as a local area of maximum intensity and counted automatically. Noise tolerance level was titrated for each cornea by examining a small region of each image with automated overlay to ensure appropriate coverage of individual guttae. We tested interrater reliability of automated counts of guttae across a spectrum of clinical and educational experience. A set of 97 retroillumination photographs was analyzed. Clinical severity as measured by a modified Krachmer scale ranged from a severity level of 1 to 5 in the set of analyzed corneas. Automated counts by an ophthalmologist correlated strongly with Krachmer grading (R = 0.79) and manual counts (R = 0.88). Intraclass correlation coefficients demonstrated strong correlation at 0.924 (95% CI, 0.870-0.958) among cases analyzed by 3 students, and 0.869 (95% CI, 0.797-0.918) among cases for which images were analyzed by an ophthalmologist and 2 students. Automated retroillumination photography analysis allows for grading of FCD severity with high resolution across a spectrum of disease severity.

The ECLSS Advanced Automation Project Evolution and Technology Assessment

NASA Technical Reports Server (NTRS)

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

1990-01-01

Viewgraphs on Environmental Control and Life Support System (ECLSS) advanced automation project evolution and technology assessment are presented. Topics covered include: the ECLSS advanced automation project; automatic fault diagnosis of ECLSS subsystems descriptions; in-line, real-time chemical and microbial fluid analysis; and object-oriented, distributed chemical and microbial modeling of regenerative environmental control systems description.

The Automated Logistics Element Planning System (ALEPS)

NASA Technical Reports Server (NTRS)

Schwaab, Douglas G.

1991-01-01

The design and functions of ALEPS (Automated Logistics Element Planning System) is a computer system that will automate planning and decision support for Space Station Freedom Logistical Elements (LEs) resupply and return operations. ALEPS provides data management, planning, analysis, monitoring, interfacing, and flight certification for support of LE flight load planning activities. The prototype ALEPS algorithm development is described.

Instrument Control (iC) – An Open-Source Software to Automate Test Equipment

PubMed Central

Pernstich, K. P.

2012-01-01

It has become common practice to automate data acquisition from programmable instrumentation, and a range of different software solutions fulfill this task. Many routine measurements require sequential processing of certain tasks, for instance to adjust the temperature of a sample stage, take a measurement, and repeat that cycle for other temperatures. This paper introduces an open-source Java program that processes a series of text-based commands that define the measurement sequence. These commands are in an intuitive format which provides great flexibility and allows quick and easy adaptation to various measurement needs. For each of these commands, the iC-framework calls a corresponding Java method that addresses the specified instrument to perform the desired task. The functionality of iC can be extended with minimal programming effort in Java or Python, and new measurement equipment can be addressed by defining new commands in a text file without any programming. PMID:26900522

Instrument Control (iC) - An Open-Source Software to Automate Test Equipment.

PubMed

Pernstich, K P

2012-01-01

It has become common practice to automate data acquisition from programmable instrumentation, and a range of different software solutions fulfill this task. Many routine measurements require sequential processing of certain tasks, for instance to adjust the temperature of a sample stage, take a measurement, and repeat that cycle for other temperatures. This paper introduces an open-source Java program that processes a series of text-based commands that define the measurement sequence. These commands are in an intuitive format which provides great flexibility and allows quick and easy adaptation to various measurement needs. For each of these commands, the iC-framework calls a corresponding Java method that addresses the specified instrument to perform the desired task. The functionality of iC can be extended with minimal programming effort in Java or Python, and new measurement equipment can be addressed by defining new commands in a text file without any programming.

Engagement with a Text-Messaging Intervention Improves Adherence in Adolescents with Type 1 Diabetes: Brief Report.

PubMed

Zhang, Shuodan; Hamburger, Emily; Kahanda, Sachini; Lyttle, Morgan; Williams, Rodayne; Jaser, Sarah S

2018-05-01

Adherence to diabetes management is a challenge for adolescents with type 1 diabetes (T1D). Positive psychology interventions have improved adherence to treatment recommendations in adults with chronic health conditions but have not been widely tested in pediatric populations. We hypothesized that higher engagement with a text-messaging intervention to promote positive affect would increase the effects on diabetes management among adolescents with T1D. Adolescents with T1D (n = 48) and their caregivers were randomized to either an attention control condition or a novel positive psychology intervention delivered through personalized automated text messaging. We examined rates of engagement (percent response to text messages) in relation to demographic factors, and we explored the effect of engagement in relation to adherence and glycemic control. Adolescent engagement was good (mean response rate of 76%) over the 8-week intervention. Engagement was related to adolescents' gender, race, baseline glycemic control, and blood glucose monitoring, but not to treatment type (pump vs. injection), diabetes duration, age, or household income. There was a significant effect of level of engagement on better caregiver-reported adherence, but adolescents' engagement was not related to self-reported adherence or glycemic control. These results indicate feasibility and initial efficacy of using automated text-messaging to deliver an intervention aimed at promoting adherence in adolescents with T1D.

Creation of a virtual cutaneous tissue bank

NASA Astrophysics Data System (ADS)

LaFramboise, William A.; Shah, Sujal; Hoy, R. W.; Letbetter, D.; Petrosko, P.; Vennare, R.; Johnson, Peter C.

2000-04-01

Cellular and non-cellular constituents of skin contain fundamental morphometric features and structural patterns that correlate with tissue function. High resolution digital image acquisitions performed using an automated system and proprietary software to assemble adjacent images and create a contiguous, lossless, digital representation of individual microscope slide specimens. Serial extraction, evaluation and statistical analysis of cutaneous feature is performed utilizing an automated analysis system, to derive normal cutaneous parameters comprising essential structural skin components. Automated digital cutaneous analysis allows for fast extraction of microanatomic dat with accuracy approximating manual measurement. The process provides rapid assessment of feature both within individual specimens and across sample populations. The images, component data, and statistical analysis comprise a bioinformatics database to serve as an architectural blueprint for skin tissue engineering and as a diagnostic standard of comparison for pathologic specimens.

Automated macromolecular crystallization screening

DOEpatents

Segelke, Brent W.; Rupp, Bernhard; Krupka, Heike I.

2005-03-01

An automated macromolecular crystallization screening system wherein a multiplicity of reagent mixes are produced. A multiplicity of analysis plates is produced utilizing the reagent mixes combined with a sample. The analysis plates are incubated to promote growth of crystals. Images of the crystals are made. The images are analyzed with regard to suitability of the crystals for analysis by x-ray crystallography. A design of reagent mixes is produced based upon the expected suitability of the crystals for analysis by x-ray crystallography. A second multiplicity of mixes of the reagent components is produced utilizing the design and a second multiplicity of reagent mixes is used for a second round of automated macromolecular crystallization screening. In one embodiment the multiplicity of reagent mixes are produced by a random selection of reagent components.

Automated electric power management and control for Space Station Freedom

NASA Technical Reports Server (NTRS)

Dolce, James L.; Mellor, Pamela A.; Kish, James A.

1990-01-01

A comprehensive automation design is being developed for Space Station Freedom's electric power system. It strives to increase station productivity by applying expert systems and conventional algorithms to automate power system operation. An integrated approach to the power system command and control problem is defined and used to direct technology development in: diagnosis, security monitoring and analysis, battery management, and cooperative problem-solving for resource allocation. The prototype automated power system is developed using simulations and test-beds.

Automated systems to identify relevant documents in product risk management

PubMed Central

2012-01-01

Background Product risk management involves critical assessment of the risks and benefits of health products circulating in the market. One of the important sources of safety information is the primary literature, especially for newer products which regulatory authorities have relatively little experience with. Although the primary literature provides vast and diverse information, only a small proportion of which is useful for product risk assessment work. Hence, the aim of this study is to explore the possibility of using text mining to automate the identification of useful articles, which will reduce the time taken for literature search and hence improving work efficiency. In this study, term-frequency inverse document-frequency values were computed for predictors extracted from the titles and abstracts of articles related to three tumour necrosis factors-alpha blockers. A general automated system was developed using only general predictors and was tested for its generalizability using articles related to four other drug classes. Several specific automated systems were developed using both general and specific predictors and training sets of different sizes in order to determine the minimum number of articles required for developing such systems. Results The general automated system had an area under the curve value of 0.731 and was able to rank 34.6% and 46.2% of the total number of 'useful' articles among the first 10% and 20% of the articles presented to the evaluators when tested on the generalizability set. However, its use may be limited by the subjective definition of useful articles. For the specific automated system, it was found that only 20 articles were required to develop a specific automated system with a prediction performance (AUC 0.748) that was better than that of general automated system. Conclusions Specific automated systems can be developed rapidly and avoid problems caused by subjective definition of useful articles. Thus the efficiency of product risk management can be improved with the use of specific automated systems. PMID:22380483

Cost-Effectiveness Analysis of the Automation of a Circulation System.

ERIC Educational Resources Information Center

Mosley, Isobel

A general methodology for cost effectiveness analysis was developed and applied to the Colorado State University library loan desk. The cost effectiveness of the existing semi-automated circulation system was compared with that of a fully manual one, based on the existing manual subsystem. Faculty users' time and computer operating costs were…

Method 365.5 Determination of Orthophosphate in Estuarine and Coastal Waters by Automated Colorimetric Analysis

EPA Science Inventory

This method provides a procedure for the determination of low-level orthophosphate concentrations normally found in estuarine and/or coastal waters. It is based upon the method of Murphy and Riley1 adapted for automated segmented flow analysis2 in which the two reagent solutions ...

An Automated Data Analysis Tool for Livestock Market Data

ERIC Educational Resources Information Center

Williams, Galen S.; Raper, Kellie Curry

2011-01-01

This article describes an automated data analysis tool that allows Oklahoma Cooperative Extension Service educators to disseminate results in a timely manner. Primary data collected at Oklahoma Quality Beef Network (OQBN) certified calf auctions across the state results in a large amount of data per sale site. Sale summaries for an individual sale…

Minimum Sample Size Requirements for Mokken Scale Analysis

ERIC Educational Resources Information Center

Straat, J. Hendrik; van der Ark, L. Andries; Sijtsma, Klaas

2014-01-01

An automated item selection procedure in Mokken scale analysis partitions a set of items into one or more Mokken scales, if the data allow. Two algorithms are available that pursue the same goal of selecting Mokken scales of maximum length: Mokken's original automated item selection procedure (AISP) and a genetic algorithm (GA). Minimum…

Analysis of Connected and Automated Vehicle Technologies Highlights

Science.gov Websites

Uncertainty in Potential Effects on Fuel Use, Miles Traveled | News | NREL Analysis of Connected and Automated Vehicle Technologies Highlights Uncertainty in Potential Effects on Fuel Use, Miles Potential Effects on Fuel Use, Miles Traveled December 13, 2016 A joint study from the U.S. Department of

Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography

DTIC Science & Technology

1980-03-01

interpreting/smoothing data containing a significant percentage of gross errors, and thus is ideally suited for applications in automated image ... analysis where interpretation is based on the data provided by error-prone feature detectors. A major portion of the paper describes the application of

The Function of Semantics in Automated Language Processing.

ERIC Educational Resources Information Center

Pacak, Milos; Pratt, Arnold W.

This paper is a survey of some of the major semantic models that have been developed for automated semantic analysis of natural language. Current approaches to semantic analysis and logical interference are based mainly on models of human cognitive processes such as Quillian's semantic memory, Simmon's Protosynthex III and others. All existing…

The role of flow injection analysis within the framework of an automated laboratory

PubMed Central

Stockwell, Peter B.

1990-01-01

Flow Injection Analysis (FIA) was invented at roughly the same time by two quite dissimilar research groups [1,2]. FIA was patented by both groups in 1974; a year also marked by the publication of the first book on automatic chemical analysis [3]. This book was a major undertaking for its authors and it is hoped that it has added to the knowledge of those analysts attempting to automate their work or to increase the level of computerization/automation and thus reduce staffing commitments. This review discusses the role of FIA in laboratory automation, the advantages and disadvantages of the FIA approach, and the part it could play in future developments. It is important to stress at the outset that the FIA approach is all too often closely paralleled with convention al continuous flow analysis (CFA). This is a mistake for many reasons, none the least of which because of the considerable success of the CFA approach in contrast to the present lack of penetration in the commercial market-place of FIA instrumentation. PMID:18925262

Screening for cervical cancer using automated analysis of PAP-smears.

PubMed

Bengtsson, Ewert; Malm, Patrik

2014-01-01

Cervical cancer is one of the most deadly and common forms of cancer among women if no action is taken to prevent it, yet it is preventable through a simple screening test, the so-called PAP-smear. This is the most effective cancer prevention measure developed so far. But the visual examination of the smears is time consuming and expensive and there have been numerous attempts at automating the analysis ever since the test was introduced more than 60 years ago. The first commercial systems for automated analysis of the cell samples appeared around the turn of the millennium but they have had limited impact on the screening costs. In this paper we examine the key issues that need to be addressed when an automated analysis system is developed and discuss how these challenges have been met over the years. The lessons learned may be useful in the efforts to create a cost-effective screening system that could make affordable screening for cervical cancer available for all women globally, thus preventing most of the quarter million annual unnecessary deaths still caused by this disease.

Automation and decision support in interactive consumer products.

PubMed

Sauer, J; Rüttinger, B

2007-06-01

This article presents two empirical studies (n = 30, n = 48) that are concerned with different forms of automation in interactive consumer products. The goal of the studies was to evaluate the effectiveness of two types of automation: perceptual augmentation (i.e. supporting users' information acquisition and analysis); and control integration (i.e. supporting users' action selection and implementation). Furthermore, the effectiveness of on-product information (i.e. labels attached to product) in supporting automation design was evaluated. The findings suggested greater benefits for automation in control integration than in perceptual augmentation alone, which may be partly due to the specific requirements of consumer product usage. If employed appropriately, on-product information can be a helpful means of information conveyance. The article discusses the implications of automation design in interactive consumer products while drawing on automation models from the work environment.

A Comparison of Human Narrative Coding of Redemption and Automated Linguistic Analysis for Understanding Life Stories.

PubMed

Weston, Sara J; Cox, Keith S; Condon, David M; Jackson, Joshua J

2016-10-01

The majority of life narrative research is performed using trained human coders. In contrast, automated linguistic analysis is oft employed in the study of verbal behaviors. These two methodological approaches are directly compared to determine the utility of automated linguistic analysis for the study of life narratives. In a study of in-person interviews (N = 158) and a second study of life stories collected online (N = 242), redemption scores are compared to the output of the Linguistic Inquiry and Word Count (Pennebaker, Francis & Booth, 2001). Additionally, patterns of language are found using exploratory principal components analysis. In both studies, redemption scores are modestly correlated with some LIWC categories and unassociated with the components. Patterns of language do not replicate across samples, indicating that the structure of language does not extend to a broader population. Redemption scores and linguistic components are independent predictors of life satisfaction up to 3 years later. These studies converge on the finding that human-coded redemption and automated linguistic analysis are complementary and nonredundant methods of analyzing life narratives, and considerations for the study of life narratives are discussed. © 2015 Wiley Periodicals, Inc.

Study of Intelligent Secure Chemical Inventory Management System

NASA Astrophysics Data System (ADS)

Shukran, Mohd Afizi Mohd; Naim Abdullah, Muhammad; Nazri Ismail, Mohd; Maskat, Kamaruzaman; Isa, Mohd Rizal Mohd; Shahfee Ishak, Muhammad; Adib Khairuddin, Muhamad

2017-08-01

Chemical inventory management system has been experiencing a new revolution from traditional inventory system which is manual to an automated inventory management system. In this paper, some review of the classic and modern approaches to chemical inventory management system has been discussed. This paper also describe about both type of inventory management. After a comparative analysis of the traditional method and automated method, it can be said that both methods have some distinctive characteristics. Moreover, the automated inventory management method has higher accuracy of calculation because the calculations are handled by software, eliminating possible errors and saving time. The automated inventory system also allows users and administrators to track the availability, location and consumption of chemicals. The study of this paper can provide forceful review analysis support for the chemical inventory management related research.

Automated power management and control

NASA Technical Reports Server (NTRS)

Dolce, James L.

1991-01-01

A comprehensive automation design is being developed for Space Station Freedom's electric power system. A joint effort between NASA's Office of Aeronautics and Exploration Technology and NASA's Office of Space Station Freedom, it strives to increase station productivity by applying expert systems and conventional algorithms to automate power system operation. The initial station operation will use ground-based dispatches to perform the necessary command and control tasks. These tasks constitute planning and decision-making activities that strive to eliminate unplanned outages. We perceive an opportunity to help these dispatchers make fast and consistent on-line decisions by automating three key tasks: failure detection and diagnosis, resource scheduling, and security analysis. Expert systems will be used for the diagnostics and for the security analysis; conventional algorithms will be used for the resource scheduling.

Automation literature: A brief review and analysis

NASA Technical Reports Server (NTRS)

Smith, D.; Dieterly, D. L.

1980-01-01

Current thought and research positions which may allow for an improved capability to understand the impact of introducing automation to an existing system are established. The orientation was toward the type of studies which may provide some general insight into automation; specifically, the impact of automation in human performance and the resulting system performance. While an extensive number of articles were reviewed, only those that addressed the issue of automation and human performance were selected to be discussed. The literature is organized along two dimensions: time, Pre-1970, Post-1970; and type of approach, Engineering or Behavioral Science. The conclusions reached are not definitive, but do provide the initial stepping stones in an attempt to begin to bridge the concept of automation in a systematic progression.

Manual, semiautomated, and fully automated measurement of the aortic annulus for planning of transcatheter aortic valve replacement (TAVR/TAVI): analysis of interchangeability.

PubMed

Lou, Junyang; Obuchowski, Nancy A; Krishnaswamy, Amar; Popovic, Zoran; Flamm, Scott D; Kapadia, Samir R; Svensson, Lars G; Bolen, Michael A; Desai, Milind Y; Halliburton, Sandra S; Tuzcu, E Murat; Schoenhagen, Paul

2015-01-01

Preprocedural 3-dimensional CT imaging of the aortic annular plane plays a critical role for transcatheter aortic valve replacement (TAVR) planning; however, manual reconstructions are complex. Automated analysis software may improve reproducibility and agreement between readers but is incompletely validated. In 110 TAVR patients (mean age, 81 years; 37% female) undergoing preprocedural multidetector CT, automated reconstruction of the aortic annular plane and planimetry of the annulus was performed with a prototype of now commercially available software (syngo.CT Cardiac Function-Valve Pilot; Siemens Healthcare, Erlangen, Germany). Fully automated, semiautomated, and manual annulus measurements were compared. Intrareader and inter-reader agreement, intermodality agreement, and interchangeability were analyzed. Finally, the impact of these measurements on recommended valve size was evaluated. Semiautomated analysis required major correction in 5 patients (4.5%). In the remaining 95.5%, only minor correction was performed. Mean manual annulus area was significantly smaller than fully automated results (P < .001 for both readers) but similar to semiautomated measurements (5.0 vs 5.4 vs 4.9 cm(2), respectively). The frequency of concordant recommendations for valve size increased if manual analysis was replaced with the semiautomated method (60% agreement was improved to 82.4%; 95% confidence interval for the difference [69.1%-83.4%]). Semiautomated aortic annulus analysis, with minor correction by the user, provides reliable results in the context of TAVR annulus evaluation. Copyright © 2015 Society of Cardiovascular Computed Tomography. Published by Elsevier Inc. All rights reserved.

Robust Ambiguity Estimation for an Automated Analysis of the Intensive Sessions

NASA Astrophysics Data System (ADS)

Kareinen, Niko; Hobiger, Thomas; Haas, Rüdiger

2016-12-01

Very Long Baseline Interferometry (VLBI) is a unique space-geodetic technique that can directly determine the Earth's phase of rotation, namely UT1. The daily estimates of the difference between UT1 and Coordinated Universal Time (UTC) are computed from one-hour long VLBI Intensive sessions. These sessions are essential for providing timely UT1 estimates for satellite navigation systems. To produce timely UT1 estimates, efforts have been made to completely automate the analysis of VLBI Intensive sessions. This requires automated processing of X- and S-band group delays. These data often contain an unknown number of integer ambiguities in the observed group delays. In an automated analysis with the c5++ software the standard approach in resolving the ambiguities is to perform a simplified parameter estimation using a least-squares adjustment (L2-norm minimization). We implement the robust L1-norm with an alternative estimation method in c5++. The implemented method is used to automatically estimate the ambiguities in VLBI Intensive sessions for the Kokee-Wettzell baseline. The results are compared to an analysis setup where the ambiguity estimation is computed using the L2-norm. Additionally, we investigate three alternative weighting strategies for the ambiguity estimation. The results show that in automated analysis the L1-norm resolves ambiguities better than the L2-norm. The use of the L1-norm leads to a significantly higher number of good quality UT1-UTC estimates with each of the three weighting strategies.

Selecting automation for the clinical chemistry laboratory.

PubMed

Melanson, Stacy E F; Lindeman, Neal I; Jarolim, Petr

2007-07-01

Laboratory automation proposes to improve the quality and efficiency of laboratory operations, and may provide a solution to the quality demands and staff shortages faced by today's clinical laboratories. Several vendors offer automation systems in the United States, with both subtle and obvious differences. Arriving at a decision to automate, and the ensuing evaluation of available products, can be time-consuming and challenging. Although considerable discussion concerning the decision to automate has been published, relatively little attention has been paid to the process of evaluating and selecting automation systems. To outline a process for evaluating and selecting automation systems as a reference for laboratories contemplating laboratory automation. Our Clinical Chemistry Laboratory staff recently evaluated all major laboratory automation systems in the United States, with their respective chemistry and immunochemistry analyzers. Our experience is described and organized according to the selection process, the important considerations in clinical chemistry automation, decisions and implementation, and we give conclusions pertaining to this experience. Including the formation of a committee, workflow analysis, submitting a request for proposal, site visits, and making a final decision, the process of selecting chemistry automation took approximately 14 months. We outline important considerations in automation design, preanalytical processing, analyzer selection, postanalytical storage, and data management. Selecting clinical chemistry laboratory automation is a complex, time-consuming process. Laboratories considering laboratory automation may benefit from the concise overview and narrative and tabular suggestions provided.

Applying Dataflow Architecture and Visualization Tools to In Vitro Pharmacology Data Automation.

PubMed

Pechter, David; Xu, Serena; Kurtz, Marc; Williams, Steven; Sonatore, Lisa; Villafania, Artjohn; Agrawal, Sony

2016-12-01

The pace and complexity of modern drug discovery places ever-increasing demands on scientists for data analysis and interpretation. Data flow programming and modern visualization tools address these demands directly. Three different requirements-one for allosteric modulator analysis, one for a specialized clotting analysis, and one for enzyme global progress curve analysis-are reviewed, and their execution in a combined data flow/visualization environment is outlined. © 2016 Society for Laboratory Automation and Screening.

Automated 3D closed surface segmentation: application to vertebral body segmentation in CT images.

PubMed

Liu, Shuang; Xie, Yiting; Reeves, Anthony P

2016-05-01

A fully automated segmentation algorithm, progressive surface resolution (PSR), is presented in this paper to determine the closed surface of approximately convex blob-like structures that are common in biomedical imaging. The PSR algorithm was applied to the cortical surface segmentation of 460 vertebral bodies on 46 low-dose chest CT images, which can be potentially used for automated bone mineral density measurement and compression fracture detection. The target surface is realized by a closed triangular mesh, which thereby guarantees the enclosure. The surface vertices of the triangular mesh representation are constrained along radial trajectories that are uniformly distributed in 3D angle space. The segmentation is accomplished by determining for each radial trajectory the location of its intersection with the target surface. The surface is first initialized based on an input high confidence boundary image and then resolved progressively based on a dynamic attraction map in an order of decreasing degree of evidence regarding the target surface location. For the visual evaluation, the algorithm achieved acceptable segmentation for 99.35 % vertebral bodies. Quantitative evaluation was performed on 46 vertebral bodies and achieved overall mean Dice coefficient of 0.939 (with max [Formula: see text] 0.957, min [Formula: see text] 0.906 and standard deviation [Formula: see text] 0.011) using manual annotations as the ground truth. Both visual and quantitative evaluations demonstrate encouraging performance of the PSR algorithm. This novel surface resolution strategy provides uniform angular resolution for the segmented surface with computation complexity and runtime that are linearly constrained by the total number of vertices of the triangular mesh representation.

Industrial applications of automated X-ray inspection

NASA Astrophysics Data System (ADS)

Shashishekhar, N.

2015-03-01

Many industries require that 100% of manufactured parts be X-ray inspected. Factors such as high production rates, focus on inspection quality, operator fatigue and inspection cost reduction translate to an increasing need for automating the inspection process. Automated X-ray inspection involves the use of image processing algorithms and computer software for analysis and interpretation of X-ray images. This paper presents industrial applications and illustrative case studies of automated X-ray inspection in areas such as automotive castings, fuel plates, air-bag inflators and tires. It is usually necessary to employ application-specific automated inspection strategies and techniques, since each application has unique characteristics and interpretation requirements.

Assessing Students' Use of Evidence and Organization in Response-to-Text Writing: Using Natural Language Processing for Rubric-Based Automated Scoring

ERIC Educational Resources Information Center

Rahimi, Zahra; Litman, Diane; Correnti, Richard; Wang, Elaine; Matsumura, Lindsay Clare

2017-01-01

This paper presents an investigation of score prediction based on natural language processing for two targeted constructs within analytic text-based writing: 1) students' effective use of evidence and, 2) their organization of ideas and evidence in support of their claim. With the long-term goal of producing feedback for students and teachers, we…

Comparison of pre-processing techniques for fluorescence microscopy images of cells labeled for actin.

PubMed

Muralidhar, Gautam S; Channappayya, Sumohana S; Slater, John H; Blinka, Ellen M; Bovik, Alan C; Frey, Wolfgang; Markey, Mia K

2008-11-06

Automated analysis of fluorescence microscopy images of endothelial cells labeled for actin is important for quantifying changes in the actin cytoskeleton. The current manual approach is laborious and inefficient. The goal of our work is to develop automated image analysis methods, thereby increasing cell analysis throughput. In this study, we present preliminary results on comparing different algorithms for cell segmentation and image denoising.

Analysis And Control System For Automated Welding

NASA Technical Reports Server (NTRS)

Powell, Bradley W.; Burroughs, Ivan A.; Kennedy, Larry Z.; Rodgers, Michael H.; Goode, K. Wayne

1994-01-01

Automated variable-polarity plasma arc (VPPA) welding apparatus operates under electronic supervision by welding analysis and control system. System performs all major monitoring and controlling functions. It acquires, analyzes, and displays weld-quality data in real time and adjusts process parameters accordingly. Also records pertinent data for use in post-weld analysis and documentation of quality. System includes optoelectronic sensors and data processors that provide feedback control of welding process.

Three-dimensional registration of intravascular optical coherence tomography and cryo-image volumes for microscopic-resolution validation.

PubMed

Prabhu, David; Mehanna, Emile; Gargesha, Madhusudhana; Brandt, Eric; Wen, Di; van Ditzhuijzen, Nienke S; Chamie, Daniel; Yamamoto, Hirosada; Fujino, Yusuke; Alian, Ali; Patel, Jaymin; Costa, Marco; Bezerra, Hiram G; Wilson, David L

2016-04-01

Evidence suggests high-resolution, high-contrast, [Formula: see text] intravascular optical coherence tomography (IVOCT) can distinguish plaque types, but further validation is needed, especially for automated plaque characterization. We developed experimental and three-dimensional (3-D) registration methods to provide validation of IVOCT pullback volumes using microscopic, color, and fluorescent cryo-image volumes with optional registered cryo-histology. A specialized registration method matched IVOCT pullback images acquired in the catheter reference frame to a true 3-D cryo-image volume. Briefly, an 11-parameter registration model including a polynomial virtual catheter was initialized within the cryo-image volume, and perpendicular images were extracted, mimicking IVOCT image acquisition. Virtual catheter parameters were optimized to maximize cryo and IVOCT lumen overlap. Multiple assessments suggested that the registration error was better than the [Formula: see text] spacing between IVOCT image frames. Tests on a digital synthetic phantom gave a registration error of only [Formula: see text] (signed distance). Visual assessment of randomly presented nearby frames suggested registration accuracy within 1 IVOCT frame interval ([Formula: see text]). This would eliminate potential misinterpretations confronted by the typical histological approaches to validation, with estimated 1-mm errors. The method can be used to create annotated datasets and automated plaque classification methods and can be extended to other intravascular imaging modalities.

Automated image-based phenotypic analysis in zebrafish embryos

PubMed Central

Vogt, Andreas; Cholewinski, Andrzej; Shen, Xiaoqiang; Nelson, Scott; Lazo, John S.; Tsang, Michael; Hukriede, Neil A.

2009-01-01

Presently, the zebrafish is the only vertebrate model compatible with contemporary paradigms of drug discovery. Zebrafish embryos are amenable to automation necessary for high-throughput chemical screens, and optical transparency makes them potentially suited for image-based screening. However, the lack of tools for automated analysis of complex images presents an obstacle to utilizing the zebrafish as a high-throughput screening model. We have developed an automated system for imaging and analyzing zebrafish embryos in multi-well plates regardless of embryo orientation and without user intervention. Images of fluorescent embryos were acquired on a high-content reader and analyzed using an artificial intelligence-based image analysis method termed Cognition Network Technology (CNT). CNT reliably detected transgenic fluorescent embryos (Tg(fli1:EGFP)y1) arrayed in 96-well plates and quantified intersegmental blood vessel development in embryos treated with small molecule inhibitors of anigiogenesis. The results demonstrate it is feasible to adapt image-based high-content screening methodology to measure complex whole organism phenotypes. PMID:19235725

RootGraph: a graphic optimization tool for automated image analysis of plant roots

PubMed Central

Cai, Jinhai; Zeng, Zhanghui; Connor, Jason N.; Huang, Chun Yuan; Melino, Vanessa; Kumar, Pankaj; Miklavcic, Stanley J.

2015-01-01

This paper outlines a numerical scheme for accurate, detailed, and high-throughput image analysis of plant roots. In contrast to existing root image analysis tools that focus on root system-average traits, a novel, fully automated and robust approach for the detailed characterization of root traits, based on a graph optimization process is presented. The scheme, firstly, distinguishes primary roots from lateral roots and, secondly, quantifies a broad spectrum of root traits for each identified primary and lateral root. Thirdly, it associates lateral roots and their properties with the specific primary root from which the laterals emerge. The performance of this approach was evaluated through comparisons with other automated and semi-automated software solutions as well as against results based on manual measurements. The comparisons and subsequent application of the algorithm to an array of experimental data demonstrate that this method outperforms existing methods in terms of accuracy, robustness, and the ability to process root images under high-throughput conditions. PMID:26224880

Automated magnification calibration in transmission electron microscopy using Fourier analysis of replica images.

PubMed

van der Laak, Jeroen A W M; Dijkman, Henry B P M; Pahlplatz, Martin M M

2006-03-01

The magnification factor in transmission electron microscopy is not very precise, hampering for instance quantitative analysis of specimens. Calibration of the magnification is usually performed interactively using replica specimens, containing line or grating patterns with known spacing. In the present study, a procedure is described for automated magnification calibration using digital images of a line replica. This procedure is based on analysis of the power spectrum of Fourier transformed replica images, and is compared to interactive measurement in the same images. Images were used with magnification ranging from 1,000 x to 200,000 x. The automated procedure deviated on average 0.10% from interactive measurements. Especially for catalase replicas, the coefficient of variation of automated measurement was considerably smaller (average 0.28%) compared to that of interactive measurement (average 3.5%). In conclusion, calibration of the magnification in digital images from transmission electron microscopy may be performed automatically, using the procedure presented here, with high precision and accuracy.

Development of automated high throughput single molecular microfluidic detection platform for signal transduction analysis

NASA Astrophysics Data System (ADS)

Huang, Po-Jung; Baghbani Kordmahale, Sina; Chou, Chao-Kai; Yamaguchi, Hirohito; Hung, Mien-Chie; Kameoka, Jun

2016-03-01

Signal transductions including multiple protein post-translational modifications (PTM), protein-protein interactions (PPI), and protein-nucleic acid interaction (PNI) play critical roles for cell proliferation and differentiation that are directly related to the cancer biology. Traditional methods, like mass spectrometry, immunoprecipitation, fluorescence resonance energy transfer, and fluorescence correlation spectroscopy require a large amount of sample and long processing time. "microchannel for multiple-parameter analysis of proteins in single-complex (mMAPS)"we proposed can reduce the process time and sample volume because this system is composed by microfluidic channels, fluorescence microscopy, and computerized data analysis. In this paper, we will present an automated mMAPS including integrated microfluidic device, automated stage and electrical relay for high-throughput clinical screening. Based on this result, we estimated that this automated detection system will be able to screen approximately 150 patient samples in a 24-hour period, providing a practical application to analyze tissue samples in a clinical setting.

Automated SEM and TEM sample preparation applied to copper/low k materials

NASA Astrophysics Data System (ADS)

Reyes, R.; Shaapur, F.; Griffiths, D.; Diebold, A. C.; Foran, B.; Raz, E.

2001-01-01

We describe the use of automated microcleaving for preparation of both SEM and TEM samples as done by SELA's new MC500 and TEMstation tools. The MC500 is an automated microcleaving tool that is capable of producing cleaves with 0.25 μm accuracy resulting in SEM-ready samples. The TEMstation is capable of taking a sample output from the MC500 (or from SELA's earlier MC200 tool) and producing a FIB ready slice of 25±5 μm, mounted on a TEM-washer and ready for FIB thinning to electron transparency for TEM analysis. The materials selected for the tool set evaluation mainly included the Cu/TaN/HOSP low-k system. The paper is divided into three sections, experimental approach, SEM preparation and analysis of HOSP low-k, and TEM preparation and analysis of Cu/TaN/HOSP low-k samples. For the samples discussed, data is presented to show the quality of preparation provided by these new automated tools.

Assessment of Automated Analyses of Cell Migration on Flat and Nanostructured Surfaces

PubMed Central

Grădinaru, Cristian; Łopacińska, Joanna M.; Huth, Johannes; Kestler, Hans A.; Flyvbjerg, Henrik; Mølhave, Kristian

2012-01-01

Motility studies of cells often rely on computer software that analyzes time-lapse recorded movies and establishes cell trajectories fully automatically. This raises the question of reproducibility of results, since different programs could yield significantly different results of such automated analysis. The fact that the segmentation routines of such programs are often challenged by nanostructured surfaces makes the question more pertinent. Here we illustrate how it is possible to track cells on bright field microscopy images with image analysis routines implemented in an open-source cell tracking program, PACT (Program for Automated Cell Tracking). We compare the automated motility analysis of three cell tracking programs, PACT, Autozell, and TLA, using the same movies as input for all three programs. We find that different programs track overlapping, but different subsets of cells due to different segmentation methods. Unfortunately, population averages based on such different cell populations, differ significantly in some cases. Thus, results obtained with one software package are not necessarily reproducible by other software. PMID:24688640

TOPS On-Line: Automating the Construction and Maintenance of HTML Pages

NASA Technical Reports Server (NTRS)

Jones, Kennie H.

1994-01-01

After the Technology Opportunities Showcase (TOPS), in October, 1993, Langley Research Center's (LaRC) Information Systems Division (ISD) accepted the challenge to preserve the investment in information assembled in the TOPS exhibits by establishing a data base. Following the lead of several people at LaRC and others around the world, the HyperText Transport Protocol (HTTP) server and Mosaic were the obvious tools of choice for implementation. Initially, some TOPS exhibitors began the conventional approach of constructing HyperText Markup Language (HTML) pages of their exhibits as input to Mosaic. Considering the number of pages to construct, a better approach was conceived that would automate the construction of pages. This approach allowed completion of the data base construction in a shorter period of time using fewer resources than would have been possible with the conventional approach. It also provided flexibility for the maintenance and enhancement of the data base. Since that time, this approach has been used to automate construction of other HTML data bases. Through these experiences, it is concluded that the most effective use of the HTTP/Mosaic technology will require better tools and techniques for creating, maintaining and managing the HTML pages. The development and use of these tools and techniques are the subject of this document.

Automated basin delineation from digital terrain data

NASA Technical Reports Server (NTRS)

Marks, D.; Dozier, J.; Frew, J.

1983-01-01

While digital terrain grids are now in wide use, accurate delineation of drainage basins from these data is difficult to efficiently automate. A recursive order N solution to this problem is presented. The algorithm is fast because no point in the basin is checked more than once, and no points outside the basin are considered. Two applications for terrain analysis and one for remote sensing are given to illustrate the method, on a basin with high relief in the Sierra Nevada. This technique for automated basin delineation will enhance the utility of digital terrain analysis for hydrologic modeling and remote sensing.

Automated Run-Time Mission and Dialog Generation

DTIC Science & Technology

2007-03-01

Processing, Social Network Analysis, Simulation, Automated Scenario Generation 16. PRICE CODE 17. SECURITY CLASSIFICATION OF REPORT Unclassified...9 D. SOCIAL NETWORKS...13 B. MISSION AND DIALOG GENERATION.................................................13 C. SOCIAL NETWORKS

New Directions in Special Education.

ERIC Educational Resources Information Center

Jones, Reginald L., Ed.

The text presents a collection of articles dealing with new research and developments relevant to special education. Discussions include automation, teaching machines, programed instruction, psycholinguistic testing, differential diagnosis, language development and testing, and remediation techniques. Other topics consider measurement of behavior,…

Datalingvistik, 2000.

ERIC Educational Resources Information Center

Kjaersgaard, Poul Soren, Ed.

2002-01-01

Papers from the conference in this volume include the following: "Towards Corpus Annotation Standards--The MATE Workbench" (Laila Dybkjaer and Niels Ole Bernsen); "Danish Text-to-Speech Synthesis Based on Stored Acoustic Segments" (Charles Hoequist); "Toward a Method for the Automated Design of Semantic…

Estimating Computer-Based Training Development Times

DTIC Science & Technology

1987-10-14

beginners , must be sure they interpret terms correctly. As a result of this informal validation, the authors suggest refinements in the tool which...Productivity tools available: automated design tools, text processor interfaces, flowcharting software, software interfaces a Multimedia interfaces e

Information retrieval algorithms: A survey

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

Raghavan, P.

We give an overview of some algorithmic problems arising in the representation of text/image/multimedia objects in a form amenable to automated searching, and in conducting these searches efficiently. These operations are central to information retrieval and digital library systems.

An Analysis for Capital Expenditure Decisions at a Naval Regional Medical Center.

DTIC Science & Technology

1981-12-01

Service Equipment Review Committee 1. Portable defibrilator Computed tomographic scanner and cardioscope 2. ECG cart Automated blood cell counter 3. Gas...system sterilizer Gas system sterilizer 4. Automated blood cell Portable defibrilator and counter cardioscope 5. Computed tomographic ECG cart scanner...dictating and automated typing) systems. e. Filing equipment f. Automatic data processing equipment including data communications equipment. g

Poster presentations at the fifth engineering foundation conference on automated cytology, Pensacola, Florida, December 12--17, 1976

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

Sullivan, E.M.

1977-02-01

Poster sessions were used as a vehicle of information exchange. Of the 101 posters presented, abstracts were received for 71. The 71 abstracts presented are concerned with cell-cycle analysis by flow cytometry, flow microfluorometric DNA measurements, application of microfluorometry to cancer chemotherapy, automated classification of neutrophils, and other aspects of automated cytology. (HLW)

Department of the Army Cost Analysis Manual

DTIC Science & Technology

2001-05-01

SECTION I - AUTOMATED COST ESTIMATING INTEGRATED TOOLS ( ACEIT ) ................................................................179 SECTION II - AUTOMATED...Management & Comptroller) endorsed the Automated Cost Estimating Integrated Tools ( ACEIT ) model and since it is widely used to prepare POEs, CCAs and...CRB IPT (in ACEIT ) will be the basis for information contained in the CAB. Any remaining unresolved issues from the IPT process will be raised at the

Towards cross-lingual alerting for bursty epidemic events.

PubMed

Collier, Nigel

2011-10-06

Online news reports are increasingly becoming a source for event-based early warning systems that detect natural disasters. Harnessing the massive volume of information available from multilingual newswire presents as many challanges as opportunities due to the patterns of reporting complex spatio-temporal events. In this article we study the problem of utilising correlated event reports across languages. We track the evolution of 16 disease outbreaks using 5 temporal aberration detection algorithms on text-mined events classified according to disease and outbreak country. Using ProMED reports as a silver standard, comparative analysis of news data for 13 languages over a 129 day trial period showed improved sensitivity, F1 and timeliness across most models using cross-lingual events. We report a detailed case study analysis for Cholera in Angola 2010 which highlights the challenges faced in correlating news events with the silver standard. The results show that automated health surveillance using multilingual text mining has the potential to turn low value news into high value alerts if informed choices are used to govern the selection of models and data sources. An implementation of the C2 alerting algorithm using multilingual news is available at the BioCaster portal http://born.nii.ac.jp/?page=globalroundup.

Automated Cancer Registry Notifications: Validation of a Medical Text Analytics System for Identifying Patients with Cancer from a State-Wide Pathology Repository

PubMed Central

Nguyen, Anthony N; Moore, Julie; O'Dwyer, John; Philpot, Shoni

2016-01-01

The paper assesses the utility of Medtex on automating Cancer Registry notifications from narrative histology and cytology reports from the Queensland state-wide pathology information system. A corpus of 45.3 million pathology HL7 messages (including 119,581 histology and cytology reports) from a Queensland pathology repository for the year of 2009 was analysed by Medtex for cancer notification. Reports analysed by Medtex were consolidated at a patient level and compared against patients with notifiable cancers from the Queensland Oncology Repository (QOR). A stratified random sample of 1,000 patients was manually reviewed by a cancer clinical coder to analyse agreements and discrepancies. Sensitivity of 96.5% (95% confidence interval: 94.5-97.8%), specificity of 96.5% (95.3-97.4%) and positive predictive value of 83.7% (79.6-86.8%) were achieved for identifying cancer notifiable patients. Medtex achieved high sensitivity and specificity across the breadth of cancers, report types, pathology laboratories and pathologists throughout the State of Queensland. The high sensitivity also resulted in the identification of cancer patients that were not found in the QOR. High sensitivity was at the expense of positive predictive value; however, these cases may be considered as lower priority to Cancer Registries as they can be quickly reviewed. Error analysis revealed that system errors tended to be tumour stream dependent. Medtex is proving to be a promising medical text analytic system. High value cancer information can be generated through intelligent data classification and extraction on large volumes of unstructured pathology reports. PMID:28269893

Using Pathfinder networks to discover alignment between expert and consumer conceptual knowledge from online vaccine content.

PubMed

Amith, Muhammad; Cunningham, Rachel; Savas, Lara S; Boom, Julie; Schvaneveldt, Roger; Tao, Cui; Cohen, Trevor

2017-10-01

This study demonstrates the use of distributed vector representations and Pathfinder Network Scaling (PFNETS) to represent online vaccine content created by health experts and by laypeople. By analyzing a target audience's conceptualization of a topic, domain experts can develop targeted interventions to improve the basic health knowledge of consumers. The underlying assumption is that the content created by different groups reflects the mental organization of their knowledge. Applying automated text analysis to this content may elucidate differences between the knowledge structures of laypeople (heath consumers) and professionals (health experts). This paper utilizes vaccine information generated by laypeople and health experts to investigate the utility of this approach. We used an established technique from cognitive psychology, Pathfinder Network Scaling to infer the structure of the associational networks between concepts learned from online content using methods of distributional semantics. In doing so, we extend the original application of PFNETS to infer knowledge structures from individual participants, to infer the prevailing knowledge structures within communities of content authors. The resulting graphs reveal opportunities for public health and vaccination education experts to improve communication and intervention efforts directed towards health consumers. Our efforts demonstrate the feasibility of using an automated procedure to examine the manifestation of conceptual models within large bodies of free text, revealing evidence of conflicting understanding of vaccine concepts among health consumers as compared with health experts. Additionally, this study provides insight into the differences between consumer and expert abstraction of domain knowledge, revealing vaccine-related knowledge gaps that suggest opportunities to improve provider-patient communication. Copyright © 2017 Elsevier Inc. All rights reserved.

Automated Cancer Registry Notifications: Validation of a Medical Text Analytics System for Identifying Patients with Cancer from a State-Wide Pathology Repository.

PubMed

Nguyen, Anthony N; Moore, Julie; O'Dwyer, John; Philpot, Shoni

2016-01-01

The paper assesses the utility of Medtex on automating Cancer Registry notifications from narrative histology and cytology reports from the Queensland state-wide pathology information system. A corpus of 45.3 million pathology HL7 messages (including 119,581 histology and cytology reports) from a Queensland pathology repository for the year of 2009 was analysed by Medtex for cancer notification. Reports analysed by Medtex were consolidated at a patient level and compared against patients with notifiable cancers from the Queensland Oncology Repository (QOR). A stratified random sample of 1,000 patients was manually reviewed by a cancer clinical coder to analyse agreements and discrepancies. Sensitivity of 96.5% (95% confidence interval: 94.5-97.8%), specificity of 96.5% (95.3-97.4%) and positive predictive value of 83.7% (79.6-86.8%) were achieved for identifying cancer notifiable patients. Medtex achieved high sensitivity and specificity across the breadth of cancers, report types, pathology laboratories and pathologists throughout the State of Queensland. The high sensitivity also resulted in the identification of cancer patients that were not found in the QOR. High sensitivity was at the expense of positive predictive value; however, these cases may be considered as lower priority to Cancer Registries as they can be quickly reviewed. Error analysis revealed that system errors tended to be tumour stream dependent. Medtex is proving to be a promising medical text analytic system. High value cancer information can be generated through intelligent data classification and extraction on large volumes of unstructured pathology reports.

Substructure analysis techniques and automation. [to eliminate logistical data handling and generation chores

NASA Technical Reports Server (NTRS)

Hennrich, C. W.; Konrath, E. J., Jr.

1973-01-01

A basic automated substructure analysis capability for NASTRAN is presented which eliminates most of the logistical data handling and generation chores that are currently associated with the method. Rigid formats are proposed which will accomplish this using three new modules, all of which can be added to level 16 with a relatively small effort.

A system-level approach to automation research

NASA Technical Reports Server (NTRS)

Harrison, F. W.; Orlando, N. E.

1984-01-01

Automation is the application of self-regulating mechanical and electronic devices to processes that can be accomplished with the human organs of perception, decision, and actuation. The successful application of automation to a system process should reduce man/system interaction and the perceived complexity of the system, or should increase affordability, productivity, quality control, and safety. The expense, time constraints, and risk factors associated with extravehicular activities have led the Automation Technology Branch (ATB), as part of the NASA Automation Research and Technology Program, to investigate the use of robots and teleoperators as automation aids in the context of space operations. The ATB program addresses three major areas: (1) basic research in autonomous operations, (2) human factors research on man-machine interfaces with remote systems, and (3) the integration and analysis of automated systems. This paper reviews the current ATB research in the area of robotics and teleoperators.

End-to-end automated microfluidic platform for synthetic biology: from design to functional analysis

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

Linshiz, Gregory; Jensen, Erik; Stawski, Nina

Synthetic biology aims to engineer biological systems for desired behaviors. The construction of these systems can be complex, often requiring genetic reprogramming, extensive de novo DNA synthesis, and functional screening. Here, we present a programmable, multipurpose microfluidic platform and associated software and apply the platform to major steps of the synthetic biology research cycle: design, construction, testing, and analysis. We show the platform’s capabilities for multiple automated DNA assembly methods, including a new method for Isothermal Hierarchical DNA Construction, and for Escherichia coli and Saccharomyces cerevisiae transformation. The platform enables the automated control of cellular growth, gene expression induction, andmore » proteogenic and metabolic output analysis. Finally, taken together, we demonstrate the microfluidic platform’s potential to provide end-to-end solutions for synthetic biology research, from design to functional analysis.« less

End-to-end automated microfluidic platform for synthetic biology: from design to functional analysis

DOE PAGES

Linshiz, Gregory; Jensen, Erik; Stawski, Nina; ...

2016-02-02

Synthetic biology aims to engineer biological systems for desired behaviors. The construction of these systems can be complex, often requiring genetic reprogramming, extensive de novo DNA synthesis, and functional screening. Here, we present a programmable, multipurpose microfluidic platform and associated software and apply the platform to major steps of the synthetic biology research cycle: design, construction, testing, and analysis. We show the platform’s capabilities for multiple automated DNA assembly methods, including a new method for Isothermal Hierarchical DNA Construction, and for Escherichia coli and Saccharomyces cerevisiae transformation. The platform enables the automated control of cellular growth, gene expression induction, andmore » proteogenic and metabolic output analysis. Finally, taken together, we demonstrate the microfluidic platform’s potential to provide end-to-end solutions for synthetic biology research, from design to functional analysis.« less

NeuronMetrics: Software for Semi-Automated Processing of Cultured-Neuron Images

PubMed Central

Narro, Martha L.; Yang, Fan; Kraft, Robert; Wenk, Carola; Efrat, Alon; Restifo, Linda L.

2007-01-01

Using primary cell culture to screen for changes in neuronal morphology requires specialized analysis software. We developed NeuronMetrics™ for semi-automated, quantitative analysis of two-dimensional (2D) images of fluorescently labeled cultured neurons. It skeletonizes the neuron image using two complementary image-processing techniques, capturing fine terminal neurites with high fidelity. An algorithm was devised to span wide gaps in the skeleton. NeuronMetrics uses a novel strategy based on geometric features called faces to extract a branch-number estimate from complex arbors with numerous neurite-to-neurite contacts, without creating a precise, contact-free representation of the neurite arbor. It estimates total neurite length, branch number, primary neurite number, territory (the area of the convex polygon bounding the skeleton and cell body), and Polarity Index (a measure of neuronal polarity). These parameters provide fundamental information about the size and shape of neurite arbors, which are critical factors for neuronal function. NeuronMetrics streamlines optional manual tasks such as removing noise, isolating the largest primary neurite, and correcting length for self-fasciculating neurites. Numeric data are output in a single text file, readily imported into other applications for further analysis. Written as modules for ImageJ, NeuronMetrics provides practical analysis tools that are easy to use and support batch processing. Depending on the need for manual intervention, processing time for a batch of ~60 2D images is 1.0–2.5 hours, from a folder of images to a table of numeric data. NeuronMetrics’ output accelerates the quantitative detection of mutations and chemical compounds that alter neurite morphology in vitro, and will contribute to the use of cultured neurons for drug discovery. PMID:17270152

NeuronMetrics: software for semi-automated processing of cultured neuron images.

PubMed

Narro, Martha L; Yang, Fan; Kraft, Robert; Wenk, Carola; Efrat, Alon; Restifo, Linda L

2007-03-23

Using primary cell culture to screen for changes in neuronal morphology requires specialized analysis software. We developed NeuronMetrics for semi-automated, quantitative analysis of two-dimensional (2D) images of fluorescently labeled cultured neurons. It skeletonizes the neuron image using two complementary image-processing techniques, capturing fine terminal neurites with high fidelity. An algorithm was devised to span wide gaps in the skeleton. NeuronMetrics uses a novel strategy based on geometric features called faces to extract a branch number estimate from complex arbors with numerous neurite-to-neurite contacts, without creating a precise, contact-free representation of the neurite arbor. It estimates total neurite length, branch number, primary neurite number, territory (the area of the convex polygon bounding the skeleton and cell body), and Polarity Index (a measure of neuronal polarity). These parameters provide fundamental information about the size and shape of neurite arbors, which are critical factors for neuronal function. NeuronMetrics streamlines optional manual tasks such as removing noise, isolating the largest primary neurite, and correcting length for self-fasciculating neurites. Numeric data are output in a single text file, readily imported into other applications for further analysis. Written as modules for ImageJ, NeuronMetrics provides practical analysis tools that are easy to use and support batch processing. Depending on the need for manual intervention, processing time for a batch of approximately 60 2D images is 1.0-2.5 h, from a folder of images to a table of numeric data. NeuronMetrics' output accelerates the quantitative detection of mutations and chemical compounds that alter neurite morphology in vitro, and will contribute to the use of cultured neurons for drug discovery.

Vaccine adverse event text mining system for extracting features from vaccine safety reports.

PubMed

Botsis, Taxiarchis; Buttolph, Thomas; Nguyen, Michael D; Winiecki, Scott; Woo, Emily Jane; Ball, Robert

2012-01-01

To develop and evaluate a text mining system for extracting key clinical features from vaccine adverse event reporting system (VAERS) narratives to aid in the automated review of adverse event reports. Based upon clinical significance to VAERS reviewing physicians, we defined the primary (diagnosis and cause of death) and secondary features (eg, symptoms) for extraction. We built a novel vaccine adverse event text mining (VaeTM) system based on a semantic text mining strategy. The performance of VaeTM was evaluated using a total of 300 VAERS reports in three sequential evaluations of 100 reports each. Moreover, we evaluated the VaeTM contribution to case classification; an information retrieval-based approach was used for the identification of anaphylaxis cases in a set of reports and was compared with two other methods: a dedicated text classifier and an online tool. The performance metrics of VaeTM were text mining metrics: recall, precision and F-measure. We also conducted a qualitative difference analysis and calculated sensitivity and specificity for classification of anaphylaxis cases based on the above three approaches. VaeTM performed best in extracting diagnosis, second level diagnosis, drug, vaccine, and lot number features (lenient F-measure in the third evaluation: 0.897, 0.817, 0.858, 0.874, and 0.914, respectively). In terms of case classification, high sensitivity was achieved (83.1%); this was equal and better compared to the text classifier (83.1%) and the online tool (40.7%), respectively. Our VaeTM implementation of a semantic text mining strategy shows promise in providing accurate and efficient extraction of key features from VAERS narratives.

Text Mining in Biomedical Domain with Emphasis on Document Clustering.

PubMed

Renganathan, Vinaitheerthan

2017-07-01

With the exponential increase in the number of articles published every year in the biomedical domain, there is a need to build automated systems to extract unknown information from the articles published. Text mining techniques enable the extraction of unknown knowledge from unstructured documents. This paper reviews text mining processes in detail and the software tools available to carry out text mining. It also reviews the roles and applications of text mining in the biomedical domain. Text mining processes, such as search and retrieval of documents, pre-processing of documents, natural language processing, methods for text clustering, and methods for text classification are described in detail. Text mining techniques can facilitate the mining of vast amounts of knowledge on a given topic from published biomedical research articles and draw meaningful conclusions that are not possible otherwise.

First On-Site Data Analysis System for Subaru/Suprime-Cam

NASA Astrophysics Data System (ADS)

Furusawa, Hisanori; Okura, Yuki; Mineo, Sogo; Takata, Tadafumi; Nakata, Fumiaki; Tanaka, Manobu; Katayama, Nobuhiko; Itoh, Ryosuke; Yasuda, Naoki; Miyazaki, Satoshi; Komiyama, Yutaka; Utsumi, Yousuke; Uchida, Tomohisa; Aihara, Hiroaki

2011-03-01

We developed an automated on-site quick analysis system for mosaic CCD data of Suprime-Cam, which is a wide-field camera mounted at the prime focus of the Subaru Telescope, Mauna Kea, Hawaii. The first version of the data-analysis system was constructed, and started to operate in general observations. This system is a new function of observing support at the Subaru Telescope to provide the Subaru user community with an automated on-site data evaluation, aiming at improvements of observers' productivity, especially in large imaging surveys. The new system assists the data evaluation tasks in observations by the continuous monitoring of the characteristics of every data frame during observations. The evaluation results and data frames processed by this system are also useful for reducing the data-processing time in a full analysis after an observation. The primary analysis functions implemented in the data-analysis system are composed of automated realtime analysis for data evaluation and on-demand analysis, which is executed upon request, including mosaicing analysis and flat making analysis. In data evaluation, which is controlled by the organizing software, the database keeps track of the analysis histories, as well as the evaluated values of data frames, including seeing and sky background levels; it also helps in the selection of frames for mosaicing and flat making analysis. We examined the system performance and confirmed an improvement in the data-processing time by a factor of 9 with the aid of distributed parallel data processing and on-memory data processing, which makes the automated data evaluation effective.

Development of a plan for automating integrated circuit processing

NASA Technical Reports Server (NTRS)

1971-01-01

The operations analysis and equipment evaluations pertinent to the design of an automated production facility capable of manufacturing beam-lead CMOS integrated circuits are reported. The overall plan shows approximate cost of major equipment, production rate and performance capability, flexibility, and special maintenance requirements. Direct computer control is compared with supervisory-mode operations. The plan is limited to wafer processing operations from the starting wafer to the finished beam-lead die after separation etching. The work already accomplished in implementing various automation schemes, and the type of equipment which can be found for instant automation are described. The plan is general, so that small shops or large production units can perhaps benefit. Examples of major types of automated processing machines are shown to illustrate the general concepts of automated wafer processing.

Automated and connected vehicle implications and analysis.

DOT National Transportation Integrated Search

2017-05-01

Automated and connected vehicles (ACV) and, in particular, autonomous vehicles have captured : the interest of the public, industry and transportation authorities. ACVs can significantly reduce : accidents, fuel consumption, pollution and the costs o...

ROBOCAL: An automated NDA (nondestructive analysis) calorimetry and gamma isotopic system

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

Hurd, J.R.; Powell, W.D.; Ostenak, C.A.

1989-11-01

ROBOCAL, which is presently being developed and tested at Los Alamos National Laboratory, is a full-scale, prototype robotic system for remote calorimetric and gamma-ray analysis of special nuclear materials. It integrates a fully automated, multidrawer, vertical stacker-retriever system for staging unmeasured nuclear materials, and a fully automated gantry robot for computer-based selection and transfer of nuclear materials to calorimetric and gamma-ray measurement stations. Since ROBOCAL is designed for minimal operator intervention, a completely programmed user interface is provided to interact with the automated mechanical and assay systems. The assay system is designed to completely integrate calorimetric and gamma-ray data acquisitionmore » and to perform state-of-the-art analyses on both homogeneous and heterogeneous distributions of nuclear materials in a wide variety of matrices.« less

High-throughput sample processing and sample management; the functional evolution of classical cytogenetic assay towards automation.

PubMed

Ramakumar, Adarsh; Subramanian, Uma; Prasanna, Pataje G S

2015-11-01

High-throughput individual diagnostic dose assessment is essential for medical management of radiation-exposed subjects after a mass casualty. Cytogenetic assays such as the Dicentric Chromosome Assay (DCA) are recognized as the gold standard by international regulatory authorities. DCA is a multi-step and multi-day bioassay. DCA, as described in the IAEA manual, can be used to assess dose up to 4-6 weeks post-exposure quite accurately but throughput is still a major issue and automation is very essential. The throughput is limited, both in terms of sample preparation as well as analysis of chromosome aberrations. Thus, there is a need to design and develop novel solutions that could utilize extensive laboratory automation for sample preparation, and bioinformatics approaches for chromosome-aberration analysis to overcome throughput issues. We have transitioned the bench-based cytogenetic DCA to a coherent process performing high-throughput automated biodosimetry for individual dose assessment ensuring quality control (QC) and quality assurance (QA) aspects in accordance with international harmonized protocols. A Laboratory Information Management System (LIMS) is designed, implemented and adapted to manage increased sample processing capacity, develop and maintain standard operating procedures (SOP) for robotic instruments, avoid data transcription errors during processing, and automate analysis of chromosome-aberrations using an image analysis platform. Our efforts described in this paper intend to bridge the current technological gaps and enhance the potential application of DCA for a dose-based stratification of subjects following a mass casualty. This paper describes one such potential integrated automated laboratory system and functional evolution of the classical DCA towards increasing critically needed throughput. Published by Elsevier B.V.

The automated system for prevention of industrial-caused diseases

NASA Astrophysics Data System (ADS)

Varnavsky, A. N.

2017-01-01

The paper presents the automated system intended to prevent industrial-caused diseases of workers, the basis of which is represented by algorithms of preventing several negative functional conditions (stress, monotony). The emergence of such state shall be determined based on an analysis of bioelectric signals, in particular, skin-galvanic reactions. Proceeding from the dynamics of the functional state, the automated system offers to perform an optimized set of measures to restore the health of the worker. Implementation of an automated system is presented in Visual Programming system LabVIEW.

SHARP: Spacecraft Health Automated Reasoning Prototype

NASA Technical Reports Server (NTRS)

Atkinson, David J.

1991-01-01

The planetary spacecraft mission OPS as applied to SHARP is studied. Knowledge systems involved in this study are detailed. SHARP development task and Voyager telecom link analysis were examined. It was concluded that artificial intelligence has a proven capability to deliver useful functions in a real time space flight operations environment. SHARP has precipitated major change in acceptance of automation at JPL. The potential payoff from automation using AI is substantial. SHARP, and other AI technology is being transferred into systems in development including mission operations automation, science data systems, and infrastructure applications.

CFD Process Pre- and Post-processing Automation in Support of Space Propulsion

NASA Technical Reports Server (NTRS)

Dorney, Suzanne M.

2003-01-01

The use of Computational Fluid Dynamics or CFD has become standard practice in the design and analysis of the major components used for space propulsion. In an attempt to standardize and improve the CFD process a series of automated tools have been developed. Through the use of these automated tools the application of CFD to the design cycle has been improved and streamlined. This paper presents a series of applications in which deficiencies were identified in the CFD process and corrected through the development of automated tools.

Augmenting Qualitative Text Analysis with Natural Language Processing: Methodological Study.

PubMed

Guetterman, Timothy C; Chang, Tammy; DeJonckheere, Melissa; Basu, Tanmay; Scruggs, Elizabeth; Vydiswaran, V G Vinod

2018-06-29

Qualitative research methods are increasingly being used across disciplines because of their ability to help investigators understand the perspectives of participants in their own words. However, qualitative analysis is a laborious and resource-intensive process. To achieve depth, researchers are limited to smaller sample sizes when analyzing text data. One potential method to address this concern is natural language processing (NLP). Qualitative text analysis involves researchers reading data, assigning code labels, and iteratively developing findings; NLP has the potential to automate part of this process. Unfortunately, little methodological research has been done to compare automatic coding using NLP techniques and qualitative coding, which is critical to establish the viability of NLP as a useful, rigorous analysis procedure. The purpose of this study was to compare the utility of a traditional qualitative text analysis, an NLP analysis, and an augmented approach that combines qualitative and NLP methods. We conducted a 2-arm cross-over experiment to compare qualitative and NLP approaches to analyze data generated through 2 text (short message service) message survey questions, one about prescription drugs and the other about police interactions, sent to youth aged 14-24 years. We randomly assigned a question to each of the 2 experienced qualitative analysis teams for independent coding and analysis before receiving NLP results. A third team separately conducted NLP analysis of the same 2 questions. We examined the results of our analyses to compare (1) the similarity of findings derived, (2) the quality of inferences generated, and (3) the time spent in analysis. The qualitative-only analysis for the drug question (n=58) yielded 4 major findings, whereas the NLP analysis yielded 3 findings that missed contextual elements. The qualitative and NLP-augmented analysis was the most comprehensive. For the police question (n=68), the qualitative-only analysis yielded 4 primary findings and the NLP-only analysis yielded 4 slightly different findings. Again, the augmented qualitative and NLP analysis was the most comprehensive and produced the highest quality inferences, increasing our depth of understanding (ie, details and frequencies). In terms of time, the NLP-only approach was quicker than the qualitative-only approach for the drug (120 vs 270 minutes) and police (40 vs 270 minutes) questions. An approach beginning with qualitative analysis followed by qualitative- or NLP-augmented analysis took longer time than that beginning with NLP for both drug (450 vs 240 minutes) and police (390 vs 220 minutes) questions. NLP provides both a foundation to code qualitatively more quickly and a method to validate qualitative findings. NLP methods were able to identify major themes found with traditional qualitative analysis but were not useful in identifying nuances. Traditional qualitative text analysis added important details and context. ©Timothy C Guetterman, Tammy Chang, Melissa DeJonckheere, Tanmay Basu, Elizabeth Scruggs, VG Vinod Vydiswaran. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 29.06.2018.