Using workflows to explore and optimise named entity recognition for chemistry.

PubMed

Kolluru, Balakrishna; Hawizy, Lezan; Murray-Rust, Peter; Tsujii, Junichi; Ananiadou, Sophia

2011-01-01

Chemistry text mining tools should be interoperable and adaptable regardless of system-level implementation, installation or even programming issues. We aim to abstract the functionality of these tools from the underlying implementation via reconfigurable workflows for automatically identifying chemical names. To achieve this, we refactored an established named entity recogniser (in the chemistry domain), OSCAR and studied the impact of each component on the net performance. We developed two reconfigurable workflows from OSCAR using an interoperable text mining framework, U-Compare. These workflows can be altered using the drag-&-drop mechanism of the graphical user interface of U-Compare. These workflows also provide a platform to study the relationship between text mining components such as tokenisation and named entity recognition (using maximum entropy Markov model (MEMM) and pattern recognition based classifiers). Results indicate that, for chemistry in particular, eliminating noise generated by tokenisation techniques lead to a slightly better performance than others, in terms of named entity recognition (NER) accuracy. Poor tokenisation translates into poorer input to the classifier components which in turn leads to an increase in Type I or Type II errors, thus, lowering the overall performance. On the Sciborg corpus, the workflow based system, which uses a new tokeniser whilst retaining the same MEMM component, increases the F-score from 82.35% to 84.44%. On the PubMed corpus, it recorded an F-score of 84.84% as against 84.23% by OSCAR.

A method for named entity normalization in biomedical articles: application to diseases and plants.

PubMed

Cho, Hyejin; Choi, Wonjun; Lee, Hyunju

2017-10-13

In biomedical articles, a named entity recognition (NER) technique that identifies entity names from texts is an important element for extracting biological knowledge from articles. After NER is applied to articles, the next step is to normalize the identified names into standard concepts (i.e., disease names are mapped to the National Library of Medicine's Medical Subject Headings disease terms). In biomedical articles, many entity normalization methods rely on domain-specific dictionaries for resolving synonyms and abbreviations. However, the dictionaries are not comprehensive except for some entities such as genes. In recent years, biomedical articles have accumulated rapidly, and neural network-based algorithms that incorporate a large amount of unlabeled data have shown considerable success in several natural language processing problems. In this study, we propose an approach for normalizing biological entities, such as disease names and plant names, by using word embeddings to represent semantic spaces. For diseases, training data from the National Center for Biotechnology Information (NCBI) disease corpus and unlabeled data from PubMed abstracts were used to construct word representations. For plants, a training corpus that we manually constructed and unlabeled PubMed abstracts were used to represent word vectors. We showed that the proposed approach performed better than the use of only the training corpus or only the unlabeled data and showed that the normalization accuracy was improved by using our model even when the dictionaries were not comprehensive. We obtained F-scores of 0.808 and 0.690 for normalizing the NCBI disease corpus and manually constructed plant corpus, respectively. We further evaluated our approach using a data set in the disease normalization task of the BioCreative V challenge. When only the disease corpus was used as a dictionary, our approach significantly outperformed the best system of the task. The proposed approach shows robust

Active learning for ontological event extraction incorporating named entity recognition and unknown word handling.

PubMed

Han, Xu; Kim, Jung-jae; Kwoh, Chee Keong

2016-01-01

Biomedical text mining may target various kinds of valuable information embedded in the literature, but a critical obstacle to the extension of the mining targets is the cost of manual construction of labeled data, which are required for state-of-the-art supervised learning systems. Active learning is to choose the most informative documents for the supervised learning in order to reduce the amount of required manual annotations. Previous works of active learning, however, focused on the tasks of entity recognition and protein-protein interactions, but not on event extraction tasks for multiple event types. They also did not consider the evidence of event participants, which might be a clue for the presence of events in unlabeled documents. Moreover, the confidence scores of events produced by event extraction systems are not reliable for ranking documents in terms of informativity for supervised learning. We here propose a novel committee-based active learning method that supports multi-event extraction tasks and employs a new statistical method for informativity estimation instead of using the confidence scores from event extraction systems. Our method is based on a committee of two systems as follows: We first employ an event extraction system to filter potential false negatives among unlabeled documents, from which the system does not extract any event. We then develop a statistical method to rank the potential false negatives of unlabeled documents 1) by using a language model that measures the probabilities of the expression of multiple events in documents and 2) by using a named entity recognition system that locates the named entities that can be event arguments (e.g. proteins). The proposed method further deals with unknown words in test data by using word similarity measures. We also apply our active learning method for the task of named entity recognition. We evaluate the proposed method against the BioNLP Shared Tasks datasets, and show that our method

Discovery of Predicate-Oriented Relations among Named Entities Extracted from Thai Texts

NASA Astrophysics Data System (ADS)

Tongtep, Nattapong; Theeramunkong, Thanaruk

Extracting named entities (NEs) and their relations is more difficult in Thai than in other languages due to several Thai specific characteristics, including no explicit boundaries for words, phrases and sentences; few case markers and modifier clues; high ambiguity in compound words and serial verbs; and flexible word orders. Unlike most previous works which focused on NE relations of specific actions, such as work_for, live_in, located_in, and kill, this paper proposes more general types of NE relations, called predicate-oriented relation (PoR), where an extracted action part (verb) is used as a core component to associate related named entities extracted from Thai Texts. Lacking a practical parser for the Thai language, we present three types of surface features, i.e. punctuation marks (such as token spaces), entity types and the number of entities and then apply five alternative commonly used learning schemes to investigate their performance on predicate-oriented relation extraction. The experimental results show that our approach achieves the F-measure of 97.76%, 99.19%, 95.00% and 93.50% on four different types of predicate-oriented relation (action-location, location-action, action-person and person-action) in crime-related news documents using a data set of 1,736 entity pairs. The effects of NE extraction techniques, feature sets and class unbalance on the performance of relation extraction are explored.

Clinical Named Entity Recognition Using Deep Learning Models.

PubMed

Wu, Yonghui; Jiang, Min; Xu, Jun; Zhi, Degui; Xu, Hua

2017-01-01

Clinical Named Entity Recognition (NER) is a critical natural language processing (NLP) task to extract important concepts (named entities) from clinical narratives. Researchers have extensively investigated machine learning models for clinical NER. Recently, there have been increasing efforts to apply deep learning models to improve the performance of current clinical NER systems. This study examined two popular deep learning architectures, the Convolutional Neural Network (CNN) and the Recurrent Neural Network (RNN), to extract concepts from clinical texts. We compared the two deep neural network architectures with three baseline Conditional Random Fields (CRFs) models and two state-of-the-art clinical NER systems using the i2b2 2010 clinical concept extraction corpus. The evaluation results showed that the RNN model trained with the word embeddings achieved a new state-of-the- art performance (a strict F1 score of 85.94%) for the defined clinical NER task, outperforming the best-reported system that used both manually defined and unsupervised learning features. This study demonstrates the advantage of using deep neural network architectures for clinical concept extraction, including distributed feature representation, automatic feature learning, and long-term dependencies capture. This is one of the first studies to compare the two widely used deep learning models and demonstrate the superior performance of the RNN model for clinical NER.

Clinical Named Entity Recognition Using Deep Learning Models

PubMed Central

Wu, Yonghui; Jiang, Min; Xu, Jun; Zhi, Degui; Xu, Hua

2017-01-01

Clinical Named Entity Recognition (NER) is a critical natural language processing (NLP) task to extract important concepts (named entities) from clinical narratives. Researchers have extensively investigated machine learning models for clinical NER. Recently, there have been increasing efforts to apply deep learning models to improve the performance of current clinical NER systems. This study examined two popular deep learning architectures, the Convolutional Neural Network (CNN) and the Recurrent Neural Network (RNN), to extract concepts from clinical texts. We compared the two deep neural network architectures with three baseline Conditional Random Fields (CRFs) models and two state-of-the-art clinical NER systems using the i2b2 2010 clinical concept extraction corpus. The evaluation results showed that the RNN model trained with the word embeddings achieved a new state-of-the- art performance (a strict F1 score of 85.94%) for the defined clinical NER task, outperforming the best-reported system that used both manually defined and unsupervised learning features. This study demonstrates the advantage of using deep neural network architectures for clinical concept extraction, including distributed feature representation, automatic feature learning, and long-term dependencies capture. This is one of the first studies to compare the two widely used deep learning models and demonstrate the superior performance of the RNN model for clinical NER. PMID:29854252

Deep learning with word embeddings improves biomedical named entity recognition

PubMed Central

Habibi, Maryam; Weber, Leon; Neves, Mariana; Wiegandt, David Luis; Leser, Ulf

2017-01-01

Abstract Motivation: Text mining has become an important tool for biomedical research. The most fundamental text-mining task is the recognition of biomedical named entities (NER), such as genes, chemicals and diseases. Current NER methods rely on pre-defined features which try to capture the specific surface properties of entity types, properties of the typical local context, background knowledge, and linguistic information. State-of-the-art tools are entity-specific, as dictionaries and empirically optimal feature sets differ between entity types, which makes their development costly. Furthermore, features are often optimized for a specific gold standard corpus, which makes extrapolation of quality measures difficult. Results: We show that a completely generic method based on deep learning and statistical word embeddings [called long short-term memory network-conditional random field (LSTM-CRF)] outperforms state-of-the-art entity-specific NER tools, and often by a large margin. To this end, we compared the performance of LSTM-CRF on 33 data sets covering five different entity classes with that of best-of-class NER tools and an entity-agnostic CRF implementation. On average, F1-score of LSTM-CRF is 5% above that of the baselines, mostly due to a sharp increase in recall. Availability and implementation: The source code for LSTM-CRF is available at https://github.com/glample/tagger and the links to the corpora are available at https://corposaurus.github.io/corpora/. Contact: habibima@informatik.hu-berlin.de PMID:28881963

Segregation of anterior temporal regions critical for retrieving names of unique and nonunique entities reflects underlying long-range connectivity

PubMed Central

Mehta, Sonya; Inoue, Kayo; Rudrauf, David; Damasio, Hanna; Tranel, Daniel; Grabowski, Thomas

2015-01-01

Lesion-deficit studies support the hypothesis that the left anterior temporal lobe (ATL) plays a critical role in retrieving names of concrete entities. They further suggest that different regions of the left ATL process different conceptual categories. Here we test the specificity of these relationships and whether the anatomical segregation is related to the underlying organization of white matter connections. We reanalyzed data from a previous lesion study of naming and recognition across five categories of concrete entities. In voxelwise logistic regressions of lesion-deficit associations, we formally incorporated measures of disconnection of long-range association fiber tracts (FTs) and covaried for recognition and non-category specific naming deficits. We also performed fiber tractwise analyses to assess whether damage to specific FTs was preferentially associated with category-selective naming deficits. Damage to the basolateral ATL was associated with naming deficits for both unique (famous faces) and non-unique entities, whereas the damage to the temporal pole was associated with naming deficits for unique entities only. This segregation pattern remained after accounting for comorbid recognition deficits or naming deficits in other categories. The tractwise analyses showed that damage to the uncinate fasciculus was associated with naming impairments for unique entities, while damage to the inferior longitudinal fasciculus was associated with naming impairments for non-unique entities. Covarying for FT transection in voxelwise analyses rendered the cortical association for unique entities more focal. These results are consistent with the partial segregation of brain system support for name retrieval of unique and non-unique entities at both the level of cortical components and underlying white matter fiber bundles. Our study reconciles theoretic accounts of the functional organization of the left ATL by revealing both category-related processing and

Deep learning with word embeddings improves biomedical named entity recognition.

PubMed

Habibi, Maryam; Weber, Leon; Neves, Mariana; Wiegandt, David Luis; Leser, Ulf

2017-07-15

Text mining has become an important tool for biomedical research. The most fundamental text-mining task is the recognition of biomedical named entities (NER), such as genes, chemicals and diseases. Current NER methods rely on pre-defined features which try to capture the specific surface properties of entity types, properties of the typical local context, background knowledge, and linguistic information. State-of-the-art tools are entity-specific, as dictionaries and empirically optimal feature sets differ between entity types, which makes their development costly. Furthermore, features are often optimized for a specific gold standard corpus, which makes extrapolation of quality measures difficult. We show that a completely generic method based on deep learning and statistical word embeddings [called long short-term memory network-conditional random field (LSTM-CRF)] outperforms state-of-the-art entity-specific NER tools, and often by a large margin. To this end, we compared the performance of LSTM-CRF on 33 data sets covering five different entity classes with that of best-of-class NER tools and an entity-agnostic CRF implementation. On average, F1-score of LSTM-CRF is 5% above that of the baselines, mostly due to a sharp increase in recall. The source code for LSTM-CRF is available at https://github.com/glample/tagger and the links to the corpora are available at https://corposaurus.github.io/corpora/ . habibima@informatik.hu-berlin.de. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Segregation of anterior temporal regions critical for retrieving names of unique and non-unique entities reflects underlying long-range connectivity.

PubMed

Mehta, Sonya; Inoue, Kayo; Rudrauf, David; Damasio, Hanna; Tranel, Daniel; Grabowski, Thomas

2016-02-01

Lesion-deficit studies support the hypothesis that the left anterior temporal lobe (ATL) plays a critical role in retrieving names of concrete entities. They further suggest that different regions of the left ATL process different conceptual categories. Here we test the specificity of these relationships and whether the anatomical segregation is related to the underlying organization of white matter connections. We reanalyzed data from a previous lesion study of naming and recognition across five categories of concrete entities. In voxelwise logistic regressions of lesion-deficit associations, we formally incorporated measures of disconnection of long-range association fiber tracts (FTs) and covaried for recognition and non-category-specific naming deficits. We also performed fiber tractwise analyses to assess whether damage to specific FTs was preferentially associated with category-selective naming deficits. Damage to the basolateral ATL was associated with naming deficits for both unique (famous faces) and non-unique entities, whereas the damage to the temporal pole was associated with naming deficits for unique entities only. This segregation pattern remained after accounting for comorbid recognition deficits or naming deficits in other categories. The tractwise analyses showed that damage to the uncinate fasciculus (UNC) was associated with naming impairments for unique entities, while damage to the inferior longitudinal fasciculus (ILF) was associated with naming impairments for non-unique entities. Covarying for FT transection in voxelwise analyses rendered the cortical association for unique entities more focal. These results are consistent with the partial segregation of brain system support for name retrieval of unique and non-unique entities at both the level of cortical components and underlying white matter fiber bundles. Our study reconciles theoretic accounts of the functional organization of the left ATL by revealing both category-related processing

Novel high/low solubility classification methods for new molecular entities.

PubMed

Dave, Rutwij A; Morris, Marilyn E

2016-09-10

This research describes a rapid solubility classification approach that could be used in the discovery and development of new molecular entities. Compounds (N=635) were divided into two groups based on information available in the literature: high solubility (BDDCS/BCS 1/3) and low solubility (BDDCS/BCS 2/4). We established decision rules for determining solubility classes using measured log solubility in molar units (MLogSM) or measured solubility (MSol) in mg/ml units. ROC curve analysis was applied to determine statistically significant threshold values of MSol and MLogSM. Results indicated that NMEs with MLogSM>-3.05 or MSol>0.30mg/mL will have ≥85% probability of being highly soluble and new molecular entities with MLogSM≤-3.05 or MSol≤0.30mg/mL will have ≥85% probability of being poorly soluble. When comparing solubility classification using the threshold values of MLogSM or MSol with BDDCS, we were able to correctly classify 85% of compounds. We also evaluated solubility classification of an independent set of 108 orally administered drugs using MSol (0.3mg/mL) and our method correctly classified 81% and 95% of compounds into high and low solubility classes, respectively. The high/low solubility classification using MLogSM or MSol is novel and independent of traditionally used dose number criteria. Copyright © 2016 Elsevier B.V. All rights reserved.

Naming unique entities in the semantic variant of primary progressive aphasia and Alzheimer's disease: Towards a better understanding of the semantic impairment.

PubMed

Montembeault, M; Brambati, S M; Joubert, S; Boukadi, M; Chapleau, M; Laforce, R Jr; Wilson, M A; Macoir, J; Rouleau, I

2017-01-27

While the semantic variant of primary progressive aphasia (svPPA) is characterized by a predominant semantic memory impairment, episodic memory impairments are the clinical hallmark of Alzheimer's disease (AD). However, AD patients also present with semantic deficits, which are more severe for semantically unique entities (e.g. a famous person) than for common concepts (e.g. a beaver). Previous studies in these patient populations have largely focused on famous-person naming. Therefore, we aimed to evaluate if these impairments also extend to other semantically unique entities such as famous places and famous logos. In this study, 13 AD patients, 9 svPPA patients, and 12 cognitively unimpaired elderly subjects (CTRL) were tested with a picture-naming test of non-unique entities (Boston Naming Test) and three experimental tests of semantically unique entities assessing naming of famous persons, places, and logos. Both clinical groups were overall more impaired at naming semantically unique entities than non-unique entities. Naming impairments in AD and svPPA extended to the other types of semantically unique entities, since a CTRL>AD>svPPA pattern was found on the performance of all naming tests. Naming famous places and famous persons appeared to be most impaired in svPPA, and both specific and general semantic knowledge for these entities were affected in these patients. Although AD patients were most significantly impaired on famous-person naming, only their specific semantic knowledge was impaired, while general knowledge was preserved. Post-hoc neuroimaging analyses also showed that famous-person naming impairments in AD correlated with atrophy in the temporo-parietal junction, a region functionally associated with lexical access. In line with previous studies, svPPA patients' impairment in both naming and semantic knowledge suggest a more profound semantic impairment, while naming impairments in AD may arise to a greater extent from impaired lexical access

Assessment of disease named entity recognition on a corpus of annotated sentences.

PubMed

Jimeno, Antonio; Jimenez-Ruiz, Ernesto; Lee, Vivian; Gaudan, Sylvain; Berlanga, Rafael; Rebholz-Schuhmann, Dietrich

2008-04-11

In recent years, the recognition of semantic types from the biomedical scientific literature has been focused on named entities like protein and gene names (PGNs) and gene ontology terms (GO terms). Other semantic types like diseases have not received the same level of attention. Different solutions have been proposed to identify disease named entities in the scientific literature. While matching the terminology with language patterns suffers from low recall (e.g., Whatizit) other solutions make use of morpho-syntactic features to better cover the full scope of terminological variability (e.g., MetaMap). Currently, MetaMap that is provided from the National Library of Medicine (NLM) is the state of the art solution for the annotation of concepts from UMLS (Unified Medical Language System) in the literature. Nonetheless, its performance has not yet been assessed on an annotated corpus. In addition, little effort has been invested so far to generate an annotated dataset that links disease entities in text to disease entries in a database, thesaurus or ontology and that could serve as a gold standard to benchmark text mining solutions. As part of our research work, we have taken a corpus that has been delivered in the past for the identification of associations of genes to diseases based on the UMLS Metathesaurus and we have reprocessed and re-annotated the corpus. We have gathered annotations for disease entities from two curators, analyzed their disagreement (0.51 in the kappa-statistic) and composed a single annotated corpus for public use. Thereafter, three solutions for disease named entity recognition including MetaMap have been applied to the corpus to automatically annotate it with UMLS Metathesaurus concepts. The resulting annotations have been benchmarked to compare their performance. The annotated corpus is publicly available at ftp://ftp.ebi.ac.uk/pub/software/textmining/corpora/diseases and can serve as a benchmark to other systems. In addition, we found

Named Entity Recognition in Chinese Clinical Text Using Deep Neural Network.

PubMed

Wu, Yonghui; Jiang, Min; Lei, Jianbo; Xu, Hua

2015-01-01

Rapid growth in electronic health records (EHRs) use has led to an unprecedented expansion of available clinical data in electronic formats. However, much of the important healthcare information is locked in the narrative documents. Therefore Natural Language Processing (NLP) technologies, e.g., Named Entity Recognition that identifies boundaries and types of entities, has been extensively studied to unlock important clinical information in free text. In this study, we investigated a novel deep learning method to recognize clinical entities in Chinese clinical documents using the minimal feature engineering approach. We developed a deep neural network (DNN) to generate word embeddings from a large unlabeled corpus through unsupervised learning and another DNN for the NER task. The experiment results showed that the DNN with word embeddings trained from the large unlabeled corpus outperformed the state-of-the-art CRF's model in the minimal feature engineering setting, achieving the highest F1-score of 0.9280. Further analysis showed that word embeddings derived through unsupervised learning from large unlabeled corpus remarkably improved the DNN with randomized embedding, denoting the usefulness of unsupervised feature learning.

Network analysis of named entity co-occurrences in written texts

NASA Astrophysics Data System (ADS)

Amancio, Diego Raphael

2016-06-01

The use of methods borrowed from statistics and physics to analyze written texts has allowed the discovery of unprecedent patterns of human behavior and cognition by establishing links between models features and language structure. While current models have been useful to unveil patterns via analysis of syntactical and semantical networks, only a few works have probed the relevance of investigating the structure arising from the relationship between relevant entities such as characters, locations and organizations. In this study, we represent entities appearing in the same context as a co-occurrence network, where links are established according to a null model based on random, shuffled texts. Computational simulations performed in novels revealed that the proposed model displays interesting topological features, such as the small world feature, characterized by high values of clustering coefficient. The effectiveness of our model was verified in a practical pattern recognition task in real networks. When compared with traditional word adjacency networks, our model displayed optimized results in identifying unknown references in texts. Because the proposed representation plays a complementary role in characterizing unstructured documents via topological analysis of named entities, we believe that it could be useful to improve the characterization of written texts (and related systems), specially if combined with traditional approaches based on statistical and deeper paradigms.

A proposal for classification of entities combining vascular malformations and deregulated growth.

PubMed

Oduber, Charlène E U; van der Horst, Chantal M A M; Sillevis Smitt, J Henk; Smeulders, Mark J C; Mendiratta, Vibhu; Harper, John I; van Steensel, Maurice A M; Hennekam, Raoul C M

2011-01-01

Agreement on terminology and nomenclature is fundamental and essential for effective exchange of information between clinicians and researchers. An adequate terminology to describe all patients showing vascular malformations combined with deregulated growth is at present not available. To propose a classification of patients with vascular malformations, not restricted to the face, and growth disturbances based on simple, clinically visible characteristics, on which clinicians and researchers can comment and which should eventually lead to an internationally accepted classification. Rooted in our joint experience we established a classification of vascular malformation not limited to the face, with growth disturbances. It is based on the nature and localization of the vascular malformations; the nature, localization and timing of growth disturbances; the nature of co-localization of the vascular malformations and growth disturbances; the presence or absence of other features. Subsequently a mixed (experienced and non-experienced) group of observers evaluated 146 patients (106 from the Netherlands; 40 from the UK) with vascular malformations and disturbed growth, using the classification. Inter-observer variability was assessed by estimating the Intra-Class Correlation (ICC) coefficient and its 95% confidence interval. We defined 6 subgroups within the group of entities with vascular malformation-deregulated growth. Scoring the patients using the proposed classification yielded a high inter-observer reproducibility (ICC varying between 0.747 and 0.895 for all levels of flow). The presently proposed classification was found to be reliable and easy to use for patients with vascular malformations with growth disturbances. We invite both clinicians and researchers to comment on the classification, in order to improve it further. This way we may obtain our final aim of an internationally accepted classification of patients, which should facilitate both clinical treatment

Transfer learning for biomedical named entity recognition with neural networks.

PubMed

Giorgi, John M; Bader, Gary D

2018-06-01

The explosive increase of biomedical literature has made information extraction an increasingly important tool for biomedical research. A fundamental task is the recognition of biomedical named entities in text (BNER) such as genes/proteins, diseases, and species. Recently, a domain-independent method based on deep learning and statistical word embeddings, called long short-term memory network-conditional random field (LSTM-CRF), has been shown to outperform state-of-the-art entity-specific BNER tools. However, this method is dependent on gold-standard corpora (GSCs) consisting of hand-labeled entities, which tend to be small but highly reliable. An alternative to GSCs are silver-standard corpora (SSCs), which are generated by harmonizing the annotations made by several automatic annotation systems. SSCs typically contain more noise than GSCs but have the advantage of containing many more training examples. Ideally, these corpora could be combined to achieve the benefits of both, which is an opportunity for transfer learning. In this work, we analyze to what extent transfer learning improves upon state-of-the-art results for BNER. We demonstrate that transferring a deep neural network (DNN) trained on a large, noisy SSC to a smaller, but more reliable GSC significantly improves upon state-of-the-art results for BNER. Compared to a state-of-the-art baseline evaluated on 23 GSCs covering four different entity classes, transfer learning results in an average reduction in error of approximately 11%. We found transfer learning to be especially beneficial for target data sets with a small number of labels (approximately 6000 or less). Source code for the LSTM-CRF is available athttps://github.com/Franck-Dernoncourt/NeuroNER/ and links to the corpora are available athttps://github.com/BaderLab/Transfer-Learning-BNER-Bioinformatics-2018/. john.giorgi@utoronto.ca. Supplementary data are available at Bioinformatics online.

New tumour entities in the 4th edition of the World Health Organization Classification of Head and Neck tumours: odontogenic and maxillofacial bone tumours.

PubMed

Speight, Paul M; Takata, Takashi

2018-03-01

The latest (4th) edition of the World Health Organization Classification of Head and Neck tumours has recently been published with a number of significant changes across all tumour sites. In particular, there has been a major attempt to simplify classifications and to use defining criteria which can be used globally in all situations, avoiding wherever possible the use of complex molecular techniques which may not be affordable or widely available. This review summarises the changes in Chapter 8: Odontogenic and maxillofacial bone lesions. The most significant change is the re-introduction of the classification of the odontogenic cysts, restoring this books status as the only text which classifies and defines the full range of lesions of the odontogenic tissues. The consensus group considered carefully the terminology of lesions and were concerned to ensure that the names used properly reflected the best evidence regarding the true nature of specific entities. For this reason, this new edition restores the odontogenic keratocyst and calcifying odontogenic cyst to the classification of odontogenic cysts and rejects the previous terminology (keratocystic odontogenic tumour and calcifying cystic odontogenic tumour) which were intended to suggest that they are true neoplasms. New entities which have been introduced include the sclerosing odontogenic carcinoma and primordial odontogenic tumour. In addition, some previously poorly defined lesions have been removed, including the ameloblastic fibrodentinoma, ameloblastic fibro-odontoma, which are probably developing odontomas, and the odontoameloblastoma, which is not regarded as an entity. Finally, the terminology "cemento" has been restored to cemento-ossifying fibroma and cemento-osseous dysplasias, to properly reflect that they are of odontogenic origin and are found in the tooth-bearing areas of the jaws.

TaggerOne: joint named entity recognition and normalization with semi-Markov Models

PubMed Central

Leaman, Robert; Lu, Zhiyong

2016-01-01

Motivation: Text mining is increasingly used to manage the accelerating pace of the biomedical literature. Many text mining applications depend on accurate named entity recognition (NER) and normalization (grounding). While high performing machine learning methods trainable for many entity types exist for NER, normalization methods are usually specialized to a single entity type. NER and normalization systems are also typically used in a serial pipeline, causing cascading errors and limiting the ability of the NER system to directly exploit the lexical information provided by the normalization. Methods: We propose the first machine learning model for joint NER and normalization during both training and prediction. The model is trainable for arbitrary entity types and consists of a semi-Markov structured linear classifier, with a rich feature approach for NER and supervised semantic indexing for normalization. We also introduce TaggerOne, a Java implementation of our model as a general toolkit for joint NER and normalization. TaggerOne is not specific to any entity type, requiring only annotated training data and a corresponding lexicon, and has been optimized for high throughput. Results: We validated TaggerOne with multiple gold-standard corpora containing both mention- and concept-level annotations. Benchmarking results show that TaggerOne achieves high performance on diseases (NCBI Disease corpus, NER f-score: 0.829, normalization f-score: 0.807) and chemicals (BioCreative 5 CDR corpus, NER f-score: 0.914, normalization f-score 0.895). These results compare favorably to the previous state of the art, notwithstanding the greater flexibility of the model. We conclude that jointly modeling NER and normalization greatly improves performance. Availability and Implementation: The TaggerOne source code and an online demonstration are available at: http://www.ncbi.nlm.nih.gov/bionlp/taggerone Contact: zhiyong.lu@nih.gov Supplementary information: Supplementary data are

Tremor entities and their classification: an update.

PubMed

Gövert, Felix; Deuschl, Günther

2015-08-01

This review focuses on important new findings in the field of tremor and illustrates the consequences for the current definition and classification of tremor. Since 1998 when the consensus criteria for tremor were proposed, new variants of tremors and new diagnostic methods were discovered that have changed particularly the concepts of essential tremor and dystonic tremor. Accumulating evidence exists that essential tremor is not a single entity rather different conditions that share the common symptom action tremor without other major abnormalities. Tremor is a common feature in patients with adult-onset focal dystonia and may involve several different body parts and forms of tremor. Recent advances, in particular, in the field of genetics, suggest that dystonic tremor may even be present without overt dystonia. Monosymptomatic asymmetric rest and postural tremor has been further delineated, and apart from tremor-dominant Parkinson's disease, there are several rare conditions including rest and action tremor with normal dopamine transporter imaging (scans without evidence of dopaminergic deficit) and essential tremor with tremor at rest. Increasing knowledge in the last decades changed the view on tremors and highlights several caveats in the current tremor classification. Given the ambiguous assignment between tremor phenomenology and tremor etiology, a more cautious definition of tremors on the basis of clinical assessment data is needed.

An attention-based BiLSTM-CRF approach to document-level chemical named entity recognition.

PubMed

Luo, Ling; Yang, Zhihao; Yang, Pei; Zhang, Yin; Wang, Lei; Lin, Hongfei; Wang, Jian

2018-04-15

In biomedical research, chemical is an important class of entities, and chemical named entity recognition (NER) is an important task in the field of biomedical information extraction. However, most popular chemical NER methods are based on traditional machine learning and their performances are heavily dependent on the feature engineering. Moreover, these methods are sentence-level ones which have the tagging inconsistency problem. In this paper, we propose a neural network approach, i.e. attention-based bidirectional Long Short-Term Memory with a conditional random field layer (Att-BiLSTM-CRF), to document-level chemical NER. The approach leverages document-level global information obtained by attention mechanism to enforce tagging consistency across multiple instances of the same token in a document. It achieves better performances with little feature engineering than other state-of-the-art methods on the BioCreative IV chemical compound and drug name recognition (CHEMDNER) corpus and the BioCreative V chemical-disease relation (CDR) task corpus (the F-scores of 91.14 and 92.57%, respectively). Data and code are available at https://github.com/lingluodlut/Att-ChemdNER. yangzh@dlut.edu.cn or wangleibihami@gmail.com. Supplementary data are available at Bioinformatics online.

TaggerOne: joint named entity recognition and normalization with semi-Markov Models.

PubMed

Leaman, Robert; Lu, Zhiyong

2016-09-15

Text mining is increasingly used to manage the accelerating pace of the biomedical literature. Many text mining applications depend on accurate named entity recognition (NER) and normalization (grounding). While high performing machine learning methods trainable for many entity types exist for NER, normalization methods are usually specialized to a single entity type. NER and normalization systems are also typically used in a serial pipeline, causing cascading errors and limiting the ability of the NER system to directly exploit the lexical information provided by the normalization. We propose the first machine learning model for joint NER and normalization during both training and prediction. The model is trainable for arbitrary entity types and consists of a semi-Markov structured linear classifier, with a rich feature approach for NER and supervised semantic indexing for normalization. We also introduce TaggerOne, a Java implementation of our model as a general toolkit for joint NER and normalization. TaggerOne is not specific to any entity type, requiring only annotated training data and a corresponding lexicon, and has been optimized for high throughput. We validated TaggerOne with multiple gold-standard corpora containing both mention- and concept-level annotations. Benchmarking results show that TaggerOne achieves high performance on diseases (NCBI Disease corpus, NER f-score: 0.829, normalization f-score: 0.807) and chemicals (BioCreative 5 CDR corpus, NER f-score: 0.914, normalization f-score 0.895). These results compare favorably to the previous state of the art, notwithstanding the greater flexibility of the model. We conclude that jointly modeling NER and normalization greatly improves performance. The TaggerOne source code and an online demonstration are available at: http://www.ncbi.nlm.nih.gov/bionlp/taggerone zhiyong.lu@nih.gov Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2016. This work is written

A System for Identifying Named Entities in Biomedical Text: how Results From two Evaluations Reflect on Both the System and the Evaluations

PubMed Central

Dingare, Shipra; Nissim, Malvina; Finkel, Jenny; Grover, Claire

2005-01-01

We present a maximum entropy-based system for identifying named entities (NEs) in biomedical abstracts and present its performance in the only two biomedical named entity recognition (NER) comparative evaluations that have been held to date, namely BioCreative and Coling BioNLP. Our system obtained an exact match F-score of 83.2% in the BioCreative evaluation and 70.1% in the BioNLP evaluation. We discuss our system in detail, including its rich use of local features, attention to correct boundary identification, innovative use of external knowledge resources, including parsing and web searches, and rapid adaptation to new NE sets. We also discuss in depth problems with data annotation in the evaluations which caused the final performance to be lower than optimal. PMID:18629295

A rule-based named-entity recognition method for knowledge extraction of evidence-based dietary recommendations

PubMed Central

2017-01-01

Evidence-based dietary information represented as unstructured text is a crucial information that needs to be accessed in order to help dietitians follow the new knowledge arrives daily with newly published scientific reports. Different named-entity recognition (NER) methods have been introduced previously to extract useful information from the biomedical literature. They are focused on, for example extracting gene mentions, proteins mentions, relationships between genes and proteins, chemical concepts and relationships between drugs and diseases. In this paper, we present a novel NER method, called drNER, for knowledge extraction of evidence-based dietary information. To the best of our knowledge this is the first attempt at extracting dietary concepts. DrNER is a rule-based NER that consists of two phases. The first one involves the detection and determination of the entities mention, and the second one involves the selection and extraction of the entities. We evaluate the method by using text corpora from heterogeneous sources, including text from several scientifically validated web sites and text from scientific publications. Evaluation of the method showed that drNER gives good results and can be used for knowledge extraction of evidence-based dietary recommendations. PMID:28644863

New tumor entities in the 4th edition of the World Health Organization classification of head and neck tumors: Nasal cavity, paranasal sinuses and skull base.

PubMed

Thompson, Lester D R; Franchi, Alessandro

2018-03-01

The World Health Organization recently published the 4th edition of the Classification of Head and Neck Tumors, including several new entities, emerging entities, and significant updates to the classification and characterization of tumor and tumor-like lesions, specifically as it relates to nasal cavity, paranasal sinuses, and skull base in this overview. Of note, three new entities (NUT carcinoma, seromucinous hamartoma, biphenotypic sinonasal sarcoma,) were added to this section, while emerging entities (SMARCB1-deficient carcinoma and HPV-related carcinoma with adenoid cystic-like features) and several tumor-like entities (respiratory epithelial adenomatoid hamartoma, chondromesenchymal hamartoma) were included as provisional diagnoses or discussed in the setting of the differential diagnosis. The sinonasal tract houses a significant diversity of entities, but interestingly, the total number of entities has been significantly reduced by excluding tumor types if they did not occur exclusively or predominantly at this site or if they are discussed in detail elsewhere in the book. Refinements to nomenclature and criteria were provided to sinonasal papilloma, borderline soft tissue tumors, and neuroendocrine neoplasms. Overall, the new WHO classification reflects the state of current understanding for many relatively rare neoplasms, with this article highlighting the most significant changes.

Mining heart disease risk factors in clinical text with named entity recognition and distributional semantic models.

PubMed

Urbain, Jay

2015-12-01

We present the design, and analyze the performance of a multi-stage natural language processing system employing named entity recognition, Bayesian statistics, and rule logic to identify and characterize heart disease risk factor events in diabetic patients over time. The system was originally developed for the 2014 i2b2 Challenges in Natural Language in Clinical Data. The system's strengths included a high level of accuracy for identifying named entities associated with heart disease risk factor events. The system's primary weakness was due to inaccuracies when characterizing the attributes of some events. For example, determining the relative time of an event with respect to the record date, whether an event is attributable to the patient's history or the patient's family history, and differentiating between current and prior smoking status. We believe these inaccuracies were due in large part to the lack of an effective approach for integrating context into our event detection model. To address these inaccuracies, we explore the addition of a distributional semantic model for characterizing contextual evidence of heart disease risk factor events. Using this semantic model, we raise our initial 2014 i2b2 Challenges in Natural Language of Clinical data F1 score of 0.838 to 0.890 and increased precision by 10.3% without use of any lexicons that might bias our results. Copyright © 2015 Elsevier Inc. All rights reserved.

NERBio: using selected word conjunctions, term normalization, and global patterns to improve biomedical named entity recognition.

PubMed

Tsai, Richard Tzong-Han; Sung, Cheng-Lung; Dai, Hong-Jie; Hung, Hsieh-Chuan; Sung, Ting-Yi; Hsu, Wen-Lian

2006-12-18

Biomedical named entity recognition (Bio-NER) is a challenging problem because, in general, biomedical named entities of the same category (e.g., proteins and genes) do not follow one standard nomenclature. They have many irregularities and sometimes appear in ambiguous contexts. In recent years, machine-learning (ML) approaches have become increasingly common and now represent the cutting edge of Bio-NER technology. This paper addresses three problems faced by ML-based Bio-NER systems. First, most ML approaches usually employ singleton features that comprise one linguistic property (e.g., the current word is capitalized) and at least one class tag (e.g., B-protein, the beginning of a protein name). However, such features may be insufficient in cases where multiple properties must be considered. Adding conjunction features that contain multiple properties can be beneficial, but it would be infeasible to include all conjunction features in an NER model since memory resources are limited and some features are ineffective. To resolve the problem, we use a sequential forward search algorithm to select an effective set of features. Second, variations in the numerical parts of biomedical terms (e.g., "2" in the biomedical term IL2) cause data sparseness and generate many redundant features. In this case, we apply numerical normalization, which solves the problem by replacing all numerals in a term with one representative numeral to help classify named entities. Third, the assignment of NE tags does not depend solely on the target word's closest neighbors, but may depend on words outside the context window (e.g., a context window of five consists of the current word plus two preceding and two subsequent words). We use global patterns generated by the Smith-Waterman local alignment algorithm to identify such structures and modify the results of our ML-based tagger. This is called pattern-based post-processing. To develop our ML-based Bio-NER system, we employ conditional

A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries.

PubMed

Jiang, Min; Chen, Yukun; Liu, Mei; Rosenbloom, S Trent; Mani, Subramani; Denny, Joshua C; Xu, Hua

2011-01-01

The authors' goal was to develop and evaluate machine-learning-based approaches to extracting clinical entities-including medical problems, tests, and treatments, as well as their asserted status-from hospital discharge summaries written using natural language. This project was part of the 2010 Center of Informatics for Integrating Biology and the Bedside/Veterans Affairs (VA) natural-language-processing challenge. The authors implemented a machine-learning-based named entity recognition system for clinical text and systematically evaluated the contributions of different types of features and ML algorithms, using a training corpus of 349 annotated notes. Based on the results from training data, the authors developed a novel hybrid clinical entity extraction system, which integrated heuristic rule-based modules with the ML-base named entity recognition module. The authors applied the hybrid system to the concept extraction and assertion classification tasks in the challenge and evaluated its performance using a test data set with 477 annotated notes. Standard measures including precision, recall, and F-measure were calculated using the evaluation script provided by the Center of Informatics for Integrating Biology and the Bedside/VA challenge organizers. The overall performance for all three types of clinical entities and all six types of assertions across 477 annotated notes were considered as the primary metric in the challenge. Systematic evaluation on the training set showed that Conditional Random Fields outperformed Support Vector Machines, and semantic information from existing natural-language-processing systems largely improved performance, although contributions from different types of features varied. The authors' hybrid entity extraction system achieved a maximum overall F-score of 0.8391 for concept extraction (ranked second) and 0.9313 for assertion classification (ranked fourth, but not statistically different than the first three systems) on the test

26 CFR 301.7701-3 - Classification of certain business entities.

Code of Federal Regulations, 2013 CFR

2013-04-01

... the new target corporation under section 338. (iii) Application to successive elections in tiered... of an entity does not result in the creation of a new entity for purposes of the sixty month... entity separate from A when A becomes the only member of X. X, however, is not treated as a new entity...

26 CFR 301.7701-3 - Classification of certain business entities.

Code of Federal Regulations, 2012 CFR

2012-04-01

... the new target corporation under section 338. (iii) Application to successive elections in tiered... of an entity does not result in the creation of a new entity for purposes of the sixty month... entity separate from A when A becomes the only member of X. X, however, is not treated as a new entity...

26 CFR 301.7701-3 - Classification of certain business entities.

Code of Federal Regulations, 2011 CFR

2011-04-01

... the new target corporation under section 338. (iii) Application to successive elections in tiered... of an entity does not result in the creation of a new entity for purposes of the sixty month... entity separate from A when A becomes the only member of X. X, however, is not treated as a new entity...

26 CFR 301.7701-3 - Classification of certain business entities.

Code of Federal Regulations, 2014 CFR

2014-04-01

... the new target corporation under section 338. (iii) Application to successive elections in tiered... of an entity does not result in the creation of a new entity for purposes of the sixty month... entity separate from A when A becomes the only member of X. X, however, is not treated as a new entity...

76 FR 28503 - Identification of Three Entities as Government of Libya Entities Pursuant to Executive Order 13566

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-17

... DEPARTMENT OF THE TREASURY Office of Foreign Assets Control Identification of Three Entities as Government of Libya Entities Pursuant to Executive Order 13566 AGENCY: Department of the Treasury. ACTION... names of three entities identified on May 5, 2011 as persons whose property and interests in property...

17 CFR 229.1107 - (Item 1107) Issuing entities.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 17 Commodity and Securities Exchanges 2 2011-04-01 2011-04-01 false (Item 1107) Issuing entities....1107 (Item 1107) Issuing entities. Provide the following information about the issuing entity: (a) State the issuing entity's name and describe the issuing entity's form of organization, including the...

17 CFR 229.1107 - (Item 1107) Issuing entities.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 17 Commodity and Securities Exchanges 2 2010-04-01 2010-04-01 false (Item 1107) Issuing entities....1107 (Item 1107) Issuing entities. Provide the following information about the issuing entity: (a) State the issuing entity's name and describe the issuing entity's form of organization, including the...

Moving Hands, Moving Entities

ERIC Educational Resources Information Center

Setti, Annalisa; Borghi, Anna M.; Tessari, Alessia

2009-01-01

In this study we investigated with a priming paradigm whether uni and bimanual actions presented as primes differently affected language processing. Animals' (self-moving entities) and plants' (not self-moving entities) names were used as targets. As prime we used grasping hands, presented both as static images and videos. The results showed an…

A New Data Representation Based on Training Data Characteristics to Extract Drug Name Entity in Medical Text

PubMed Central

Basaruddin, T.

2016-01-01

One essential task in information extraction from the medical corpus is drug name recognition. Compared with text sources come from other domains, the medical text mining poses more challenges, for example, more unstructured text, the fast growing of new terms addition, a wide range of name variation for the same drug, the lack of labeled dataset sources and external knowledge, and the multiple token representations for a single drug name. Although many approaches have been proposed to overwhelm the task, some problems remained with poor F-score performance (less than 0.75). This paper presents a new treatment in data representation techniques to overcome some of those challenges. We propose three data representation techniques based on the characteristics of word distribution and word similarities as a result of word embedding training. The first technique is evaluated with the standard NN model, that is, MLP. The second technique involves two deep network classifiers, that is, DBN and SAE. The third technique represents the sentence as a sequence that is evaluated with a recurrent NN model, that is, LSTM. In extracting the drug name entities, the third technique gives the best F-score performance compared to the state of the art, with its average F-score being 0.8645. PMID:27843447

Divorcing Strain Classification from Species Names.

PubMed

Baltrus, David A

2016-06-01

Confusion about strain classification and nomenclature permeates modern microbiology. Although taxonomists have traditionally acted as gatekeepers of order, the numbers of, and speed at which, new strains are identified has outpaced the opportunity for professional classification for many lineages. Furthermore, the growth of bioinformatics and database-fueled investigations have placed metadata curation in the hands of researchers with little taxonomic experience. Here I describe practical challenges facing modern microbial taxonomy, provide an overview of complexities of classification for environmentally ubiquitous taxa like Pseudomonas syringae, and emphasize that classification can be independent of nomenclature. A move toward implementation of relational classification schemes based on inherent properties of whole genomes could provide sorely needed continuity in how strains are referenced across manuscripts and data sets. Copyright © 2016 Elsevier Ltd. All rights reserved.

Moving beyond the Name: Defining Corporate Entities to Support Provenance-Based Access

ERIC Educational Resources Information Center

Light, Michelle

2007-01-01

The second edition of the "International Standard Archival Authority Records for Corporate Bodies, Persons, and Families (ISAAR(CPF)2)" focuses on describing entities as they exist in reality, rather than on establishing authorized terms. This change allows authority records to include multiple authorized terms representing an entity as it changed…

77 FR 61658 - Designation of Two Entities Pursuant to Executive Orders

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-10

... DEPARTMENT OF THE TREASURY Office of Foreign Assets Control Designation of Two Entities Pursuant... Treasury Department's Office of Foreign Assets Control (``OFAC'') is publishing the names of two entities....'' DATES: The designation by the Director of OFAC of the two entities named in this notice, pursuant to...

Round Cell Tumors: Classification and Immunohistochemistry.

PubMed

Sharma, Shweta; Kamala, R; Nair, Divya; Ragavendra, T Raju; Mhatre, Swapnil; Sabharwal, Robin; Choudhury, Basanta Kumar; Rana, Vivek

2017-01-01

Round cell tumors as the name suggest are comprised round cells with increased nuclear-cytoplasmic ratio. This group of tumor includes entities such as peripheral neuroectodermal tumor, rhabdomyosarcoma, synovial sarcoma, non-Hodgkin's lymphoma, neuroblastoma, hepatoblastoma, Wilms' tumor, and desmoplastic small round cell tumor. These round cells tumors are characterized by typical histological pattern, immunohistochemical, and electron microscopic features that can help in differential diagnosis. The present article describes the classification and explains the histopathology and immunohistochemistry of some important round cell tumors.

Entity-based Stochastic Analysis of Search Results for Query Expansion and Results Re-Ranking

DTIC Science & Technology

2015-11-20

pages) and struc- tured data (e.g. Linked Open Data ( LOD ) [8]) coexist in var- ious forms. An important observation is that entity names (like names of...the top-L (e.g. L = 1, 000) results are retrieved. Then, Named Entity Recognition (NER) is applied in these results for identifying LOD entities. In...the next (optional) step, more semantic information about the identified entities is retrieved from the LOD (like properties and related entities). A

Encoding of Fundamental Chemical Entities of Organic Reactivity Interest using chemical ontology and XML.

PubMed

Durairaj, Vijayasarathi; Punnaivanam, Sankar

2015-09-01

Fundamental chemical entities are identified in the context of organic reactivity and classified as appropriate concept classes namely ElectronEntity, AtomEntity, AtomGroupEntity, FunctionalGroupEntity and MolecularEntity. The entity classes and their subclasses are organized into a chemical ontology named "ChemEnt" for the purpose of assertion, restriction and modification of properties through entity relations. Individual instances of entity classes are defined and encoded as a library of chemical entities in XML. The instances of entity classes are distinguished with a unique notation and identification values in order to map them with the ontology definitions. A model GUI named Entity Table is created to view graphical representations of all the entity instances. The detection of chemical entities in chemical structures is achieved through suitable algorithms. The possibility of asserting properties to the entities at different levels and the mechanism of property flow within the hierarchical entity levels is outlined. Copyright © 2015 Elsevier Inc. All rights reserved.

Context and Domain Knowledge Enhanced Entity Spotting in Informal Text

NASA Astrophysics Data System (ADS)

Gruhl, Daniel; Nagarajan, Meena; Pieper, Jan; Robson, Christine; Sheth, Amit

This paper explores the application of restricted relationship graphs (RDF) and statistical NLP techniques to improve named entity annotation in challenging Informal English domains. We validate our approach using on-line forums discussing popular music. Named entity annotation is particularly difficult in this domain because it is characterized by a large number of ambiguous entities, such as the Madonna album "Music" or Lilly Allen's pop hit "Smile".

Cystic renal tumors: new entities and novel concepts.

PubMed

Moch, Holger

2010-05-01

Cystic renal neoplasms and renal epithelial stromal tumors are diagnostically challenging and represent some novel tumor entities. In this article, clinical and pathologic features of established and novel entities are discussed. Predominantly cystic renal tumors include cystic nephroma/mixed epithelial and stromal tumor, synovial sarcoma, and multilocular cystic renal cell carcinoma. These entities are own tumor entities of the 2004 WHO classification of renal tumors. Tubulocystic carcinoma and acquired cystic disease-associated renal cell carcinoma are neoplasms with an intrinsically cystic growth pattern. Both tumor types should be included in a future WHO classification as novel entities owing to their characteristic features. Cysts and clear cell renal cell carcinoma frequently coexist within the kidneys of patients with von Hippel-Lindau disease. Sporadic clear cell renal cell carcinomas often contain cysts, usually as a minor component. Some clear cell renal cell carcinomas have prominent cysts, and multilocular cystic renal cell carcinoma is composed almost exclusively of cysts. Recent molecular findings suggest that clear cell renal cancer may develop through cyst-dependent and cyst-independent molecular pathways.

Two Influential Primate Classifications Logically Aligned

PubMed Central

Franz, Nico M.; Pier, Naomi M.; Reeder, Deeann M.; Chen, Mingmin; Yu, Shizhuo; Kianmajd, Parisa; Bowers, Shawn; Ludäscher, Bertram

2016-01-01

Classifications and phylogenies of perceived natural entities change in the light of new evidence. Taxonomic changes, translated into Code-compliant names, frequently lead to name:meaning dissociations across succeeding treatments. Classification standards such as the Mammal Species of the World (MSW) may experience significant levels of taxonomic change from one edition to the next, with potential costs to long-term, large-scale information integration. This circumstance challenges the biodiversity and phylogenetic data communities to express taxonomic congruence and incongruence in ways that both humans and machines can process, that is, to logically represent taxonomic alignments across multiple classifications. We demonstrate that such alignments are feasible for two classifications of primates corresponding to the second and third MSW editions. Our approach has three main components: (i) use of taxonomic concept labels, that is name sec. author (where sec. means according to), to assemble each concept hierarchy separately via parent/child relationships; (ii) articulation of select concepts across the two hierarchies with user-provided Region Connection Calculus (RCC-5) relationships; and (iii) the use of an Answer Set Programming toolkit to infer and visualize logically consistent alignments of these input constraints. Our use case entails the Primates sec. Groves (1993; MSW2–317 taxonomic concepts; 233 at the species level) and Primates sec. Groves (2005; MSW3–483 taxonomic concepts; 376 at the species level). Using 402 RCC-5 input articulations, the reasoning process yields a single, consistent alignment and 153,111 Maximally Informative Relations that constitute a comprehensive meaning resolution map for every concept pair in the Primates sec. MSW2/MSW3. The complete alignment, and various partitions thereof, facilitate quantitative analyses of name:meaning dissociation, revealing that nearly one in three taxonomic names are not reliable across

A System to Automatically Classify and Name Any Individual Genome-Sequenced Organism Independently of Current Biological Classification and Nomenclature

PubMed Central

Song, Yuhyun; Leman, Scotland; Monteil, Caroline L.; Heath, Lenwood S.; Vinatzer, Boris A.

2014-01-01

A broadly accepted and stable biological classification system is a prerequisite for biological sciences. It provides the means to describe and communicate about life without ambiguity. Current biological classification and nomenclature use the species as the basic unit and require lengthy and laborious species descriptions before newly discovered organisms can be assigned to a species and be named. The current system is thus inadequate to classify and name the immense genetic diversity within species that is now being revealed by genome sequencing on a daily basis. To address this lack of a general intra-species classification and naming system adequate for today’s speed of discovery of new diversity, we propose a classification and naming system that is exclusively based on genome similarity and that is suitable for automatic assignment of codes to any genome-sequenced organism without requiring any phenotypic or phylogenetic analysis. We provide examples demonstrating that genome similarity-based codes largely align with current taxonomic groups at many different levels in bacteria, animals, humans, plants, and viruses. Importantly, the proposed approach is only slightly affected by the order of code assignment and can thus provide codes that reflect similarity between organisms and that do not need to be revised upon discovery of new diversity. We envision genome similarity-based codes to complement current biological nomenclature and to provide a universal means to communicate unambiguously about any genome-sequenced organism in fields as diverse as biodiversity research, infectious disease control, human and microbial forensics, animal breed and plant cultivar certification, and human ancestry research. PMID:24586551

Impact of translation on named-entity recognition in radiology texts

PubMed Central

Pedro, Vasco

2017-01-01

Abstract Radiology reports describe the results of radiography procedures and have the potential of being a useful source of information which can bring benefits to health care systems around the world. One way to automatically extract information from the reports is by using Text Mining tools. The problem is that these tools are mostly developed for English and reports are usually written in the native language of the radiologist, which is not necessarily English. This creates an obstacle to the sharing of Radiology information between different communities. This work explores the solution of translating the reports to English before applying the Text Mining tools, probing the question of what translation approach should be used. We created MRRAD (Multilingual Radiology Research Articles Dataset), a parallel corpus of Portuguese research articles related to Radiology and a number of alternative translations (human, automatic and semi-automatic) to English. This is a novel corpus which can be used to move forward the research on this topic. Using MRRAD we studied which kind of automatic or semi-automatic translation approach is more effective on the Named-entity recognition task of finding RadLex terms in the English version of the articles. Considering the terms extracted from human translations as our gold standard, we calculated how similar to this standard were the terms extracted using other translations. We found that a completely automatic translation approach using Google leads to F-scores (between 0.861 and 0.868, depending on the extraction approach) similar to the ones obtained through a more expensive semi-automatic translation approach using Unbabel (between 0.862 and 0.870). To better understand the results we also performed a qualitative analysis of the type of errors found in the automatic and semi-automatic translations. Database URL: https://github.com/lasigeBioTM/MRRAD PMID:29220455

31 CFR 306.88 - Political entities and public corporations.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 2 2011-07-01 2011-07-01 false Political entities and public... entities and public corporations. Securities registered in the name of, or assigned to, a State, county, city, town, village, school district or other political entity, public body or corporation, may be...

31 CFR 306.88 - Political entities and public corporations.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 2 2010-07-01 2010-07-01 false Political entities and public... entities and public corporations. Securities registered in the name of, or assigned to, a State, county, city, town, village, school district or other political entity, public body or corporation, may be...

26 CFR 301.7701-3 - Classification of certain business entities.

Code of Federal Regulations, 2010 CFR

2010-04-01

... association (S1), which wholly owns another eligible entity classified as an association (S2), which wholly... this section are filed to classify S1, S2, and S3 each as disregarded as an entity separate from its... transaction occurring on the same day immediately after the preceding transaction S1 is treated as liquidating...

Identifying non-elliptical entity mentions in a coordinated NP with ellipses.

PubMed

Chae, Jeongmin; Jung, Younghee; Lee, Taemin; Jung, Soonyoung; Huh, Chan; Kim, Gilhan; Kim, Hyeoncheol; Oh, Heungbum

2014-02-01

Named entities in the biomedical domain are often written using a Noun Phrase (NP) along with a coordinating conjunction such as 'and' and 'or'. In addition, repeated words among named entity mentions are frequently omitted. It is often difficult to identify named entities. Although various Named Entity Recognition (NER) methods have tried to solve this problem, these methods can only deal with relatively simple elliptical patterns in coordinated NPs. We propose a new NER method for identifying non-elliptical entity mentions with simple or complex ellipses using linguistic rules and an entity mention dictionary. The GENIA and CRAFT corpora were used to evaluate the performance of the proposed system. The GENIA corpus was used to evaluate the performance of the system according to the quality of the dictionary. The GENIA corpus comprises 3434 non-elliptical entity mentions in 1585 coordinated NPs with ellipses. The system achieves 92.11% precision, 95.20% recall, and 93.63% F-score in identification of non-elliptical entity mentions in coordinated NPs. The accuracy of the system in resolving simple and complex ellipses is 94.54% and 91.95%, respectively. The CRAFT corpus was used to evaluate the performance of the system under realistic conditions. The system achieved 78.47% precision, 67.10% recall, and 72.34% F-score in coordinated NPs. The performance evaluations of the system show that it efficiently solves the problem caused by ellipses, and improves NER performance. The algorithm is implemented in PHP and the code can be downloaded from https://code.google.com/p/medtextmining/. Copyright © 2013. Published by Elsevier Inc.

Two Influential Primate Classifications Logically Aligned.

PubMed

Franz, Nico M; Pier, Naomi M; Reeder, Deeann M; Chen, Mingmin; Yu, Shizhuo; Kianmajd, Parisa; Bowers, Shawn; Ludäscher, Bertram

2016-07-01

Classifications and phylogenies of perceived natural entities change in the light of new evidence. Taxonomic changes, translated into Code-compliant names, frequently lead to name:meaning dissociations across succeeding treatments. Classification standards such as the Mammal Species of the World (MSW) may experience significant levels of taxonomic change from one edition to the next, with potential costs to long-term, large-scale information integration. This circumstance challenges the biodiversity and phylogenetic data communities to express taxonomic congruence and incongruence in ways that both humans and machines can process, that is, to logically represent taxonomic alignments across multiple classifications. We demonstrate that such alignments are feasible for two classifications of primates corresponding to the second and third MSW editions. Our approach has three main components: (i) use of taxonomic concept labels, that is name sec. author (where sec. means according to), to assemble each concept hierarchy separately via parent/child relationships; (ii) articulation of select concepts across the two hierarchies with user-provided Region Connection Calculus (RCC-5) relationships; and (iii) the use of an Answer Set Programming toolkit to infer and visualize logically consistent alignments of these input constraints. Our use case entails the Primates sec. Groves (1993; MSW2-317 taxonomic concepts; 233 at the species level) and Primates sec. Groves (2005; MSW3-483 taxonomic concepts; 376 at the species level). Using 402 RCC-5 input articulations, the reasoning process yields a single, consistent alignment and 153,111 Maximally Informative Relations that constitute a comprehensive meaning resolution map for every concept pair in the Primates sec. MSW2/MSW3. The complete alignment, and various partitions thereof, facilitate quantitative analyses of name:meaning dissociation, revealing that nearly one in three taxonomic names are not reliable across treatments

Disease named entity recognition from biomedical literature using a novel convolutional neural network.

PubMed

Zhao, Zhehuan; Yang, Zhihao; Luo, Ling; Wang, Lei; Zhang, Yin; Lin, Hongfei; Wang, Jian

2017-12-28

Automatic disease named entity recognition (DNER) is of utmost importance for development of more sophisticated BioNLP tools. However, most conventional CRF based DNER systems rely on well-designed features whose selection is labor intensive and time-consuming. Though most deep learning methods can solve NER problems with little feature engineering, they employ additional CRF layer to capture the correlation information between labels in neighborhoods which makes them much complicated. In this paper, we propose a novel multiple label convolutional neural network (MCNN) based disease NER approach. In this approach, instead of the CRF layer, a multiple label strategy (MLS) first introduced by us, is employed. First, the character-level embedding, word-level embedding and lexicon feature embedding are concatenated. Then several convolutional layers are stacked over the concatenated embedding. Finally, MLS strategy is applied to the output layer to capture the correlation information between neighboring labels. As shown by the experimental results, MCNN can achieve the state-of-the-art performance on both NCBI and CDR corpora. The proposed MCNN based disease NER method achieves the state-of-the-art performance with little feature engineering. And the experimental results show the MLS strategy's effectiveness of capturing the correlation information between labels in the neighborhood.

Noun and knowledge retrieval for biological and non-biological entities following right occipitotemporal lesions.

PubMed

Bruffaerts, Rose; De Weer, An-Sofie; De Grauwe, Sophie; Thys, Miek; Dries, Eva; Thijs, Vincent; Sunaert, Stefan; Vandenbulcke, Mathieu; De Deyne, Simon; Storms, Gerrit; Vandenberghe, Rik

2014-09-01

We investigated the critical contribution of right ventral occipitotemporal cortex to knowledge of visual and functional-associative attributes of biological and non-biological entities and how this relates to category-specificity during confrontation naming. In a consecutive series of 7 patients with lesions confined to right ventral occipitotemporal cortex, we conducted an extensive assessment of oral generation of visual-sensory and functional-associative features in response to the names of biological and nonbiological entities. Subjects also performed a confrontation naming task for these categories. Our main novel finding related to a unique case with a small lesion confined to right medial fusiform gyrus who showed disproportionate naming impairment for nonbiological versus biological entities, specifically for tools. Generation of visual and functional-associative features was preserved for biological and non-biological entities. In two other cases, who had a relatively small posterior lesion restricted to primary visual and posterior fusiform cortex, retrieval of visual attributes was disproportionately impaired compared to functional-associative attributes, in particular for biological entities. However, these cases did not show a category-specific naming deficit. Two final cases with the largest lesions showed a classical dissociation between biological versus nonbiological entities during naming, with normal feature generation performance. This is the first lesion-based evidence of a critical contribution of the right medial fusiform cortex to tool naming. Second, dissociations along the dimension of attribute type during feature generation do not co-occur with category-specificity during naming in the current patient sample. Copyright © 2014 Elsevier Ltd. All rights reserved.

Adapting Web content for low-literacy readers by using lexical elaboration and named entities labeling

NASA Astrophysics Data System (ADS)

Watanabe, W. M.; Candido, A.; Amâncio, M. A.; De Oliveira, M.; Pardo, T. A. S.; Fortes, R. P. M.; Aluísio, S. M.

2010-12-01

This paper presents an approach for assisting low-literacy readers in accessing Web online information. The "Educational FACILITA" tool is a Web content adaptation tool that provides innovative features and follows more intuitive interaction models regarding accessibility concerns. Especially, we propose an interaction model and a Web application that explore the natural language processing tasks of lexical elaboration and named entity labeling for improving Web accessibility. We report on the results obtained from a pilot study on usability analysis carried out with low-literacy users. The preliminary results show that "Educational FACILITA" improves the comprehension of text elements, although the assistance mechanisms might also confuse users when word sense ambiguity is introduced, by gathering, for a complex word, a list of synonyms with multiple meanings. This fact evokes a future solution in which the correct sense for a complex word in a sentence is identified, solving this pervasive characteristic of natural languages. The pilot study also identified that experienced computer users find the tool to be more useful than novice computer users do.

Chemical Entity Recognition and Resolution to ChEBI

PubMed Central

Grego, Tiago; Pesquita, Catia; Bastos, Hugo P.; Couto, Francisco M.

2012-01-01

Chemical entities are ubiquitous through the biomedical literature and the development of text-mining systems that can efficiently identify those entities are required. Due to the lack of available corpora and data resources, the community has focused its efforts in the development of gene and protein named entity recognition systems, but with the release of ChEBI and the availability of an annotated corpus, this task can be addressed. We developed a machine-learning-based method for chemical entity recognition and a lexical-similarity-based method for chemical entity resolution and compared them with Whatizit, a popular-dictionary-based method. Our methods outperformed the dictionary-based method in all tasks, yielding an improvement in F-measure of 20% for the entity recognition task, 2–5% for the entity-resolution task, and 15% for combined entity recognition and resolution tasks. PMID:25937941

The 2015 World Health Organization Classification of Lung Tumors: Impact of Genetic, Clinical and Radiologic Advances Since the 2004 Classification.

PubMed

Travis, William D; Brambilla, Elisabeth; Nicholson, Andrew G; Yatabe, Yasushi; Austin, John H M; Beasley, Mary Beth; Chirieac, Lucian R; Dacic, Sanja; Duhig, Edwina; Flieder, Douglas B; Geisinger, Kim; Hirsch, Fred R; Ishikawa, Yuichi; Kerr, Keith M; Noguchi, Masayuki; Pelosi, Giuseppe; Powell, Charles A; Tsao, Ming Sound; Wistuba, Ignacio

2015-09-01

The 2015 World Health Organization (WHO) Classification of Tumors of the Lung, Pleura, Thymus and Heart has just been published with numerous important changes from the 2004 WHO classification. The most significant changes in this edition involve (1) use of immunohistochemistry throughout the classification, (2) a new emphasis on genetic studies, in particular, integration of molecular testing to help personalize treatment strategies for advanced lung cancer patients, (3) a new classification for small biopsies and cytology similar to that proposed in the 2011 Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification, (4) a completely different approach to lung adenocarcinoma as proposed by the 2011 Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification, (5) restricting the diagnosis of large cell carcinoma only to resected tumors that lack any clear morphologic or immunohistochemical differentiation with reclassification of the remaining former large cell carcinoma subtypes into different categories, (6) reclassifying squamous cell carcinomas into keratinizing, nonkeratinizing, and basaloid subtypes with the nonkeratinizing tumors requiring immunohistochemistry proof of squamous differentiation, (7) grouping of neuroendocrine tumors together in one category, (8) adding NUT carcinoma, (9) changing the term sclerosing hemangioma to sclerosing pneumocytoma, (10) changing the name hamartoma to "pulmonary hamartoma," (11) creating a group of PEComatous tumors that include (a) lymphangioleiomyomatosis, (b) PEComa, benign (with clear cell tumor as a variant) and (c) PEComa, malignant, (12) introducing the entity pulmonary myxoid sarcoma with an EWSR1-CREB1 translocation, (13) adding the entities myoepithelioma and myoepithelial carcinomas, which can show EWSR1 gene rearrangements, (14) recognition of usefulness of WWTR1-CAMTA1 fusions in diagnosis of epithelioid

2 CFR 170.110 - Types of entities to which this part applies.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 2 Grants and Agreements 1 2014-01-01 2014-01-01 false Types of entities to which this part applies... or receive agency awards; or (2) Receive subawards under those awards. (b) Exceptions. (1) None of... her name). (2) None of the requirements regarding reporting names and total compensation of an entity...

2 CFR 170.110 - Types of entities to which this part applies.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 2 Grants and Agreements 1 2011-01-01 2011-01-01 false Types of entities to which this part applies... or receive agency awards; or (2) Receive subawards under those awards. (b) Exceptions. (1) None of... her name). (2) None of the requirements regarding reporting names and total compensation of an entity...

GRAM-CNN: a deep learning approach with local context for named entity recognition in biomedical text.

PubMed

Zhu, Qile; Li, Xiaolin; Conesa, Ana; Pereira, Cécile

2018-05-01

Best performing named entity recognition (NER) methods for biomedical literature are based on hand-crafted features or task-specific rules, which are costly to produce and difficult to generalize to other corpora. End-to-end neural networks achieve state-of-the-art performance without hand-crafted features and task-specific knowledge in non-biomedical NER tasks. However, in the biomedical domain, using the same architecture does not yield competitive performance compared with conventional machine learning models. We propose a novel end-to-end deep learning approach for biomedical NER tasks that leverages the local contexts based on n-gram character and word embeddings via Convolutional Neural Network (CNN). We call this approach GRAM-CNN. To automatically label a word, this method uses the local information around a word. Therefore, the GRAM-CNN method does not require any specific knowledge or feature engineering and can be theoretically applied to a wide range of existing NER problems. The GRAM-CNN approach was evaluated on three well-known biomedical datasets containing different BioNER entities. It obtained an F1-score of 87.26% on the Biocreative II dataset, 87.26% on the NCBI dataset and 72.57% on the JNLPBA dataset. Those results put GRAM-CNN in the lead of the biological NER methods. To the best of our knowledge, we are the first to apply CNN based structures to BioNER problems. The GRAM-CNN source code, datasets and pre-trained model are available online at: https://github.com/valdersoul/GRAM-CNN. andyli@ece.ufl.edu or aconesa@ufl.edu. Supplementary data are available at Bioinformatics online.

GRAM-CNN: a deep learning approach with local context for named entity recognition in biomedical text

PubMed Central

Zhu, Qile; Li, Xiaolin; Conesa, Ana; Pereira, Cécile

2018-01-01

Abstract Motivation Best performing named entity recognition (NER) methods for biomedical literature are based on hand-crafted features or task-specific rules, which are costly to produce and difficult to generalize to other corpora. End-to-end neural networks achieve state-of-the-art performance without hand-crafted features and task-specific knowledge in non-biomedical NER tasks. However, in the biomedical domain, using the same architecture does not yield competitive performance compared with conventional machine learning models. Results We propose a novel end-to-end deep learning approach for biomedical NER tasks that leverages the local contexts based on n-gram character and word embeddings via Convolutional Neural Network (CNN). We call this approach GRAM-CNN. To automatically label a word, this method uses the local information around a word. Therefore, the GRAM-CNN method does not require any specific knowledge or feature engineering and can be theoretically applied to a wide range of existing NER problems. The GRAM-CNN approach was evaluated on three well-known biomedical datasets containing different BioNER entities. It obtained an F1-score of 87.26% on the Biocreative II dataset, 87.26% on the NCBI dataset and 72.57% on the JNLPBA dataset. Those results put GRAM-CNN in the lead of the biological NER methods. To the best of our knowledge, we are the first to apply CNN based structures to BioNER problems. Availability and implementation The GRAM-CNN source code, datasets and pre-trained model are available online at: https://github.com/valdersoul/GRAM-CNN. Contact andyli@ece.ufl.edu or aconesa@ufl.edu Supplementary information Supplementary data are available at Bioinformatics online. PMID:29272325

31 CFR 306.88 - Political entities and public corporations.

Code of Federal Regulations, 2013 CFR

2013-07-01

... corporations. 306.88 Section 306.88 Money and Finance: Treasury Regulations Relating to Money and Finance... entities and public corporations. Securities registered in the name of, or assigned to, a State, county, city, town, village, school district or other political entity, public body or corporation, may be...

31 CFR 306.88 - Political entities and public corporations.

Code of Federal Regulations, 2014 CFR

2014-07-01

... corporations. 306.88 Section 306.88 Money and Finance: Treasury Regulations Relating to Money and Finance... entities and public corporations. Securities registered in the name of, or assigned to, a State, county, city, town, village, school district or other political entity, public body or corporation, may be...

31 CFR 306.88 - Political entities and public corporations.

Code of Federal Regulations, 2012 CFR

2012-07-01

... corporations. 306.88 Section 306.88 Money and Finance: Treasury Regulations Relating to Money and Finance... entities and public corporations. Securities registered in the name of, or assigned to, a State, county, city, town, village, school district or other political entity, public body or corporation, may be...

Aggressive B-cell lymphomas in the update of the 4th edition of the World Health Organization classification of haematopoietic and lymphatic tissues: refinements of the classification, new entities and genetic findings.

PubMed

Ott, German

2017-09-01

The update of the 4th edition of the World Health Organization Classification of Haematopoietic and Lymphatic Tissues portends important new findings and concepts in the diagnosis, classification and biology of lymphomas. This review summarizes the basic concepts and cornerstones of the classification of aggressive B-cell lymphomas and details the major changes. Of importance, there is a new concept of High-grade B-cell lymphomas (HGBL), partly replacing the provisional entity of B-cell lymphoma, unclassifiable, with features intermediate between diffuse large B-cell lymphoma (DLBCL) and Burkitt lymphoma, the so-called grey zone lymphomas. They either harbour MYC translocations together with a BCL2 and/or a BCL6 rearrangement (HGBL-Double Hit) or HGBL, not otherwise specified (NOS), lacking a double or triple hit constellation. In addition, the requirement for providing the cell-of-origin classification in the diagnostic work-up of DLBCLs, the role of MYC alterations in DLBCL subtypes, and newer findings in the specific variants/subtypes are highlighted. © 2017 John Wiley & Sons Ltd.

Named Entity Recognition in a Hungarian NL Based QA System

NASA Astrophysics Data System (ADS)

Tikkl, Domonkos; Szidarovszky, P. Ferenc; Kardkovacs, Zsolt T.; Magyar, Gábor

In WoW project our purpose is to create a complex search interface with the following features: search in the deep web content of contracted partners' databases, processing Hungarian natural language (NL) questions and transforming them to SQL queries for database access, image search supported by a visual thesaurus that describes in a structural form the visual content of images (also in Hungarian). This paper primarily focuses on a particular problem of question processing task: the entity recognition. Before going into details we give a short overview of the project's aims.

76 FR 52384 - Designation of Additional Entities Pursuant to Executive Order 13405

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-22

... DEPARTMENT OF THE TREASURY Office of Foreign Assets Control Designation of Additional Entities... Assets Control (``OFAC'') is publishing the names of four newly-designated entities whose property and... the Director of OFAC of the four entities identified in this notice, pursuant to Executive [[Page...

A Novel Approach towards Medical Entity Recognition in Chinese Clinical Text

PubMed Central

Yu, Jian

2017-01-01

Medical entity recognition, a basic task in the language processing of clinical data, has been extensively studied in analyzing admission notes in alphabetic languages such as English. However, much less work has been done on nonstructural texts that are written in Chinese, or in the setting of differentiation of Chinese drug names between traditional Chinese medicine and Western medicine. Here, we propose a novel cascade-type Chinese medication entity recognition approach that aims at integrating the sentence category classifier from a support vector machine and the conditional random field-based medication entity recognition. We hypothesized that this approach could avoid the side effects of abundant negative samples and improve the performance of the named entity recognition from admission notes written in Chinese. Therefore, we applied this approach to a test set of 324 Chinese-written admission notes with manual annotation by medical experts. Our data demonstrated that this approach had a score of 94.2% in precision, 92.8% in recall, and 93.5% in F-measure for the recognition of traditional Chinese medicine drug names and 91.2% in precision, 92.6% in recall, and 91.7% F-measure for the recognition of Western medicine drug names. The differences in F-measure were significant compared with those in the baseline systems. PMID:29065612

Anatomical Entity Recognition with a Hierarchical Framework Augmented by External Resources

PubMed Central

Xu, Yan; Hua, Ji; Ni, Zhaoheng; Chen, Qinlang; Fan, Yubo; Ananiadou, Sophia; Chang, Eric I-Chao; Tsujii, Junichi

2014-01-01

References to anatomical entities in medical records consist not only of explicit references to anatomical locations, but also other diverse types of expressions, such as specific diseases, clinical tests, clinical treatments, which constitute implicit references to anatomical entities. In order to identify these implicit anatomical entities, we propose a hierarchical framework, in which two layers of named entity recognizers (NERs) work in a cooperative manner. Each of the NERs is implemented using the Conditional Random Fields (CRF) model, which use a range of external resources to generate features. We constructed a dictionary of anatomical entity expressions by exploiting four existing resources, i.e., UMLS, MeSH, RadLex and BodyPart3D, and supplemented information from two external knowledge bases, i.e., Wikipedia and WordNet, to improve inference of anatomical entities from implicit expressions. Experiments conducted on 300 discharge summaries showed a micro-averaged performance of 0.8509 Precision, 0.7796 Recall and 0.8137 F1 for explicit anatomical entity recognition, and 0.8695 Precision, 0.6893 Recall and 0.7690 F1 for implicit anatomical entity recognition. The use of the hierarchical framework, which combines the recognition of named entities of various types (diseases, clinical tests, treatments) with information embedded in external knowledge bases, resulted in a 5.08% increment in F1. The resources constructed for this research will be made publicly available. PMID:25343498

Identification of related gene/protein names based on an HMM of name variations.

PubMed

Yeganova, L; Smith, L; Wilbur, W J

2004-04-01

Gene and protein names follow few, if any, true naming conventions and are subject to great variation in different occurrences of the same name. This gives rise to two important problems in natural language processing. First, can one locate the names of genes or proteins in free text, and second, can one determine when two names denote the same gene or protein? The first of these problems is a special case of the problem of named entity recognition, while the second is a special case of the problem of automatic term recognition (ATR). We study the second problem, that of gene or protein name variation. Here we describe a system which, given a query gene or protein name, identifies related gene or protein names in a large list. The system is based on a dynamic programming algorithm for sequence alignment in which the mutation matrix is allowed to vary under the control of a fully trainable hidden Markov model.

[New features in the 2014 WHO classification of uterine neoplasms].

PubMed

Lax, S F

2016-11-01

The 2014 World Health Organization (WHO) classification of uterine tumors revealed simplification of the classification by fusion of several entities and the introduction of novel entities. Among the multitude of alterations, the following are named: a simplified classification for precursor lesions of endometrial carcinoma now distinguishes between hyperplasia without atypia and atypical hyperplasia, the latter also known as endometrioid intraepithelial neoplasia (EIN). For endometrial carcinoma a differentiation is made between type 1 (endometrioid carcinoma with variants and mucinous carcinoma) and type 2 (serous and clear cell carcinoma). Besides a papillary architecture serous carcinomas may show solid and glandular features and TP53 immunohistochemistry with an "all or null pattern" assists in the diagnosis of serous carcinoma with ambiguous features. Neuroendocrine neoplasms are categorized in a similar way to the gastrointestinal tract into well differentiated neuroendocrine tumors and poorly differentiated neuroendocrine carcinomas (small cell and large cell types). Leiomyosarcomas of the uterus are typically high grade and characterized by marked nuclear atypia and lively mitotic activity. Low grade stromal neoplasms frequently show gene fusions, such as JAZF1/SUZ12. High grade endometrial stromal sarcoma is newly defined by cyclin D1 overexpression and the presence of the fusion gene YWHAE/FAM22 and must be distinguished from undifferentiated uterine sarcoma. Carcinosarcomas (malignant mixed Mullerian tumors MMMT) show biological and molecular similarities to high-grade carcinomas.

14 CFR 1203.701 - Classification.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 5 2013-01-01 2013-01-01 false Classification. 1203.701 Section 1203.701... Government Information § 1203.701 Classification. (a) Foreign government information that is classified by a foreign entity shall either retain its original classification designation or be marked with a United...

14 CFR 1203.701 - Classification.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 5 2012-01-01 2012-01-01 false Classification. 1203.701 Section 1203.701... Government Information § 1203.701 Classification. (a) Foreign government information that is classified by a foreign entity shall either retain its original classification designation or be marked with a United...

14 CFR 1203.701 - Classification.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 5 2011-01-01 2010-01-01 true Classification. 1203.701 Section 1203.701... Government Information § 1203.701 Classification. (a) Foreign government information that is classified by a foreign entity shall either retain its original classification designation or be marked with a United...

The left temporal pole is a heteromodal hub for retrieving proper names

PubMed Central

Waldron, Eric J.; Manzel, Kenneth; Tranel, Daniel

2015-01-01

The left temporal pole (LTP) has been posited to be a heteromodal hub for retrieving proper names for semantically unique entities. Previous investigations have demonstrated that LTP is important for retrieving names for famous faces and unique landmarks. However, whether such a relationship would hold for unique entities apprehended through stimulus modalities other than vision has not been well established, and such evidence is critical to adjudicate claims about the “heteromodal” nature of the LTP. Here, we tested the hypothesis that the LTP would be important for naming famous voices. Individuals with LTP lesions were asked to recognize and name famous persons speaking in audio clips. Relative to neurologically normal and brain damaged comparison participants, patients with LTP lesions were able to recognize famous persons from their voices normally, but were selectively impaired in naming famous persons from their voices. The current results extend previous research and provide further support for the notion that the LTP is a convergence region serving as a heteromodal hub for retrieving the names of semantically unique entities. PMID:24389260

InterLymph hierarchical classification of lymphoid neoplasms for epidemiologic research based on the WHO classification (2008): update and future directions

PubMed Central

Morton, Lindsay M.; Linet, Martha S.; Clarke, Christina A.; Kadin, Marshall E.; Vajdic, Claire M.; Monnereau, Alain; Maynadié, Marc; Chiu, Brian C.-H.; Marcos-Gragera, Rafael; Costantini, Adele Seniori; Cerhan, James R.; Weisenburger, Dennis D.

2010-01-01

After publication of the updated World Health Organization (WHO) classification of tumors of hematopoietic and lymphoid tissues in 2008, the Pathology Working Group of the International Lymphoma Epidemiology Consortium (InterLymph) now presents an update of the hierarchical classification of lymphoid neoplasms for epidemiologic research based on the 2001 WHO classification, which we published in 2007. The updated hierarchical classification incorporates all of the major and provisional entities in the 2008 WHO classification, including newly defined entities based on age, site, certain infections, and molecular characteristics, as well as borderline categories, early and “in situ” lesions, disorders with limited capacity for clinical progression, lesions without current International Classification of Diseases for Oncology, 3rd Edition codes, and immunodeficiency-associated lymphoproliferative disorders. WHO subtypes are defined in hierarchical groupings, with newly defined groups for small B-cell lymphomas with plasmacytic differentiation and for primary cutaneous T-cell lymphomas. We suggest approaches for applying the hierarchical classification in various epidemiologic settings, including strategies for dealing with multiple coexisting lymphoma subtypes in one patient, and cases with incomplete pathologic information. The pathology materials useful for state-of-the-art epidemiology studies are also discussed. We encourage epidemiologists to adopt the updated InterLymph hierarchical classification, which incorporates the most recent WHO entities while demonstrating their relationship to older classifications. PMID:20699439

InterLymph hierarchical classification of lymphoid neoplasms for epidemiologic research based on the WHO classification (2008): update and future directions.

PubMed

Turner, Jennifer J; Morton, Lindsay M; Linet, Martha S; Clarke, Christina A; Kadin, Marshall E; Vajdic, Claire M; Monnereau, Alain; Maynadié, Marc; Chiu, Brian C-H; Marcos-Gragera, Rafael; Costantini, Adele Seniori; Cerhan, James R; Weisenburger, Dennis D

2010-11-18

After publication of the updated World Health Organization (WHO) classification of tumors of hematopoietic and lymphoid tissues in 2008, the Pathology Working Group of the International Lymphoma Epidemiology Consortium (InterLymph) now presents an update of the hierarchical classification of lymphoid neoplasms for epidemiologic research based on the 2001 WHO classification, which we published in 2007. The updated hierarchical classification incorporates all of the major and provisional entities in the 2008 WHO classification, including newly defined entities based on age, site, certain infections, and molecular characteristics, as well as borderline categories, early and "in situ" lesions, disorders with limited capacity for clinical progression, lesions without current International Classification of Diseases for Oncology, 3rd Edition codes, and immunodeficiency-associated lymphoproliferative disorders. WHO subtypes are defined in hierarchical groupings, with newly defined groups for small B-cell lymphomas with plasmacytic differentiation and for primary cutaneous T-cell lymphomas. We suggest approaches for applying the hierarchical classification in various epidemiologic settings, including strategies for dealing with multiple coexisting lymphoma subtypes in one patient, and cases with incomplete pathologic information. The pathology materials useful for state-of-the-art epidemiology studies are also discussed. We encourage epidemiologists to adopt the updated InterLymph hierarchical classification, which incorporates the most recent WHO entities while demonstrating their relationship to older classifications.

New Brain Tumor Entities Emerge from Molecular Classification of CNS-PNETs.

PubMed

Sturm, Dominik; Orr, Brent A; Toprak, Umut H; Hovestadt, Volker; Jones, David T W; Capper, David; Sill, Martin; Buchhalter, Ivo; Northcott, Paul A; Leis, Irina; Ryzhova, Marina; Koelsche, Christian; Pfaff, Elke; Allen, Sariah J; Balasubramanian, Gnanaprakash; Worst, Barbara C; Pajtler, Kristian W; Brabetz, Sebastian; Johann, Pascal D; Sahm, Felix; Reimand, Jüri; Mackay, Alan; Carvalho, Diana M; Remke, Marc; Phillips, Joanna J; Perry, Arie; Cowdrey, Cynthia; Drissi, Rachid; Fouladi, Maryam; Giangaspero, Felice; Łastowska, Maria; Grajkowska, Wiesława; Scheurlen, Wolfram; Pietsch, Torsten; Hagel, Christian; Gojo, Johannes; Lötsch, Daniela; Berger, Walter; Slavc, Irene; Haberler, Christine; Jouvet, Anne; Holm, Stefan; Hofer, Silvia; Prinz, Marco; Keohane, Catherine; Fried, Iris; Mawrin, Christian; Scheie, David; Mobley, Bret C; Schniederjan, Matthew J; Santi, Mariarita; Buccoliero, Anna M; Dahiya, Sonika; Kramm, Christof M; von Bueren, André O; von Hoff, Katja; Rutkowski, Stefan; Herold-Mende, Christel; Frühwald, Michael C; Milde, Till; Hasselblatt, Martin; Wesseling, Pieter; Rößler, Jochen; Schüller, Ulrich; Ebinger, Martin; Schittenhelm, Jens; Frank, Stephan; Grobholz, Rainer; Vajtai, Istvan; Hans, Volkmar; Schneppenheim, Reinhard; Zitterbart, Karel; Collins, V Peter; Aronica, Eleonora; Varlet, Pascale; Puget, Stephanie; Dufour, Christelle; Grill, Jacques; Figarella-Branger, Dominique; Wolter, Marietta; Schuhmann, Martin U; Shalaby, Tarek; Grotzer, Michael; van Meter, Timothy; Monoranu, Camelia-Maria; Felsberg, Jörg; Reifenberger, Guido; Snuderl, Matija; Forrester, Lynn Ann; Koster, Jan; Versteeg, Rogier; Volckmann, Richard; van Sluis, Peter; Wolf, Stephan; Mikkelsen, Tom; Gajjar, Amar; Aldape, Kenneth; Moore, Andrew S; Taylor, Michael D; Jones, Chris; Jabado, Nada; Karajannis, Matthias A; Eils, Roland; Schlesner, Matthias; Lichter, Peter; von Deimling, Andreas; Pfister, Stefan M; Ellison, David W; Korshunov, Andrey; Kool, Marcel

2016-02-25

Primitive neuroectodermal tumors of the central nervous system (CNS-PNETs) are highly aggressive, poorly differentiated embryonal tumors occurring predominantly in young children but also affecting adolescents and adults. Herein, we demonstrate that a significant proportion of institutionally diagnosed CNS-PNETs display molecular profiles indistinguishable from those of various other well-defined CNS tumor entities, facilitating diagnosis and appropriate therapy for patients with these tumors. From the remaining fraction of CNS-PNETs, we identify four new CNS tumor entities, each associated with a recurrent genetic alteration and distinct histopathological and clinical features. These new molecular entities, designated "CNS neuroblastoma with FOXR2 activation (CNS NB-FOXR2)," "CNS Ewing sarcoma family tumor with CIC alteration (CNS EFT-CIC)," "CNS high-grade neuroepithelial tumor with MN1 alteration (CNS HGNET-MN1)," and "CNS high-grade neuroepithelial tumor with BCOR alteration (CNS HGNET-BCOR)," will enable meaningful clinical trials and the development of therapeutic strategies for patients affected by poorly differentiated CNS tumors. Copyright © 2016 Elsevier Inc. All rights reserved.

77 FR 31806 - Changes to Implement Micro Entity Status for Paying Patent Fees

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-30

... legislative history of 35 U.S.C. 123 is clear that it is directed to a subset of small entities, namely... history do not, for example, contemplate a for-profit, large entity applicant becoming a ``micro entity... across government agencies and identified goals designed to promote innovation; (8) considered approaches...

Recognizing the Emotional Valence of Names: An ERP Study

ERIC Educational Resources Information Center

Wang, Lin; Zhu, Zude; Bastiaansen, Marcel; Hagoort, Peter; Yang, Yufang

2013-01-01

Unlike common nouns, person names refer to unique entities and generally have a referring function. We used event-related potentials to investigate the time course of identifying the emotional meaning of nouns and names. The emotional valence of names and nouns were manipulated separately. The results show early N1 effects in response to emotional…

LeadMine: a grammar and dictionary driven approach to entity recognition.

PubMed

Lowe, Daniel M; Sayle, Roger A

2015-01-01

Chemical entity recognition has traditionally been performed by machine learning approaches. Here we describe an approach using grammars and dictionaries. This approach has the advantage that the entities found can be directly related to a given grammar or dictionary, which allows the type of an entity to be known and, if an entity is misannotated, indicates which resource should be corrected. As recognition is driven by what is expected, if spelling errors occur, they can be corrected. Correcting such errors is highly useful when attempting to lookup an entity in a database or, in the case of chemical names, converting them to structures. Our system uses a mixture of expertly curated grammars and dictionaries, as well as dictionaries automatically derived from public resources. We show that the heuristics developed to filter our dictionary of trivial chemical names (from PubChem) yields a better performing dictionary than the previously published Jochem dictionary. Our final system performs post-processing steps to modify the boundaries of entities and to detect abbreviations. These steps are shown to significantly improve performance (2.6% and 4.0% F1-score respectively). Our complete system, with incremental post-BioCreative workshop improvements, achieves 89.9% precision and 85.4% recall (87.6% F1-score) on the CHEMDNER test set. Grammar and dictionary approaches can produce results at least as good as the current state of the art in machine learning approaches. While machine learning approaches are commonly thought of as "black box" systems, our approach directly links the output entities to the input dictionaries and grammars. Our approach also allows correction of errors in detected entities, which can assist with entity resolution.

The International Society of Urological Pathology (ISUP) Vancouver Classification of Renal Neoplasia.

PubMed

Srigley, John R; Delahunt, Brett; Eble, John N; Egevad, Lars; Epstein, Jonathan I; Grignon, David; Hes, Ondrej; Moch, Holger; Montironi, Rodolfo; Tickoo, Satish K; Zhou, Ming; Argani, Pedram

2013-10-01

The classification working group of the International Society of Urological Pathology consensus conference on renal neoplasia was in charge of making recommendations regarding additions and changes to the current World Health Organization Classification of Renal Tumors (2004). Members of the group performed an exhaustive literature review, assessed the results of the preconference survey and participated in the consensus conference discussion and polling activities. On the basis of the above inputs, there was consensus that 5 entities should be recognized as new distinct epithelial tumors within the classification system: tubulocystic renal cell carcinoma (RCC), acquired cystic disease-associated RCC, clear cell (tubulo) papillary RCC, the MiT family translocation RCCs (in particular t(6;11) RCC), and hereditary leiomyomatosis RCC syndrome-associated RCC. In addition, there are 3 rare carcinomas that were considered as emerging or provisional new entities: thyroid-like follicular RCC; succinate dehydrogenase B deficiency-associated RCC; and ALK translocation RCC. Further reports of these entities are required to better understand the nature and behavior of these highly unusual tumors. There were a number of new concepts and suggested modifications to the existing World Health Organization 2004 categories. Within the clear cell RCC group, it was agreed upon that multicystic clear cell RCC is best considered as a neoplasm of low malignant potential. There was agreement that subtyping of papillary RCC is of value and that the oncocytic variant of papillary RCC should not be considered as a distinct entity. The hybrid oncocytic chromophobe tumor, which is an indolent tumor that occurs in 3 settings, namely Birt-Hogg-Dubé Syndrome, renal oncocytosis, and as a sporadic neoplasm, was placed, for the time being, within the chromophobe RCC category. Recent advances related to collecting duct carcinoma, renal medullary carcinoma, and mucinous spindle cell and tubular RCC

CheNER: a tool for the identification of chemical entities and their classes in biomedical literature.

PubMed

Usié, Anabel; Cruz, Joaquim; Comas, Jorge; Solsona, Francesc; Alves, Rui

2015-01-01

Small chemical molecules regulate biological processes at the molecular level. Those molecules are often involved in causing or treating pathological states. Automatically identifying such molecules in biomedical text is difficult due to both, the diverse morphology of chemical names and the alternative types of nomenclature that are simultaneously used to describe them. To address these issues, the last BioCreAtIvE challenge proposed a CHEMDNER task, which is a Named Entity Recognition (NER) challenge that aims at labelling different types of chemical names in biomedical text. To address this challenge we tested various approaches to recognizing chemical entities in biomedical documents. These approaches range from linear Conditional Random Fields (CRFs) to a combination of CRFs with regular expression and dictionary matching, followed by a post-processing step to tag those chemical names in a corpus of Medline abstracts. We named our best performing systems CheNER. We evaluate the performance of the various approaches using the F-score statistics. Higher F-scores indicate better performance. The highest F-score we obtain in identifying unique chemical entities is 72.88%. The highest F-score we obtain in identifying all chemical entities is 73.07%. We also evaluate the F-Score of combining our system with ChemSpot, and find an increase from 72.88% to 73.83%. CheNER presents a valid alternative for automated annotation of chemical entities in biomedical documents. In addition, CheNER may be used to derive new features to train newer methods for tagging chemical entities. CheNER can be downloaded from http://metres.udl.cat and included in text annotation pipelines.

LeadMine: a grammar and dictionary driven approach to entity recognition

PubMed Central

2015-01-01

Background Chemical entity recognition has traditionally been performed by machine learning approaches. Here we describe an approach using grammars and dictionaries. This approach has the advantage that the entities found can be directly related to a given grammar or dictionary, which allows the type of an entity to be known and, if an entity is misannotated, indicates which resource should be corrected. As recognition is driven by what is expected, if spelling errors occur, they can be corrected. Correcting such errors is highly useful when attempting to lookup an entity in a database or, in the case of chemical names, converting them to structures. Results Our system uses a mixture of expertly curated grammars and dictionaries, as well as dictionaries automatically derived from public resources. We show that the heuristics developed to filter our dictionary of trivial chemical names (from PubChem) yields a better performing dictionary than the previously published Jochem dictionary. Our final system performs post-processing steps to modify the boundaries of entities and to detect abbreviations. These steps are shown to significantly improve performance (2.6% and 4.0% F1-score respectively). Our complete system, with incremental post-BioCreative workshop improvements, achieves 89.9% precision and 85.4% recall (87.6% F1-score) on the CHEMDNER test set. Conclusions Grammar and dictionary approaches can produce results at least as good as the current state of the art in machine learning approaches. While machine learning approaches are commonly thought of as "black box" systems, our approach directly links the output entities to the input dictionaries and grammars. Our approach also allows correction of errors in detected entities, which can assist with entity resolution. PMID:25810776

41 CFR 102-173.50 - What is the naming convention for States?

Code of Federal Regulations, 2014 CFR

2014-01-01

...-INTERNET GOV DOMAIN Registration § 102-173.50 What is the naming convention for States? (a) To register any second-level domain within dot-gov, State government entities must register the full State name or clearly indicate the State postal code within the name. Examples of acceptable names include virginia.gov...

41 CFR 102-173.50 - What is the naming convention for States?

Code of Federal Regulations, 2011 CFR

2011-01-01

...-INTERNET GOV DOMAIN Registration § 102-173.50 What is the naming convention for States? (a) To register any second-level domain within dot-gov, State government entities must register the full State name or clearly indicate the State postal code within the name. Examples of acceptable names include virginia.gov...

41 CFR 102-173.50 - What is the naming convention for States?

Code of Federal Regulations, 2010 CFR

2010-07-01

...-INTERNET GOV DOMAIN Registration § 102-173.50 What is the naming convention for States? (a) To register any second-level domain within dot-gov, State government entities must register the full State name or clearly indicate the State postal code within the name. Examples of acceptable names include virginia.gov...

41 CFR 102-173.50 - What is the naming convention for States?

Code of Federal Regulations, 2013 CFR

2013-07-01

...-INTERNET GOV DOMAIN Registration § 102-173.50 What is the naming convention for States? (a) To register any second-level domain within dot-gov, State government entities must register the full State name or clearly indicate the State postal code within the name. Examples of acceptable names include virginia.gov...

41 CFR 102-173.50 - What is the naming convention for States?

Code of Federal Regulations, 2012 CFR

2012-01-01

...-INTERNET GOV DOMAIN Registration § 102-173.50 What is the naming convention for States? (a) To register any second-level domain within dot-gov, State government entities must register the full State name or clearly indicate the State postal code within the name. Examples of acceptable names include virginia.gov...

Building a protein name dictionary from full text: a machine learning term extraction approach.

PubMed

Shi, Lei; Campagne, Fabien

2005-04-07

The majority of information in the biological literature resides in full text articles, instead of abstracts. Yet, abstracts remain the focus of many publicly available literature data mining tools. Most literature mining tools rely on pre-existing lexicons of biological names, often extracted from curated gene or protein databases. This is a limitation, because such databases have low coverage of the many name variants which are used to refer to biological entities in the literature. We present an approach to recognize named entities in full text. The approach collects high frequency terms in an article, and uses support vector machines (SVM) to identify biological entity names. It is also computationally efficient and robust to noise commonly found in full text material. We use the method to create a protein name dictionary from a set of 80,528 full text articles. Only 8.3% of the names in this dictionary match SwissProt description lines. We assess the quality of the dictionary by studying its protein name recognition performance in full text. This dictionary term lookup method compares favourably to other published methods, supporting the significance of our direct extraction approach. The method is strong in recognizing name variants not found in SwissProt.

Building a protein name dictionary from full text: a machine learning term extraction approach

PubMed Central

Shi, Lei; Campagne, Fabien

2005-01-01

Background The majority of information in the biological literature resides in full text articles, instead of abstracts. Yet, abstracts remain the focus of many publicly available literature data mining tools. Most literature mining tools rely on pre-existing lexicons of biological names, often extracted from curated gene or protein databases. This is a limitation, because such databases have low coverage of the many name variants which are used to refer to biological entities in the literature. Results We present an approach to recognize named entities in full text. The approach collects high frequency terms in an article, and uses support vector machines (SVM) to identify biological entity names. It is also computationally efficient and robust to noise commonly found in full text material. We use the method to create a protein name dictionary from a set of 80,528 full text articles. Only 8.3% of the names in this dictionary match SwissProt description lines. We assess the quality of the dictionary by studying its protein name recognition performance in full text. Conclusion This dictionary term lookup method compares favourably to other published methods, supporting the significance of our direct extraction approach. The method is strong in recognizing name variants not found in SwissProt. PMID:15817129

Classifying Web Pages by Using Knowledge Bases for Entity Retrieval

NASA Astrophysics Data System (ADS)

Kiritani, Yusuke; Ma, Qiang; Yoshikawa, Masatoshi

In this paper, we propose a novel method to classify Web pages by using knowledge bases for entity search, which is a kind of typical Web search for information related to a person, location or organization. First, we map a Web page to entities according to the similarities between the page and the entities. Various methods for computing such similarity are applied. For example, we can compute the similarity between a given page and a Wikipedia article describing a certain entity. The frequency of an entity appearing in the page is another factor used in computing the similarity. Second, we construct a directed acyclic graph, named PEC graph, based on the relations among Web pages, entities, and categories, by referring to YAGO, a knowledge base built on Wikipedia and WordNet. Finally, by analyzing the PEC graph, we classify Web pages into categories. The results of some preliminary experiments validate the methods proposed in this paper.

Categorizing entities by common role.

PubMed

Goldwater, Micah B; Markman, Arthur B

2011-04-01

Many categories group together entities that play a common role across situations. For example, guest and host refer to complementary roles in visiting situations and, thus, are role-governed categories (A. B. Markman & Stilwell, Journal of Experiment & Theoretical Artificial Intelligence, 13, 329-358, 2001). However, categorizing an entity by role is one of many possible classification strategies. This article examines factors that promote role-governed categorization over thematic-relation-based categorization (Lin & Murphy, Journal of Experimental Psychology: General, 130, 3-28, 2001). In Experiments 1a and 1b, we demonstrate that the use of novel category labels facilitates role-governed categorization. In Experiments 2a and 2b, we demonstrate that analogical comparison facilitates role-governed categorization. In Experiments 1b and 2b, we show that these facilitatory factors induce a general sensitivity to role information, as opposed to only promoting role-governed categorization on an item-by-item basis.

Evaluation and Cross-Comparison of Lexical Entities of Biological Interest (LexEBI)

PubMed Central

Rebholz-Schuhmann, Dietrich; Kim, Jee-Hyub; Yan, Ying; Dixit, Abhishek; Friteyre, Caroline; Hoehndorf, Robert; Backofen, Rolf; Lewin, Ian

2013-01-01

Motivation Biomedical entities, their identifiers and names, are essential in the representation of biomedical facts and knowledge. In the same way, the complete set of biomedical and chemical terms, i.e. the biomedical “term space” (the “Lexeome”), forms a key resource to achieve the full integration of the scientific literature with biomedical data resources: any identified named entity can immediately be normalized to the correct database entry. This goal does not only require that we are aware of all existing terms, but would also profit from knowing all their senses and their semantic interpretation (ambiguities, nestedness). Result This study compiles a resource for lexical terms of biomedical interest in a standard format (called “LexEBI”), determines the overall number of terms, their reuse in different resources and the nestedness of terms. LexEBI comprises references for protein and gene entries and their term variants and chemical entities amongst other terms. In addition, disease terms have been identified from Medline and PubmedCentral and added to LexEBI. Our analysis demonstrates that the baseforms of terms from the different semantic types show only little polysemous use. Nonetheless, the term variants of protein and gene names (PGNs) frequently contain species mentions, which should have been avoided according to protein annotation guidelines. Furthermore, the protein and gene entities as well as the chemical entities, both do comprise enzymes leading to hierarchical polysemy, and a large portion of PGNs make reference to a chemical entity. Altogether, according to our analysis based on the Medline distribution, 401,869 unique PGNs in the documents contain a reference to 25,022 chemical entities, 3,125 disease terms or 1,576 species mentions. Conclusion LexEBI delivers the complete biomedical and chemical Lexeome in a standardized representation (http://www.ebi.ac.uk/Rebholz-srv/LexEBI/). The resource provides the disease terms as open

Feature generation and representations for protein-protein interaction classification.

PubMed

Lan, Man; Tan, Chew Lim; Su, Jian

2009-10-01

Automatic detecting protein-protein interaction (PPI) relevant articles is a crucial step for large-scale biological database curation. The previous work adopted POS tagging, shallow parsing and sentence splitting techniques, but they achieved worse performance than the simple bag-of-words representation. In this paper, we generated and investigated multiple types of feature representations in order to further improve the performance of PPI text classification task. Besides the traditional domain-independent bag-of-words approach and the term weighting methods, we also explored other domain-dependent features, i.e. protein-protein interaction trigger keywords, protein named entities and the advanced ways of incorporating Natural Language Processing (NLP) output. The integration of these multiple features has been evaluated on the BioCreAtIvE II corpus. The experimental results showed that both the advanced way of using NLP output and the integration of bag-of-words and NLP output improved the performance of text classification. Specifically, in comparison with the best performance achieved in the BioCreAtIvE II IAS, the feature-level and classifier-level integration of multiple features improved the performance of classification 2.71% and 3.95%, respectively.

Developing a hybrid dictionary-based bio-entity recognition technique.

PubMed

Song, Min; Yu, Hwanjo; Han, Wook-Shin

2015-01-01

Bio-entity extraction is a pivotal component for information extraction from biomedical literature. The dictionary-based bio-entity extraction is the first generation of Named Entity Recognition (NER) techniques. This paper presents a hybrid dictionary-based bio-entity extraction technique. The approach expands the bio-entity dictionary by combining different data sources and improves the recall rate through the shortest path edit distance algorithm. In addition, the proposed technique adopts text mining techniques in the merging stage of similar entities such as Part of Speech (POS) expansion, stemming, and the exploitation of the contextual cues to further improve the performance. The experimental results show that the proposed technique achieves the best or at least equivalent performance among compared techniques, GENIA, MESH, UMLS, and combinations of these three resources in F-measure. The results imply that the performance of dictionary-based extraction techniques is largely influenced by information resources used to build the dictionary. In addition, the edit distance algorithm shows steady performance with three different dictionaries in precision whereas the context-only technique achieves a high-end performance with three difference dictionaries in recall.

Developing a hybrid dictionary-based bio-entity recognition technique

PubMed Central

2015-01-01

Background Bio-entity extraction is a pivotal component for information extraction from biomedical literature. The dictionary-based bio-entity extraction is the first generation of Named Entity Recognition (NER) techniques. Methods This paper presents a hybrid dictionary-based bio-entity extraction technique. The approach expands the bio-entity dictionary by combining different data sources and improves the recall rate through the shortest path edit distance algorithm. In addition, the proposed technique adopts text mining techniques in the merging stage of similar entities such as Part of Speech (POS) expansion, stemming, and the exploitation of the contextual cues to further improve the performance. Results The experimental results show that the proposed technique achieves the best or at least equivalent performance among compared techniques, GENIA, MESH, UMLS, and combinations of these three resources in F-measure. Conclusions The results imply that the performance of dictionary-based extraction techniques is largely influenced by information resources used to build the dictionary. In addition, the edit distance algorithm shows steady performance with three different dictionaries in precision whereas the context-only technique achieves a high-end performance with three difference dictionaries in recall. PMID:26043907

Using Ontology Fingerprints to disambiguate gene name entities in the biomedical literature

PubMed Central

Chen, Guocai; Zhao, Jieyi; Cohen, Trevor; Tao, Cui; Sun, Jingchun; Xu, Hua; Bernstam, Elmer V.; Lawson, Andrew; Zeng, Jia; Johnson, Amber M.; Holla, Vijaykumar; Bailey, Ann M.; Lara-Guerra, Humberto; Litzenburger, Beate; Meric-Bernstam, Funda; Jim Zheng, W.

2015-01-01

Ambiguous gene names in the biomedical literature are a barrier to accurate information extraction. To overcome this hurdle, we generated Ontology Fingerprints for selected genes that are relevant for personalized cancer therapy. These Ontology Fingerprints were used to evaluate the association between genes and biomedical literature to disambiguate gene names. We obtained 93.6% precision for the test gene set and 80.4% for the area under a receiver-operating characteristics curve for gene and article association. The core algorithm was implemented using a graphics processing unit-based MapReduce framework to handle big data and to improve performance. We conclude that Ontology Fingerprints can help disambiguate gene names mentioned in text and analyse the association between genes and articles. Database URL: http://www.ontologyfingerprint.org PMID:25858285

New daily persistent headache: An evolving entity.

PubMed

Uniyal, Ravi; Paliwal, Vimal Kumar; Anand, Sucharita; Ambesh, Paurush

2018-01-01

New daily persistent headache (NDPH) is characterized by an abrupt onset of headache that becomes a daily entity, is unremitting and continuous from the onset, and lasts for more than 3 months. Dr Walter Vanast first described NDPH in the year 1986. Originally, it was proposed as a chronic daily headache but it was placed under "other primary headaches" in the International Classification of Headache Disorder Second Edition (ICHD 2nd edition). However, with evolving literature and better understanding of its clinical characteristics, it was classified as a "chronic daily headache" in the ICHD 3 rd edition beta. There are still many knowledge-gaps regarding the underlying cause, pathophysiology, natural history and treatment of NDPH. This review tries to revisit the entity and discusses the current status of understanding regarding NDPH.

Using Ontology Fingerprints to disambiguate gene name entities in the biomedical literature.

PubMed

Chen, Guocai; Zhao, Jieyi; Cohen, Trevor; Tao, Cui; Sun, Jingchun; Xu, Hua; Bernstam, Elmer V; Lawson, Andrew; Zeng, Jia; Johnson, Amber M; Holla, Vijaykumar; Bailey, Ann M; Lara-Guerra, Humberto; Litzenburger, Beate; Meric-Bernstam, Funda; Jim Zheng, W

2015-01-01

Ambiguous gene names in the biomedical literature are a barrier to accurate information extraction. To overcome this hurdle, we generated Ontology Fingerprints for selected genes that are relevant for personalized cancer therapy. These Ontology Fingerprints were used to evaluate the association between genes and biomedical literature to disambiguate gene names. We obtained 93.6% precision for the test gene set and 80.4% for the area under a receiver-operating characteristics curve for gene and article association. The core algorithm was implemented using a graphics processing unit-based MapReduce framework to handle big data and to improve performance. We conclude that Ontology Fingerprints can help disambiguate gene names mentioned in text and analyse the association between genes and articles. Database URL: http://www.ontologyfingerprint.org © The Author(s) 2015. Published by Oxford University Press.

2 CFR 170.110 - Types of entities to which this part applies.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 2 Grants and Agreements 1 2013-01-01 2013-01-01 false Types of entities to which this part applies...) Apply for or receive agency awards; or (2) Receive subawards under those awards. (b) Exceptions. (1... his or her name). (2) None of the requirements regarding reporting names and total compensation of an...

2 CFR 170.110 - Types of entities to which this part applies.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 2 Grants and Agreements 1 2012-01-01 2012-01-01 false Types of entities to which this part applies...) Apply for or receive agency awards; or (2) Receive subawards under those awards. (b) Exceptions. (1... his or her name). (2) None of the requirements regarding reporting names and total compensation of an...

12 CFR 602.24 - Responses to demands served on non-FCA employees or entities.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Responses to demands served on non-FCA employees or entities. 602.24 Section 602.24 Banks and Banking FARM CREDIT ADMINISTRATION ADMINISTRATIVE... Not a Named Party § 602.24 Responses to demands served on non-FCA employees or entities. If you are...

Scientific names of organisms: attribution, rights, and licensing

PubMed Central

2014-01-01

Background As biological disciplines extend into the ‘big data’ world, they will need a names-based infrastructure to index and interconnect distributed data. The infrastructure must have access to all names of all organisms if it is to manage all information. Those who compile lists of species hold different views as to the intellectual property rights that apply to the lists. This creates uncertainty that impedes the development of a much-needed infrastructure for sharing biological data in the digital world. Findings The laws in the United States of America and European Union are consistent with the position that scientific names of organisms and their compilation in checklists, classifications or taxonomic revisions are not subject to copyright. Compilations of names, such as classifications or checklists, are not creative in the sense of copyright law. Many content providers desire credit for their efforts. Conclusions A ‘blue list’ identifies elements of checklists, classifications and monographs to which intellectual property rights do not apply. To promote sharing, authors of taxonomic content, compilers, intermediaries, and aggregators should receive citable recognition for their contributions, with the greatest recognition being given to the originating authors. Mechanisms for achieving this are discussed. PMID:24495358

Principles for ecological classification

Treesearch

Dennis H. Grossman; Patrick Bourgeron; Wolf-Dieter N. Busch; David T. Cleland; William Platts; G. Ray; C. Robins; Gary Roloff

1999-01-01

The principal purpose of any classification is to relate common properties among different entities to facilitate understanding of evolutionary and adaptive processes. In the context of this volume, it is to facilitate ecosystem stewardship, i.e., to help support ecosystem conservation and management objectives.

What is in a name? Is food addiction a misnomer?

PubMed

Vella, Shae-Leigh; Pai, Nagesh

2017-02-01

Recently interest in the phenomenon of food addiction has increased substantially since the inclusion of gambling disorder in the DSM-5. However the phenomenon of food addiction remains controversial and the designation continues to lack clear consideration. Few researchers have offered an explicit theoretical definition of the phenomenon which is fundamental; as it not only pertains to the aetiology it also directs research and management of the phenomenon. Therefore this review explores 'what is in a name'? Specifically possible aetiologies of food addiction, eating addiction and food addiction as an eating disorder are reviewed and the potential DSM-5 classification espoused. It is evident that the phenomenon requires further research and evaluation in order to delineate whether the phenomenon constitutes a disorder and if the phenomenon is found to be a valid entity the most appropriate designation. As it is too early to draw definitive conclusions regarding the concept all plausible designations and the associated aetiologies require further investigation. Copyright © 2016 Elsevier B.V. All rights reserved.

Update from the 4th Edition of the World Health Organization Classification of Head and Neck Tumours: Tumors of the Salivary Gland.

PubMed

Seethala, Raja R; Stenman, Göran

2017-03-01

The salivary gland section in the 4th edition of the World Health Organization classification of head and neck tumors features the description and inclusion of several entities, the most significant of which is represented by (mammary analogue) secretory carcinoma. This entity was extracted mainly from acinic cell carcinoma based on recapitulation of breast secretory carcinoma and a shared ETV6-NTRK3 gene fusion. Also new is the subsection of "Other epithelial lesions," for which key entities include sclerosing polycystic adenosis and intercalated duct hyperplasia. Many entities have been compressed into their broader categories given clinical and morphologic similarities, or transitioned to a different grouping as was the case with low-grade cribriform cystadenocarcinoma reclassified as intraductal carcinoma (with the applied qualifier of low-grade). Specific grade has been removed from the names of the salivary gland entities such as polymorphous adenocarcinoma, providing pathologists flexibility in assigning grade and allowing for recognition of a broader spectrum within an entity. Cribriform adenocarcinoma of (minor) salivary gland origin continues to be divisive in terms of whether it should be recognized as a distinct category. This chapter also features new key concepts such as high-grade transformation. The new paradigm of translocations and gene fusions being common in salivary gland tumors is featured heavily in this chapter.

31 CFR 598.408 - Alleged change in ownership or control of an entity designated as a specially designated...

Code of Federal Regulations, 2010 CFR

2010-07-01

... of capital; and contracts evidencing the sale of the entity to its new owners. (b) Any continuing... narcotics trafficker could lead to designation of the purchaser. Mere change in name of an entity will not...

Geographic names of the Antarctic

USGS Publications Warehouse

,; ,; ,; ,; Alberts, Fred G.

1995-01-01

This gazetteer contains 12,710 names approved by the United States Board on Geographic Names and the Secretary of the Interior for features in Antarctica and the area extending northward to the Antarctic Convergence. Included in this geographic area, the Antarctic region, are the off-lying South Shetland Islands, the South Orkney Islands, the South Sandwich Islands, South Georgia, Bouvetøya, Heard Island, and the Balleny Islands. These names have been approved for use by U.S. Government agencies. Their use by the Antarctic specialist and the public is highly recommended for the sake of accuracy and uniformity. This publication, which supersedes previous Board gazetteers or lists for the area, contains names approved as recently as December 1994. The basic name coverage of this gazetteer corresponds to that of maps at the scale of 1:250,000 or larger for coastal Antarctica, the off-lying islands, and isolated mountains and ranges of the continent. Much of the interior of Antarctica is a featureless ice plateau. That area has been mapped at a smaller scale and is nearly devoid of toponyms. All of the names are for natural features, such as mountains, glaciers, peninsulas, capes, bays, islands, and subglacial entities. The names of scientific stations have not been listed alphabetically, but they may appear in the texts of some decisions. For the names of submarine features, reference should be made to the Gazetteer of Undersea Features, 4th edition, U.S. Board on Geographic Names, 1990.

Determining similarity of scientific entities in annotation datasets

PubMed Central

Palma, Guillermo; Vidal, Maria-Esther; Haag, Eric; Raschid, Louiqa; Thor, Andreas

2015-01-01

Linked Open Data initiatives have made available a diversity of scientific collections where scientists have annotated entities in the datasets with controlled vocabulary terms from ontologies. Annotations encode scientific knowledge, which is captured in annotation datasets. Determining relatedness between annotated entities becomes a building block for pattern mining, e.g. identifying drug–drug relationships may depend on the similarity of the targets that interact with each drug. A diversity of similarity measures has been proposed in the literature to compute relatedness between a pair of entities. Each measure exploits some knowledge including the name, function, relationships with other entities, taxonomic neighborhood and semantic knowledge. We propose a novel general-purpose annotation similarity measure called ‘AnnSim’ that measures the relatedness between two entities based on the similarity of their annotations. We model AnnSim as a 1–1 maximum weight bipartite match and exploit properties of existing solvers to provide an efficient solution. We empirically study the performance of AnnSim on real-world datasets of drugs and disease associations from clinical trials and relationships between drugs and (genomic) targets. Using baselines that include a variety of measures, we identify where AnnSim can provide a deeper understanding of the semantics underlying the relatedness of a pair of entities or where it could lead to predicting new links or identifying potential novel patterns. Although AnnSim does not exploit knowledge or properties of a particular domain, its performance compares well with a variety of state-of-the-art domain-specific measures. Database URL: http://www.yeastgenome.org/ PMID:25725057

Entity recognition in the biomedical domain using a hybrid approach.

PubMed

Basaldella, Marco; Furrer, Lenz; Tasso, Carlo; Rinaldi, Fabio

2017-11-09

This article describes a high-recall, high-precision approach for the extraction of biomedical entities from scientific articles. The approach uses a two-stage pipeline, combining a dictionary-based entity recognizer with a machine-learning classifier. First, the OGER entity recognizer, which has a bias towards high recall, annotates the terms that appear in selected domain ontologies. Subsequently, the Distiller framework uses this information as a feature for a machine learning algorithm to select the relevant entities only. For this step, we compare two different supervised machine-learning algorithms: Conditional Random Fields and Neural Networks. In an in-domain evaluation using the CRAFT corpus, we test the performance of the combined systems when recognizing chemicals, cell types, cellular components, biological processes, molecular functions, organisms, proteins, and biological sequences. Our best system combines dictionary-based candidate generation with Neural-Network-based filtering. It achieves an overall precision of 86% at a recall of 60% on the named entity recognition task, and a precision of 51% at a recall of 49% on the concept recognition task. These results are to our knowledge the best reported so far in this particular task.

Breast cancer - one term, many entities?

PubMed

Bertos, Nicholas R; Park, Morag

2011-10-01

Breast cancer, rather than constituting a monolithic entity, comprises heterogeneous tumors with different clinical characteristics, disease courses, and responses to specific treatments. Tumor-intrinsic features, including classical histological and immunopathological classifications as well as more recently described molecular subtypes, separate breast tumors into multiple groups. Tumor-extrinsic features, including microenvironmental configuration, also have prognostic significance and further expand the list of tumor-defining variables. A better understanding of the features underlying heterogeneity, as well as of the mechanisms and consequences of their interactions, is essential to improve targeting of existing therapies and to develop novel agents addressing specific combinations of features.

A study of active learning methods for named entity recognition in clinical text.

PubMed

Chen, Yukun; Lasko, Thomas A; Mei, Qiaozhu; Denny, Joshua C; Xu, Hua

2015-12-01

Named entity recognition (NER), a sequential labeling task, is one of the fundamental tasks for building clinical natural language processing (NLP) systems. Machine learning (ML) based approaches can achieve good performance, but they often require large amounts of annotated samples, which are expensive to build due to the requirement of domain experts in annotation. Active learning (AL), a sample selection approach integrated with supervised ML, aims to minimize the annotation cost while maximizing the performance of ML-based models. In this study, our goal was to develop and evaluate both existing and new AL methods for a clinical NER task to identify concepts of medical problems, treatments, and lab tests from the clinical notes. Using the annotated NER corpus from the 2010 i2b2/VA NLP challenge that contained 349 clinical documents with 20,423 unique sentences, we simulated AL experiments using a number of existing and novel algorithms in three different categories including uncertainty-based, diversity-based, and baseline sampling strategies. They were compared with the passive learning that uses random sampling. Learning curves that plot performance of the NER model against the estimated annotation cost (based on number of sentences or words in the training set) were generated to evaluate different active learning and the passive learning methods and the area under the learning curve (ALC) score was computed. Based on the learning curves of F-measure vs. number of sentences, uncertainty sampling algorithms outperformed all other methods in ALC. Most diversity-based methods also performed better than random sampling in ALC. To achieve an F-measure of 0.80, the best method based on uncertainty sampling could save 66% annotations in sentences, as compared to random sampling. For the learning curves of F-measure vs. number of words, uncertainty sampling methods again outperformed all other methods in ALC. To achieve 0.80 in F-measure, in comparison to random

Identifying interactions between chemical entities in biomedical text.

PubMed

Lamurias, Andre; Ferreira, João D; Couto, Francisco M

2014-10-23

Interactions between chemical compounds described in biomedical text can be of great importance to drug discovery and design, as well as pharmacovigilance. We developed a novel system, \\"Identifying Interactions between Chemical Entities\\" (IICE), to identify chemical interactions described in text. Kernel-based Support Vector Machines first identify the interactions and then an ensemble classifier validates and classifies the type of each interaction. This relation extraction module was evaluated with the corpus released for the DDI Extraction task of SemEval 2013, obtaining results comparable to state-of-the-art methods for this type of task. We integrated this module with our chemical named entity recognition module and made the whole system available as a web tool at www.lasige.di.fc.ul.pt/webtools/iice.

Identifying interactions between chemical entities in biomedical text.

PubMed

Lamurias, Andre; Ferreira, João D; Couto, Francisco M

2014-12-01

Interactions between chemical compounds described in biomedical text can be of great importance to drug discovery and design, as well as pharmacovigilance. We developed a novel system, "Identifying Interactions between Chemical Entities" (IICE), to identify chemical interactions described in text. Kernel-based Support Vector Machines first identify the interactions and then an ensemble classifier validates and classifies the type of each interaction. This relation extraction module was evaluated with the corpus released for the DDI Extraction task of SemEval 2013, obtaining results comparable to stateof- the-art methods for this type of task. We integrated this module with our chemical named entity recognition module and made the whole system available as a web tool at www.lasige.di.fc.ul.pt/webtools/iice.

29 CFR 510.24 - Governmental entities eligible for minimum wage phase-in.

Code of Federal Regulations, 2010 CFR

2010-07-01

.... 510.24 Section 510.24 Labor Regulations Relating to Labor (Continued) WAGE AND HOUR DIVISION... FAIR LABOR STANDARDS ACT IN PUERTO RICO Classification of Industries § 510.24 Governmental entities... engaged in one or more of the “traditional” functions listed in § 510.24 (a) or (b). All other employees...

Determining similarity of scientific entities in annotation datasets.

PubMed

Palma, Guillermo; Vidal, Maria-Esther; Haag, Eric; Raschid, Louiqa; Thor, Andreas

2015-01-01

Linked Open Data initiatives have made available a diversity of scientific collections where scientists have annotated entities in the datasets with controlled vocabulary terms from ontologies. Annotations encode scientific knowledge, which is captured in annotation datasets. Determining relatedness between annotated entities becomes a building block for pattern mining, e.g. identifying drug-drug relationships may depend on the similarity of the targets that interact with each drug. A diversity of similarity measures has been proposed in the literature to compute relatedness between a pair of entities. Each measure exploits some knowledge including the name, function, relationships with other entities, taxonomic neighborhood and semantic knowledge. We propose a novel general-purpose annotation similarity measure called 'AnnSim' that measures the relatedness between two entities based on the similarity of their annotations. We model AnnSim as a 1-1 maximum weight bipartite match and exploit properties of existing solvers to provide an efficient solution. We empirically study the performance of AnnSim on real-world datasets of drugs and disease associations from clinical trials and relationships between drugs and (genomic) targets. Using baselines that include a variety of measures, we identify where AnnSim can provide a deeper understanding of the semantics underlying the relatedness of a pair of entities or where it could lead to predicting new links or identifying potential novel patterns. Although AnnSim does not exploit knowledge or properties of a particular domain, its performance compares well with a variety of state-of-the-art domain-specific measures. Database URL: http://www.yeastgenome.org/ © The Author(s) 2015. Published by Oxford University Press.

Mixed-phenotype acute leukemia: state-of-the-art of the diagnosis, classification and treatment.

PubMed

Cernan, Martin; Szotkowski, Tomas; Pikalova, Zuzana

2017-09-01

Mixed-phenotype acute leukemia (MPAL) is a heterogeneous group of hematopoietic malignancies in which blasts show markers of multiple developmental lineages and cannot be clearly classified as acute myeloid or lymphoblastic leukemias. Historically, various names and classifications were used for this rare entity accounting for 2-5% of all acute leukemias depending on the diagnostic criterias used. The currently valid classification of myeloid neoplasms and acute leukemia published by the World Health Organization (WHO) in 2016 refers to this group of diseases as MPAL. Because adverse cytogenetic abnormalities are frequently present, MPAL is generally considered a disease with a poor prognosis. Knowledge of its treatment is limited to retrospective analyses of small patient cohorts. So far, no treatment recommendations verified by prospective studies have been published. The reported data suggest that induction therapy for acute lymphoblastic leukemia followed by allogeneic hematopoietic cell transplantation is more effective than induction therapy for acute myeloid leukemia or consolidation chemotherapy. The establishment of cooperative groups and international registries based on the recent WHO criterias are required to ensure further progress in understanding and treatment of MPAL. This review summarizes current knowledge on the diagnosis, classification, prognosis and treatment of MPAL patients.

Naming, labeling, and packaging of pharmaceuticals.

PubMed

Kenagy, J W; Stein, G C

2001-11-01

The problem of medical errors associated with the naming, labeling, and packaging of pharmaceuticals is discussed. Sound-alike and look-alike drug names and packages can lead pharmacists and nurses to unintended interchanges of drugs that can result in patient injury or death. The existing medication-use system is flawed because its safety depends on human perfection. Simplicity, standardization, differentiation, lack of duplication, and unambiguous communication are human factors concepts that are relevant to the medication-use process. These principles have often been ignored in drug naming, labeling, and packaging. Instead, current methods are based on long-standing commercial considerations and bureaucratic procedures. The process for naming a marketable drug is lengthy and complex and involves submission of a new chemical entity and patent application, generic naming, brand naming, FDA review, and final approval. Drug companies seek the fastest possible approval and may believe that the incremental benefit of human factors evaluation is small. "Trade dress" is the concept that underlies labeling and packaging issues for the drug industry. Drug companies are resistant to changing trade dress and brand names. Although a variety of private-sector organizations have called for reforms in drug naming, labeling, and packaging standards have been proposed, the problem remains. Drug names, labels, and packages are not selected and designed in accordance with human factors principles. FDA standards do not require application of these principles, the drug industry has struggled with change, and private-sector initiatives have had only limited success.

32 CFR 2001.21 - Original classification.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 32 National Defense 6 2010-07-01 2010-07-01 false Original classification. 2001.21 Section 2001.21... Markings § 2001.21 Original classification. (a) Primary markings. At the time of original classification... authority. The name and position, or personal identifier, of the original classification authority shall...

"New drug" designations for new therapeutic entities: new active substance, new chemical entity, new biological entity, new molecular entity.

PubMed

Branch, Sarah K; Agranat, Israel

2014-11-13

This Perspective addresses ambiguities in designations of "new drugs" intended as new therapeutic entities (NTEs). Designation of an NTE as a new drug is significant, as it may confer regulatory exclusivity, an important incentive for development of novel compounds. Such designations differ between jurisdictions according to their drug laws and drug regulations. Chemical, biological, and innovative drugs are addressed in turn. The terms new chemical entity (NCE), new molecular entity (NME), new active substance (NAS), and new biological entity (NBE) as applied in worldwide jurisdictions are clarified. Differences between them are explored through case studies showing why new drugs have different periods of exclusivity in different jurisdictions or none at all. Finally, this Perspective recommends that in future, for the purpose of new drug compilations, NME is used for a new chemical drug, NBE for a new biological drug, and the combined designation NTE should refer to either an NME or an NBE.

PKDE4J: Entity and relation extraction for public knowledge discovery.

PubMed

Song, Min; Kim, Won Chul; Lee, Dahee; Heo, Go Eun; Kang, Keun Young

2015-10-01

Due to an enormous number of scientific publications that cannot be handled manually, there is a rising interest in text-mining techniques for automated information extraction, especially in the biomedical field. Such techniques provide effective means of information search, knowledge discovery, and hypothesis generation. Most previous studies have primarily focused on the design and performance improvement of either named entity recognition or relation extraction. In this paper, we present PKDE4J, a comprehensive text-mining system that integrates dictionary-based entity extraction and rule-based relation extraction in a highly flexible and extensible framework. Starting with the Stanford CoreNLP, we developed the system to cope with multiple types of entities and relations. The system also has fairly good performance in terms of accuracy as well as the ability to configure text-processing components. We demonstrate its competitive performance by evaluating it on many corpora and found that it surpasses existing systems with average F-measures of 85% for entity extraction and 81% for relation extraction. Copyright © 2015 Elsevier Inc. All rights reserved.

Abstracts versus Full Texts and Patents: A Quantitative Analysis of Biomedical Entities

NASA Astrophysics Data System (ADS)

Müller, Bernd; Klinger, Roman; Gurulingappa, Harsha; Mevissen, Heinz-Theodor; Hofmann-Apitius, Martin; Fluck, Juliane; Friedrich, Christoph M.

In information retrieval, named entity recognition gives the opportunity to apply semantic search in domain specific corpora. Recently, more full text patents and journal articles became freely available. As the information distribution amongst the different sections is unknown, an analysis of the diversity is of interest.

Integrated Bio-Entity Network: A System for Biological Knowledge Discovery

PubMed Central

Bell, Lindsey; Chowdhary, Rajesh; Liu, Jun S.; Niu, Xufeng; Zhang, Jinfeng

2011-01-01

A significant part of our biological knowledge is centered on relationships between biological entities (bio-entities) such as proteins, genes, small molecules, pathways, gene ontology (GO) terms and diseases. Accumulated at an increasing speed, the information on bio-entity relationships is archived in different forms at scattered places. Most of such information is buried in scientific literature as unstructured text. Organizing heterogeneous information in a structured form not only facilitates study of biological systems using integrative approaches, but also allows discovery of new knowledge in an automatic and systematic way. In this study, we performed a large scale integration of bio-entity relationship information from both databases containing manually annotated, structured information and automatic information extraction of unstructured text in scientific literature. The relationship information we integrated in this study includes protein–protein interactions, protein/gene regulations, protein–small molecule interactions, protein–GO relationships, protein–pathway relationships, and pathway–disease relationships. The relationship information is organized in a graph data structure, named integrated bio-entity network (IBN), where the vertices are the bio-entities and edges represent their relationships. Under this framework, graph theoretic algorithms can be designed to perform various knowledge discovery tasks. We designed breadth-first search with pruning (BFSP) and most probable path (MPP) algorithms to automatically generate hypotheses—the indirect relationships with high probabilities in the network. We show that IBN can be used to generate plausible hypotheses, which not only help to better understand the complex interactions in biological systems, but also provide guidance for experimental designs. PMID:21738677

A Statistical Model for Multilingual Entity Detection and Tracking

DTIC Science & Technology

2004-01-01

tomatic Content Extraction ( ACE ) evaluation achieved top-tier results in all three evaluation languages. 1 Introduction Detecting entities, whether named...of com- bining the detected mentions into groups of references to the same object. The work presented here is motivated by the ACE eval- uation...Entropy (MaxEnt henceforth) (Berger et al., 1996) and Robust Risk Minimization (RRM henceforth) 1For a description of the ACE program see http

Enterprise Standard Industrial Classification Manual. 1974.

ERIC Educational Resources Information Center

Executive Office of the President, Washington, DC. Statistical Policy Div.

This classification is presented to provide a standard for use with statistics about enterprises (i.e., companies, rather than their individual establishments) by kind of economic activity. The enterprise unit consists of all establishments under common direct or indirect ownership. It is defined to include all entities, including subsidiaries,…

12 CFR 1229.12 - Procedures related to capital classification and other actions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Procedures related to capital classification and other actions. 1229.12 Section 1229.12 Banks and Banking FEDERAL HOUSING FINANCE AGENCY ENTITY REGULATIONS CAPITAL CLASSIFICATIONS AND PROMPT CORRECTIVE ACTION Federal Home Loan Banks § 1229.12 Procedures...

Human-machine interaction to disambiguate entities in unstructured text and structured datasets

NASA Astrophysics Data System (ADS)

Ward, Kevin; Davenport, Jack

2017-05-01

Creating entity network graphs is a manual, time consuming process for an intelligence analyst. Beyond the traditional big data problems of information overload, individuals are often referred to by multiple names and shifting titles as they advance in their organizations over time which quickly makes simple string or phonetic alignment methods for entities insufficient. Conversely, automated methods for relationship extraction and entity disambiguation typically produce questionable results with no way for users to vet results, correct mistakes or influence the algorithm's future results. We present an entity disambiguation tool, DRADIS, which aims to bridge the gap between human-centric and machinecentric methods. DRADIS automatically extracts entities from multi-source datasets and models them as a complex set of attributes and relationships. Entities are disambiguated across the corpus using a hierarchical model executed in Spark allowing it to scale to operational sized data. Resolution results are presented to the analyst complete with sourcing information for each mention and relationship allowing analysts to quickly vet the correctness of results as well as correct mistakes. Corrected results are used by the system to refine the underlying model allowing analysts to optimize the general model to better deal with their operational data. Providing analysts with the ability to validate and correct the model to produce a system they can trust enables them to better focus their time on producing higher quality analysis products.

Using nanoinformatics methods for automatically identifying relevant nanotoxicology entities from the literature.

PubMed

García-Remesal, Miguel; García-Ruiz, Alejandro; Pérez-Rey, David; de la Iglesia, Diana; Maojo, Víctor

2013-01-01

Nanoinformatics is an emerging research field that uses informatics techniques to collect, process, store, and retrieve data, information, and knowledge on nanoparticles, nanomaterials, and nanodevices and their potential applications in health care. In this paper, we have focused on the solutions that nanoinformatics can provide to facilitate nanotoxicology research. For this, we have taken a computational approach to automatically recognize and extract nanotoxicology-related entities from the scientific literature. The desired entities belong to four different categories: nanoparticles, routes of exposure, toxic effects, and targets. The entity recognizer was trained using a corpus that we specifically created for this purpose and was validated by two nanomedicine/nanotoxicology experts. We evaluated the performance of our entity recognizer using 10-fold cross-validation. The precisions range from 87.6% (targets) to 93.0% (routes of exposure), while recall values range from 82.6% (routes of exposure) to 87.4% (toxic effects). These results prove the feasibility of using computational approaches to reliably perform different named entity recognition (NER)-dependent tasks, such as for instance augmented reading or semantic searches. This research is a "proof of concept" that can be expanded to stimulate further developments that could assist researchers in managing data, information, and knowledge at the nanolevel, thus accelerating research in nanomedicine.

NeuroNames: an ontology for the BrainInfo portal to neuroscience on the web.

PubMed

Bowden, Douglas M; Song, Evan; Kosheleva, Julia; Dubach, Mark F

2012-01-01

BrainInfo ( http://braininfo.org ) is a growing portal to neuroscientific information on the Web. It is indexed by NeuroNames, an ontology designed to compensate for ambiguities in neuroanatomical nomenclature. The 20-year old ontology continues to evolve toward the ideal of recognizing all names of neuroanatomical entities and accommodating all structural concepts about which neuroscientists communicate, including multiple concepts of entities for which neuroanatomists have yet to determine the best or 'true' conceptualization. To make the definitions of structural concepts unambiguous and terminologically consistent we created a 'default vocabulary' of unique structure names selected from existing terminology. We selected standard names by criteria designed to maximize practicality for use in verbal communication as well as computerized knowledge management. The ontology of NeuroNames accommodates synonyms and homonyms of the standard terms in many languages. It defines complex structures as models composed of primary structures, which are defined in unambiguous operational terms. NeuroNames currently relates more than 16,000 names in eight languages to some 2,500 neuroanatomical concepts. The ontology is maintained in a relational database with three core tables: Names, Concepts and Models. BrainInfo uses NeuroNames to index information by structure, to interpret users' queries and to clarify terminology on remote web pages. NeuroNames is a resource vocabulary of the NLM's Unified Medical Language System (UMLS, 2011) and the basis for the brain regions component of NIFSTD (NeuroLex, 2011). The current version has been downloaded to hundreds of laboratories for indexing data and linking to BrainInfo, which attracts some 400 visitors/day, downloading 2,000 pages/day.

Naming the newly found landforms on Venus

NASA Technical Reports Server (NTRS)

Batson, R. M.; Russell, J. F.

1991-01-01

The mapping of Venus is unique in the history of cartigraphy; never has so much territory been discovered and mapped in so short a period of time. Therefore, in the interest of international scientific communication, there is a unique urgency to the development of a system of names for surface features on Venus. The process began with the naming of features seen on radar images taken from Earth and continued through mapping expeditions of the U.S. and U.S.S.R. However, the Magellan Mission resolves features twenty-five times smaller than those mapped previously, and its radar data will cover an area nearly equivalent to that of the continents and the sea-floors of the Earth combined. The International Astronomical Union (IAU) was charged with the formal endorsement of names of features on the planets. Proposed names are collected, approved, and applied through the IAU Working Group for Planetary System Nomenclature (WGPSN) and its task groups, prior to IAU approval by the IAU General Assembly. Names approved by the WGPSN and its task groups, prior to final approval may be used on published maps and articles, provided that their provisional nature is stipulated. The IAU has established themes for the names to be used on each of the planets; names of historical and mythological women are used on Venus. Names of political entities and those identified with active religions are not acceptable, and a person must have been deceased for three years or more to be considered. Any interested person may propose a name for consideration by the IAU.

A practicable approach for periodontal classification

PubMed Central

Mittal, Vishnu; Bhullar, Raman Preet K.; Bansal, Rachita; Singh, Karanprakash; Bhalodi, Anand; Khinda, Paramjit K.

2013-01-01

The Diagnosis and classification of periodontal diseases has remained a dilemma since long. Two distinct concepts have been used to define diseases: Essentialism and Nominalism. Essentialistic concept implies the real existence of disease whereas; nominalistic concept states that the names of diseases are the convenient way of stating concisely the endpoint of a diagnostic process. It generally advances from assessment of symptoms and signs toward knowledge of causation and gives a feasible option to name the disease for which etiology is either unknown or it is too complex to access in routine clinical practice. Various classifications have been proposed by the American Academy of Periodontology (AAP) in 1986, 1989 and 1999. The AAP 1999 classification is among the most widely used classification. But this classification also has demerits which provide impediment for its use in day to day practice. Hence a classification and diagnostic system is required which can help the clinician to access the patient's need and provide a suitable treatment which is in harmony with the diagnosis for that particular case. Here is an attempt to propose a practicable classification and diagnostic system of periodontal diseases for better treatment outcome. PMID:24379855

Naming and outline of Dothideomycetes-2014 including proposals for the protection or suppression of generic names.

PubMed

Wijayawardene, Nalin N; Crous, Pedro W; Kirk, Paul M; Hawksworth, David L; Boonmee, Saranyaphat; Braun, Uwe; Dai, Dong-Qin; D'souza, Melvina J; Diederich, Paul; Dissanayake, Asha; Doilom, Mingkhuan; Hongsanan, Singang; Jones, E B Gareth; Groenewald, Johannes Z; Jayawardena, Ruvishika; Lawrey, James D; Liu, Jian-Kui; Lücking, Robert; Madrid, Hugo; Manamgoda, Dimuthu S; Muggia, Lucia; Nelsen, Matthew P; Phookamsak, Rungtiwa; Suetrong, Satinee; Tanaka, Kazuaki; Thambugala, Kasun M; Wanasinghe, Dhanushka N; Wikee, Saowanee; Zhang, Ying; Aptroot, André; Ariyawansa, H A; Bahkali, Ali H; Bhat, D Jayarama; Gueidan, Cécile; Chomnunti, Putarak; De Hoog, G Sybren; Knudsen, Kerry; Li, Wen-Jing; McKenzie, Eric H C; Miller, Andrew N; Phillips, Alan J L; Piątek, Marcin; Raja, Huzefa A; Shivas, Roger S; Slippers, Bernad; Taylor, Joanne E; Tian, Qing; Wang, Yong; Woudenberg, Joyce H C; Cai, Lei; Jaklitsch, Walter M; Hyde, Kevin D

2014-11-01

Article 59.1, of the International Code of Nomenclature for Algae, Fungi, and Plants (ICN; Melbourne Code), which addresses the nomenclature of pleomorphic fungi, became effective from 30 July 2011. Since that date, each fungal species can have one nomenclaturally correct name in a particular classification. All other previously used names for this species will be considered as synonyms. The older generic epithet takes priority over the younger name. Any widely used younger names proposed for use, must comply with Art. 57.2 and their usage should be approved by the Nomenclature Committee for Fungi (NCF). In this paper, we list all genera currently accepted by us in Dothideomycetes (belonging to 23 orders and 110 families), including pleomorphic and nonpleomorphic genera. In the case of pleomorphic genera, we follow the rulings of the current ICN and propose single generic names for future usage. The taxonomic placements of 1261 genera are listed as an outline. Protected names and suppressed names for 34 pleomorphic genera are listed separately. Notes and justifications are provided for possible proposed names after the list of genera. Notes are also provided on recent advances in our understanding of asexual and sexual morph linkages in Dothideomycetes . A phylogenetic tree based on four gene analyses supported 23 orders and 75 families, while 35 families still lack molecular data.

Naming and outline of Dothideomycetes–2014 including proposals for the protection or suppression of generic names

PubMed Central

Wijayawardene, Nalin N.; Crous, Pedro W.; Kirk, Paul M.; Hawksworth, David L.; Boonmee, Saranyaphat; Braun, Uwe; Dai, Dong-Qin; D’souza, Melvina J.; Diederich, Paul; Dissanayake, Asha; Doilom, Mingkhuan; Hongsanan, Singang; Jones, E. B.Gareth; Groenewald, Johannes Z.; Jayawardena, Ruvishika; Lawrey, James D.; Liu, Jian-Kui; Lücking, Robert; Madrid, Hugo; Manamgoda, Dimuthu S.; Muggia, Lucia; Nelsen, Matthew P.; Phookamsak, Rungtiwa; Suetrong, Satinee; Tanaka, Kazuaki; Thambugala, Kasun M.; Wanasinghe, Dhanushka N.; Wikee, Saowanee; Zhang, Ying; Aptroot, André; Ariyawansa, H. A.; Bahkali, Ali H.; Bhat, D. Jayarama; Gueidan, Cécile; Chomnunti, Putarak; De Hoog, G. Sybren; Knudsen, Kerry; Li, Wen-Jing; McKenzie, Eric H. C.; Miller, Andrew N.; Phillips, Alan J. L.; Piątek, Marcin; Raja, Huzefa A.; Shivas, Roger S.; Slippers, Bernad; Taylor, Joanne E.; Tian, Qing; Wang, Yong; Woudenberg, Joyce H. C.; Cai, Lei; Jaklitsch, Walter M.

2016-01-01

Article 59.1, of the International Code of Nomenclature for Algae, Fungi, and Plants (ICN; Melbourne Code), which addresses the nomenclature of pleomorphic fungi, became effective from 30 July 2011. Since that date, each fungal species can have one nomenclaturally correct name in a particular classification. All other previously used names for this species will be considered as synonyms. The older generic epithet takes priority over the younger name. Any widely used younger names proposed for use, must comply with Art. 57.2 and their usage should be approved by the Nomenclature Committee for Fungi (NCF). In this paper, we list all genera currently accepted by us in Dothideomycetes (belonging to 23 orders and 110 families), including pleomorphic and nonpleomorphic genera. In the case of pleomorphic genera, we follow the rulings of the current ICN and propose single generic names for future usage. The taxonomic placements of 1261 genera are listed as an outline. Protected names and suppressed names for 34 pleomorphic genera are listed separately. Notes and justifications are provided for possible proposed names after the list of genera. Notes are also provided on recent advances in our understanding of asexual and sexual morph linkages in Dothideomycetes. A phylogenetic tree based on four gene analyses supported 23 orders and 75 families, while 35 families still lack molecular data. PMID:27284275

Ethnicity and Population Structure in Personal Naming Networks

PubMed Central

Mateos, Pablo; Longley, Paul A.; O'Sullivan, David

2011-01-01

Personal naming practices exist in all human groups and are far from random. Rather, they continue to reflect social norms and ethno-cultural customs that have developed over generations. As a consequence, contemporary name frequency distributions retain distinct geographic, social and ethno-cultural patterning that can be exploited to understand population structure in human biology, public health and social science. Previous attempts to detect and delineate such structure in large populations have entailed extensive empirical analysis of naming conventions in different parts of the world without seeking any general or automated methods of population classification by ethno-cultural origin. Here we show how ‘naming networks’, constructed from forename-surname pairs of a large sample of the contemporary human population in 17 countries, provide a valuable representation of cultural, ethnic and linguistic population structure around the world. This innovative approach enriches and adds value to automated population classification through conventional national data sources such as telephone directories and electoral registers. The method identifies clear social and ethno-cultural clusters in such naming networks that extend far beyond the geographic areas in which particular names originated, and that are preserved even after international migration. Moreover, one of the most striking findings of this approach is that these clusters simply ‘emerge’ from the aggregation of millions of individual decisions on parental naming practices for their children, without any prior knowledge introduced by the researcher. Our probabilistic approach to community assignment, both at city level as well as at a global scale, helps to reveal the degree of isolation, integration or overlap between human populations in our rapidly globalising world. As such, this work has important implications for research in population genetics, public health, and social science adding new

Spatial distribution and influence factors of interprovincial terrestrial physical geographical names in China

NASA Astrophysics Data System (ADS)

Zhang, S.; Wang, Y.; Ju, H.

2017-12-01

The interprovincial terrestrial physical geographical entities are the key areas of regional integrated management. Based on toponomy dictionaries and different thematic maps, the attributes and the spatial extent of the interprovincial terrestrial physical geographical names (ITPGN, including terrain ITPGN and water ITPGN) were extracted. The coefficient of variation and Moran's I were combined together to measure the spatial variation and spatial association of ITPGN. The influencing factors of the distribution of ITPGN and the implications for the regional management were further discussed. The results showed that 11325 ITPGN were extracted, including 7082 terrain ITPGN and 4243 water ITPGN. Hunan Province had the largest number of ITPGN in China, and Shanghai had the smallest number. The spatial variance of the terrain ITPGN was larger than that of the water ITPGN, and the ITPGN showed a significant agglomeration phenomenon in the southern part of China. Further analysis showed that the number of ITPGN was positively related with the relative elevation and the population where the relative elevation was lower than 2000m and the population was less than 50 million. But the number of ITPGN showed a negative relationship with the two factors when their values became larger, indicating a large number of unnamed entities existed in complex terrain areas and a decreasing number of terrestrial physical geographical entities in densely populated area. Based on these analysis, we suggest the government take the ITPGN as management units to realize a balance development between different parts of the entities and strengthen the geographical names census and the nomination of unnamed interprovincial physical geographical entities. This study also demonstrated that the methods of literature survey, coefficient of variation and Moran's I can be combined to enhance the understanding of the spatial pattern of ITPGN.

Primary intraosseous squamous cell carcinoma in odontogenic keratocyst: A rare entity

PubMed Central

Saxena, Chitrapriya; Aggarwal, Pooja; Wadhwan, Vijay; Bansal, Vishal

2015-01-01

Squamous cell carcinoma (SCC) arising from the wall of an odontogenic cyst (also known as primary intraosseous carcinoma) is a rare tumor which occurs only in jaw bones. This tumor was first described by Loos in 1913 as a central epidermoid carcinoma of the jaw. Primary intraosseous carcinomas (PIOC) may theoretically arise from the lining of an odontogenic cyst or de novo from presumed odontogenic cell rests. According to the new histological classification of tumors of the World Health Organization, odontogenic keratocyst is nowadays considered a specific odontogenic tumor and the PIOC derived from it is considered as a specific entity which is different from other PIOCs derived from the odontogenic cysts. The following report describes a case of such extremely rare entity that is primary intraosseous SCC of the mandible derived from an OKC in a 60-year-old male patient with brief review of literature. PMID:26980976

Mayo Clinic/Renal Pathology Society Consensus Report on Pathologic Classification, Diagnosis, and Reporting of GN.

PubMed

Sethi, Sanjeev; Haas, Mark; Markowitz, Glen S; D'Agati, Vivette D; Rennke, Helmut G; Jennette, J Charles; Bajema, Ingeborg M; Alpers, Charles E; Chang, Anthony; Cornell, Lynn D; Cosio, Fernando G; Fogo, Agnes B; Glassock, Richard J; Hariharan, Sundaram; Kambham, Neeraja; Lager, Donna J; Leung, Nelson; Mengel, Michael; Nath, Karl A; Roberts, Ian S; Rovin, Brad H; Seshan, Surya V; Smith, Richard J H; Walker, Patrick D; Winearls, Christopher G; Appel, Gerald B; Alexander, Mariam P; Cattran, Daniel C; Casado, Carmen Avila; Cook, H Terence; De Vriese, An S; Radhakrishnan, Jai; Racusen, Lorraine C; Ronco, Pierre; Fervenza, Fernando C

2016-05-01

Renal pathologists and nephrologists met on February 20, 2015 to establish an etiology/pathogenesis-based system for classification and diagnosis of GN, with a major aim of standardizing the kidney biopsy report of GN. On the basis of etiology/pathogenesis, GN is classified into the following five pathogenic types, each with specific disease entities: immune-complex GN, pauci-immune GN, antiglomerular basement membrane GN, monoclonal Ig GN, and C3 glomerulopathy. The pathogenesis-based classification forms the basis of the kidney biopsy report. To standardize the report, the diagnosis consists of a primary diagnosis and a secondary diagnosis. The primary diagnosis should include the disease entity/pathogenic type (if disease entity is not known) followed in order by pattern of injury (mixed patterns may be present); score/grade/class for disease entities, such as IgA nephropathy, lupus nephritis, and ANCA GN; and additional features as detailed herein. A pattern diagnosis as the sole primary diagnosis is not recommended. Secondary diagnoses should be reported separately and include coexisting lesions that do not form the primary diagnosis. Guidelines for the report format, light microscopy, immunofluorescence microscopy, electron microscopy, and ancillary studies are also provided. In summary, this consensus report emphasizes a pathogenesis-based classification of GN and provides guidelines for the standardized reporting of GN. Copyright © 2016 by the American Society of Nephrology.

[Cystic renal neoplasms. New entities and molecular findings].

PubMed

Moch, H

2010-10-01

Renal neoplasms with dominant cysts represent a broad spectrum of known as well as novel renal tumor entities. Established renal tumors with dominant cysts include cystic nephroma, mixed epithelial and stromal tumor, synovial sarcoma and multilocular cystic renal cancer (WHO classification 2004). Novel tumor types have recently been reported, which are also characterized by marked cyst formation. Examples are tubulocystic renal cancer and renal cancer in end-stage renal disease. These tumors are very likely to be included in a future WHO classification due to their characteristic phenotype and molecular features. Cysts and clear cell renal cell carcinoma frequently coexist in the kidneys of patients with von Hippel-Lindau disease. Cysts are also a component of many sporadic clear cell renal cell carcinomas. Multilocular cystic renal cell carcinoma is composed almost exclusively of cysts and is regarded as a specific subtype of clear cell renal cancer. Recent molecular findings suggest that clear cell renal cancer may develop via a cyst-dependent mechanism in von Hippel-Lindau syndrome as well as via cyst-independent molecular pathways in sporadic clear cell renal cancer.

78 FR 78514 - Designation of One Individual and Three Entities Pursuant to Executive Order

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-26

... DEPARTMENT OF THE TREASURY Office of Foreign Assets Control Designation of One Individual and... publishing the name of one individual and three entities whose property and interests in property are blocked..., Security, or Stability of Burma.'' DATES: The designation by the Director of OFAC of the one individual and...

Indonesian name matching using machine learning supervised approach

NASA Astrophysics Data System (ADS)

Alifikri, Mohamad; Arif Bijaksana, Moch.

2018-03-01

Most existing name matching methods are developed for English language and so they cover the characteristics of this language. Up to this moment, there is no specific one has been designed and implemented for Indonesian names. The purpose of this thesis is to develop Indonesian name matching dataset as a contribution to academic research and to propose suitable feature set by utilizing combination of context of name strings and its permute-winkler score. Machine learning classification algorithms is taken as the method for performing name matching. Based on the experiments, by using tuned Random Forest algorithm and proposed features, there is an improvement of matching performance by approximately 1.7% and it is able to reduce until 70% misclassification result of the state of the arts methods. This improving performance makes the matching system more effective and reduces the risk of misclassified matches.

Naming Lunar Mare Basalts: Quo Vadimus Redux

NASA Astrophysics Data System (ADS)

Ryder, G.

1999-01-01

Nearly a decade ago, I noted that the nomenclature of lunar mare basalts was inconsistent, complicated, and arcane. I suggested that this reflected both the limitations of our understanding of the basalts, and the piecemeal progression made in lunar science by the nature of the Apollo missions. Although the word "classification" is commonly attached to various schemes of mare basalt nomenclature, there is still no classification of mare basalts that has any fundamental grounding. We remain basically at a classification of the first kind in the terms of Shand; that is, things have names. Quoting John Stuart Mill, Shand discussed classification of the second kind: "The ends of scientific classification are best answered when the objects are formed into groups respecting which a greater number of propositions can be made, and those propositions more important than could be made respecting any other groups into which the same things could be distributed." Here I repeat some of the main contents of my discussion from a decade ago, and add a further discussion based on events of the last decade. A necessary first step of sample studies that aims to understand lunar mare basalt processes is to associate samples with one another as members of the same igneous event, such as a single eruption lava flow, or differentiation event. This has been fairly successful, and discrete suites have been identified at all mare sites, members that are eruptively related to each other but not to members of other suites. These eruptive members have been given site-specific labels, e.g., Luna24 VLT, Apollo 11 hi-K, A12 olivine basalts, and Apollo 15 Green Glass C. This is classification of the first kind, but is not a useful classification of any other kind. At a minimum, a classification is inclusive (all objects have a place) and exclusive (all objects have only one place). The answer to "How should rocks be classified?" is far from trivial, for it demands a fundamental choice about nature

The 2016 revision of the World Health Organization classification of lymphoid neoplasms | Center for Cancer Research

Cancer.gov

A revision of the nearly 8-year-old World Health Organization classification of the lymphoid neoplasms and the accompanying monograph is being published. It reflects a consensus among hematopathologists, geneticists, and clinicians regarding both updates to current entities as well as the addition of a limited number of new provisional entities.

Gimli: open source and high-performance biomedical name recognition

PubMed Central

2013-01-01

Background Automatic recognition of biomedical names is an essential task in biomedical information extraction, presenting several complex and unsolved challenges. In recent years, various solutions have been implemented to tackle this problem. However, limitations regarding system characteristics, customization and usability still hinder their wider application outside text mining research. Results We present Gimli, an open-source, state-of-the-art tool for automatic recognition of biomedical names. Gimli includes an extended set of implemented and user-selectable features, such as orthographic, morphological, linguistic-based, conjunctions and dictionary-based. A simple and fast method to combine different trained models is also provided. Gimli achieves an F-measure of 87.17% on GENETAG and 72.23% on JNLPBA corpus, significantly outperforming existing open-source solutions. Conclusions Gimli is an off-the-shelf, ready to use tool for named-entity recognition, providing trained and optimized models for recognition of biomedical entities from scientific text. It can be used as a command line tool, offering full functionality, including training of new models and customization of the feature set and model parameters through a configuration file. Advanced users can integrate Gimli in their text mining workflows through the provided library, and extend or adapt its functionalities. Based on the underlying system characteristics and functionality, both for final users and developers, and on the reported performance results, we believe that Gimli is a state-of-the-art solution for biomedical NER, contributing to faster and better research in the field. Gimli is freely available at http://bioinformatics.ua.pt/gimli. PMID:23413997

Assessment of Orthographic Similarity of Drugs Names between Iran and Overseas Using the Solar Model

PubMed Central

ABOLHASSANI, Nazanin; AKBARI SARI, Ali; RASHIDIAN, Arash; RASTEGARPANAH, Mansoor

2017-01-01

Background: The recognition of patient safety is now occupying a prominent place on the health policy agenda since medical errors can result in adverse events. The existence of confusing drug names is one of the most common causes of medication errors. In Iran, the General Office of Trademarks Registry (GOTR), for four years (2010–2014) was responsible for approving drug proprietary names. This study aimed to investigate the performance of the GOTR in terms of drug names orthographic similarity using the SOLAR model. Methods: First, 100 names were randomly selected from the GOTR’s database. Then, each name was searched through pharmaceutical websites including Martindale (the Complete Drug Reference published by Pharmaceutical Press), Drugs.com and Medicines Complete. Pair of drugs whose names look orthographically similar with different indications were identified. Then, the SOLAR model was utilized to determine orthographic similarity between all pair of drug names. Results: The mean of match values of these 100 pairs of drug was 77% indicating the high risk of similarity. The match value for most of the reviewed pairs (92%) was high (≥66%). This value was medium (≥ 33% and <66%) just for 8% of the pairs of drug. These results indicate high risk of confusion due to similarity of drug names. Conclusion: The stewardship of the GOTR in patient safety considerations is fundamentally problematic. Thus, as a best practice, we recommend that proprietary names of drugs be evaluated by an entity within the health system. While an entity within the health system should address patient safety considerations, the GOTR is responsible for intellectual property rights. PMID:29259940

Liberal Entity Extraction: Rapid Construction of Fine-Grained Entity Typing Systems.

PubMed

Huang, Lifu; May, Jonathan; Pan, Xiaoman; Ji, Heng; Ren, Xiang; Han, Jiawei; Zhao, Lin; Hendler, James A

2017-03-01

The ability of automatically recognizing and typing entities in natural language without prior knowledge (e.g., predefined entity types) is a major challenge in processing such data. Most existing entity typing systems are limited to certain domains, genres, and languages. In this article, we propose a novel unsupervised entity-typing framework by combining symbolic and distributional semantics. We start from learning three types of representations for each entity mention: general semantic representation, specific context representation, and knowledge representation based on knowledge bases. Then we develop a novel joint hierarchical clustering and linking algorithm to type all mentions using these representations. This framework does not rely on any annotated data, predefined typing schema, or handcrafted features; therefore, it can be quickly adapted to a new domain, genre, and/or language. Experiments on genres (news and discussion forum) show comparable performance with state-of-the-art supervised typing systems trained from a large amount of labeled data. Results on various languages (English, Chinese, Japanese, Hausa, and Yoruba) and domains (general and biomedical) demonstrate the portability of our framework.

Liberal Entity Extraction: Rapid Construction of Fine-Grained Entity Typing Systems

PubMed Central

Huang, Lifu; May, Jonathan; Pan, Xiaoman; Ji, Heng; Ren, Xiang; Han, Jiawei; Zhao, Lin; Hendler, James A.

2017-01-01

Abstract The ability of automatically recognizing and typing entities in natural language without prior knowledge (e.g., predefined entity types) is a major challenge in processing such data. Most existing entity typing systems are limited to certain domains, genres, and languages. In this article, we propose a novel unsupervised entity-typing framework by combining symbolic and distributional semantics. We start from learning three types of representations for each entity mention: general semantic representation, specific context representation, and knowledge representation based on knowledge bases. Then we develop a novel joint hierarchical clustering and linking algorithm to type all mentions using these representations. This framework does not rely on any annotated data, predefined typing schema, or handcrafted features; therefore, it can be quickly adapted to a new domain, genre, and/or language. Experiments on genres (news and discussion forum) show comparable performance with state-of-the-art supervised typing systems trained from a large amount of labeled data. Results on various languages (English, Chinese, Japanese, Hausa, and Yoruba) and domains (general and biomedical) demonstrate the portability of our framework. PMID:28328252

Relatedness-based Multi-Entity Summarization

PubMed Central

Gunaratna, Kalpa; Yazdavar, Amir Hossein; Thirunarayan, Krishnaprasad; Sheth, Amit; Cheng, Gong

2017-01-01

Representing world knowledge in a machine processable format is important as entities and their descriptions have fueled tremendous growth in knowledge-rich information processing platforms, services, and systems. Prominent applications of knowledge graphs include search engines (e.g., Google Search and Microsoft Bing), email clients (e.g., Gmail), and intelligent personal assistants (e.g., Google Now, Amazon Echo, and Apple’s Siri). In this paper, we present an approach that can summarize facts about a collection of entities by analyzing their relatedness in preference to summarizing each entity in isolation. Specifically, we generate informative entity summaries by selecting: (i) inter-entity facts that are similar and (ii) intra-entity facts that are important and diverse. We employ a constrained knapsack problem solving approach to efficiently compute entity summaries. We perform both qualitative and quantitative experiments and demonstrate that our approach yields promising results compared to two other stand-alone state-of-the-art entity summarization approaches. PMID:29051696

Detection of IUPAC and IUPAC-like chemical names.

PubMed

Klinger, Roman; Kolárik, Corinna; Fluck, Juliane; Hofmann-Apitius, Martin; Friedrich, Christoph M

2008-07-01

Chemical compounds like small signal molecules or other biological active chemical substances are an important entity class in life science publications and patents. Several representations and nomenclatures for chemicals like SMILES, InChI, IUPAC or trivial names exist. Only SMILES and InChI names allow a direct structure search, but in biomedical texts trivial names and Iupac like names are used more frequent. While trivial names can be found with a dictionary-based approach and in such a way mapped to their corresponding structures, it is not possible to enumerate all IUPAC names. In this work, we present a new machine learning approach based on conditional random fields (CRF) to find mentions of IUPAC and IUPAC-like names in scientific text as well as its evaluation and the conversion rate with available name-to-structure tools. We present an IUPAC name recognizer with an F(1) measure of 85.6% on a MEDLINE corpus. The evaluation of different CRF orders and offset conjunction orders demonstrates the importance of these parameters. An evaluation of hand-selected patent sections containing large enumerations and terms with mixed nomenclature shows a good performance on these cases (F(1) measure 81.5%). Remaining recognition problems are to detect correct borders of the typically long terms, especially when occurring in parentheses or enumerations. We demonstrate the scalability of our implementation by providing results from a full MEDLINE run. We plan to publish the corpora, annotation guideline as well as the conditional random field model as a UIMA component.

Enhancing of chemical compound and drug name recognition using representative tag scheme and fine-grained tokenization.

PubMed

Dai, Hong-Jie; Lai, Po-Ting; Chang, Yung-Chun; Tsai, Richard Tzong-Han

2015-01-01

The functions of chemical compounds and drugs that affect biological processes and their particular effect on the onset and treatment of diseases have attracted increasing interest with the advancement of research in the life sciences. To extract knowledge from the extensive literatures on such compounds and drugs, the organizers of BioCreative IV administered the CHEMical Compound and Drug Named Entity Recognition (CHEMDNER) task to establish a standard dataset for evaluating state-of-the-art chemical entity recognition methods. This study introduces the approach of our CHEMDNER system. Instead of emphasizing the development of novel feature sets for machine learning, this study investigates the effect of various tag schemes on the recognition of the names of chemicals and drugs by using conditional random fields. Experiments were conducted using combinations of different tokenization strategies and tag schemes to investigate the effects of tag set selection and tokenization method on the CHEMDNER task. This study presents the performance of CHEMDNER of three more representative tag schemes-IOBE, IOBES, and IOB12E-when applied to a widely utilized IOB tag set and combined with the coarse-/fine-grained tokenization methods. The experimental results thus reveal that the fine-grained tokenization strategy performance best in terms of precision, recall and F-scores when the IOBES tag set was utilized. The IOBES model with fine-grained tokenization yielded the best-F-scores in the six chemical entity categories other than the "Multiple" entity category. Nonetheless, no significant improvement was observed when a more representative tag schemes was used with the coarse or fine-grained tokenization rules. The best F-scores that were achieved using the developed system on the test dataset of the CHEMDNER task were 0.833 and 0.815 for the chemical documents indexing and the chemical entity mention recognition tasks, respectively. The results herein highlight the importance

#nowplaying Madonna: a large-scale evaluation on estimating similarities between music artists and between movies from microblogs.

PubMed

Schedl, Markus

2012-01-01

Different term weighting techniques such as [Formula: see text] or BM25 have been used intensely for manifold text-based information retrieval tasks. Their use for modeling term profiles for named entities and subsequent calculation of similarities between these named entities have been studied to a much smaller extent. The recent trend of microblogging made available massive amounts of information about almost every topic around the world. Therefore, microblogs represent a valuable source for text-based named entity modeling. In this paper, we present a systematic and comprehensive evaluation of different term weighting measures , normalization techniques , query schemes , index term sets , and similarity functions for the task of inferring similarities between named entities, based on data extracted from microblog posts . We analyze several thousand combinations of choices for the above mentioned dimensions, which influence the similarity calculation process, and we investigate in which way they impact the quality of the similarity estimates. Evaluation is performed using three real-world data sets: two collections of microblogs related to music artists and one related to movies. For the music collections, we present results of genre classification experiments using as benchmark genre information from allmusic.com. For the movie collection, we present results of multi-class classification experiments using as benchmark categories from IMDb. We show that microblogs can indeed be exploited to model named entity similarity with remarkable accuracy, provided the correct settings for the analyzed aspects are used. We further compare the results to those obtained when using Web pages as data source.

13 CFR 130.200 - Eligible entities.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 13 Business Credit and Assistance 1 2011-01-01 2011-01-01 false Eligible entities. 130.200 Section... CENTERS § 130.200 Eligible entities. (a) Recipient Organization. The following entities are eligible to... community or junior college; (5) An entity formed by two or more of the above entities; or (6) Any entity...

31 CFR 575.304 - Entity of the Government of Iraq; Iraqi Government entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity of the Government of Iraq; Iraqi Government entity. 575.304 Section 575.304 Money and Finance: Treasury Regulations Relating to... SANCTIONS REGULATIONS General Definitions § 575.304 Entity of the Government of Iraq; Iraqi Government...

Towards an Obesity-Cancer Knowledge Base: Biomedical Entity Identification and Relation Detection

PubMed Central

Lossio-Ventura, Juan Antonio; Hogan, William; Modave, François; Hicks, Amanda; Hanna, Josh; Guo, Yi; He, Zhe; Bian, Jiang

2017-01-01

Obesity is associated with increased risks of various types of cancer, as well as a wide range of other chronic diseases. On the other hand, access to health information activates patient participation, and improve their health outcomes. However, existing online information on obesity and its relationship to cancer is heterogeneous ranging from pre-clinical models and case studies to mere hypothesis-based scientific arguments. A formal knowledge representation (i.e., a semantic knowledge base) would help better organizing and delivering quality health information related to obesity and cancer that consumers need. Nevertheless, current ontologies describing obesity, cancer and related entities are not designed to guide automatic knowledge base construction from heterogeneous information sources. Thus, in this paper, we present methods for named-entity recognition (NER) to extract biomedical entities from scholarly articles and for detecting if two biomedical entities are related, with the long term goal of building a obesity-cancer knowledge base. We leverage both linguistic and statistical approaches in the NER task, which supersedes the state-of-the-art results. Further, based on statistical features extracted from the sentences, our method for relation detection obtains an accuracy of 99.3% and a f-measure of 0.993. PMID:28503356

Perspectives on Next Steps in Classification of Orofacial Pain – Part 2: Role of psychosocial factors

PubMed Central

Durham, Justin; Raphael, Karen G.; Benoliel, Rafael; Ceusters, Werner; Michelotti, Ambra; Ohrbach, Richard

2015-01-01

This paper was initiated by a symposium, in which the present authors contributed, organised by the International RDC/TMD Consortium Network in March 2013. The purpose of the paper is to review the status of biobehavioural research – both quantitative and qualitative – related to orofacial pain with respect to the etiology, pathophysiology, diagnosis and management of orofacial pain conditions, and how this information can optimally be used for developing a structured orofacial pain classification system for research. In particular, we address: representation of psychosocial entities in classification systems, use of qualitative research to identify and understand the full scope of psychosocial entities and their interaction, and the usage of classification system for guiding treatment. We then provide recommendations for addressing these problems, including how ontological principles can inform this process. PMID:26257252

31 CFR 800.211 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 800.211 Section 800.211 Money... FOREIGN PERSONS Definitions § 800.211 Entity. The term entity means any branch, partnership, group or sub... separate legal entity) operated by any one of the foregoing as a business undertaking in a particular...

Update on the integrated histopathological and genetic classification of medulloblastoma - a practical diagnostic guideline.

PubMed

Pietsch, Torsten; Haberler, Christine

The revised WHO classification of tumors of the CNS 2016 has introduced the concept of the integrated diagnosis. The definition of medulloblastoma entities now requires a combination of the traditional histological information with additional molecular/genetic features. For definition of the histopathological component of the medulloblastoma diagnosis, the tumors should be assigned to one of the four entities classic, desmoplastic/nodular (DNMB), extensive nodular (MBEN), or large cell/anaplastic (LC/A) medulloblastoma. The genetically defined component comprises the four entities WNT-activated, SHH-activated and TP53 wildtype, SHH-activated and TP53 mutant, or non-WNT/non-SHH medulloblastoma. Robust and validated methods are available to allow a precise diagnosis of these medulloblastoma entities according to the updated WHO classification, and for differential diagnostic purposes. A combination of immunohistochemical markers including β-catenin, Yap1, p75-NGFR, Otx2, and p53, in combination with targeted sequencing and copy number assessment such as FISH analysis for MYC genes allows a precise assignment of patients for risk-adapted stratification. It also allows comparison to results of study cohorts in the past and provides a robust basis for further treatment refinement.
.

[Definition and classification of pulmonary arterial hypertension].

PubMed

Nakanishi, Norifumi

2008-11-01

Pulmonary hypertension(PH) is a disorder that may occur either in the setting of a variety of underlying medical conditions or as a disease that uniquely affects the pulmonary vasculature. Because an accurate diagnosis of PH in a patient is essential to establish an effective treatment, a classification of PH has been helpful. The first classification, established at WHO Symposium in 1973, classified PH into groups based on the known cause and defined primary pulmonary hypertension (PPH) as a separate entity of unknown cause. In 1998, the second World Symposium on PPH was held in Evian. Evian classification introduced the concept of conditions that directly affected the pulmonary vasculature (i.e., PAH), which included PPH. In 2003, the third World Symposium on PAH convened in Venice. In Venice classification, the term 'PPH' was abandoned in favor of 'idiopathic' within the group of disease known as 'PAH'.

Exploring the Repeated Name Penalty and the Overt Pronoun Penalty in Spanish

ERIC Educational Resources Information Center

Gelormini-Lezama, Carlos

2018-01-01

Anaphoric expressions such as repeated names, overt pronouns, and null pronouns serve a major role in the creation and maintenance of discourse coherence. The felicitous use of an anaphoric expression is highly dependent on the discourse salience of the entity introduced by the antecedent. Gordon et al. ("Cogn Sci" 17:311-347, 1993)…

26 CFR 301.7701(i)-3 - Effective dates and duration of taxable mortgage pool classification.

Code of Federal Regulations, 2011 CFR

2011-04-01

... mortgage pool classification. 301.7701(i)-3 Section 301.7701(i)-3 Internal Revenue INTERNAL REVENUE SERVICE... § 301.7701(i)-3 Effective dates and duration of taxable mortgage pool classification. (a) Effective... connected to the entity's issuance of related debt obligations (as defined in paragraph (b)(3) of this...

78 FR 37664 - Identification of Entities Pursuant to the Iranian Transactions and Sanctions Regulations and...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-21

... Control (``OFAC'') is publishing the names of 38 entities identified as the Government of Iran under the... Government of Iran and Iranian Financial Institutions'' (the ``Order''). Section 1(a) of the Order blocks, with certain exceptions, all property and interests in property of the Government of Iran, including...

A database of natural products and chemical entities from marine habitat

PubMed Central

Babu, Padavala Ajay; Puppala, Suma Sree; Aswini, Satyavarapu Lakshmi; Vani, Metta Ramya; Kumar, Chinta Narasimha; Prasanna, Tallapragada

2008-01-01

Marine compound database consists of marine natural products and chemical entities, collected from various literature sources, which are known to possess bioactivity against human diseases. The database is constructed using html code. The 12 categories of 182 compounds are provided with the source, compound name, 2-dimensional structure, bioactivity and clinical trial information. The database is freely available online and can be accessed at http://www.progenebio.in/mcdb/index.htm PMID:19238254

Detection of IUPAC and IUPAC-like chemical names

PubMed Central

Klinger, Roman; Kolářik, Corinna; Fluck, Juliane; Hofmann-Apitius, Martin; Friedrich, Christoph M.

2008-01-01

Motivation: Chemical compounds like small signal molecules or other biological active chemical substances are an important entity class in life science publications and patents. Several representations and nomenclatures for chemicals like SMILES, InChI, IUPAC or trivial names exist. Only SMILES and InChI names allow a direct structure search, but in biomedical texts trivial names and Iupac like names are used more frequent. While trivial names can be found with a dictionary-based approach and in such a way mapped to their corresponding structures, it is not possible to enumerate all IUPAC names. In this work, we present a new machine learning approach based on conditional random fields (CRF) to find mentions of IUPAC and IUPAC-like names in scientific text as well as its evaluation and the conversion rate with available name-to-structure tools. Results: We present an IUPAC name recognizer with an F1 measure of 85.6% on a MEDLINE corpus. The evaluation of different CRF orders and offset conjunction orders demonstrates the importance of these parameters. An evaluation of hand-selected patent sections containing large enumerations and terms with mixed nomenclature shows a good performance on these cases (F1 measure 81.5%). Remaining recognition problems are to detect correct borders of the typically long terms, especially when occurring in parentheses or enumerations. We demonstrate the scalability of our implementation by providing results from a full MEDLINE run. Availability: We plan to publish the corpora, annotation guideline as well as the conditional random field model as a UIMA component. Contact: roman.klinger@scai.fraunhofer.de PMID:18586724

22 CFR 96.5 - Requirement that accrediting entity be a nonprofit or public entity.

Code of Federal Regulations, 2010 CFR

2010-04-01

... administering standards for entities providing child welfare services; or (b) A public entity (other than a... political subdivision, agency, or instrumentality thereof, that is responsible for licensing adoption agencies in a State and that has expertise in developing and administering standards for entities providing...

A stacked sequential learning method for investigator name recognition from web-based medical articles

NASA Astrophysics Data System (ADS)

Zhang, Xiaoli; Zou, Jie; Le, Daniel X.; Thoma, George

2010-01-01

"Investigator Names" is a newly required field in MEDLINE citations. It consists of personal names listed as members of corporate organizations in an article. Extracting investigator names automatically is necessary because of the increasing volume of articles reporting collaborative biomedical research in which a large number of investigators participate. In this paper, we present an SVM-based stacked sequential learning method in a novel application - recognizing named entities such as the first and last names of investigators from online medical journal articles. Stacked sequential learning is a meta-learning algorithm which can boost any base learner. It exploits contextual information by adding the predicted labels of the surrounding tokens as features. We apply this method to tag words in text paragraphs containing investigator names, and demonstrate that stacked sequential learning improves the performance of a nonsequential base learner such as an SVM classifier.

Cholangiocarcinoma: classification, diagnosis, staging, imaging features, and management.

PubMed

Oliveira, Irai S; Kilcoyne, Aoife; Everett, Jamie M; Mino-Kenudson, Mari; Harisinghani, Mukesh G; Ganesan, Karthik

2017-06-01

Cholangiocarcinoma is a relatively uncommon malignant neoplasm with poor prognosis. The distinction between extrahepatic and intrahepatic subtypes is important as epidemiological features, biologic and pathologic characteristics, and clinical course are different for both entities. This review study focuses on the role imaging plays in the diagnosis, classification, staging, and post-treatment assessment of cholangiocarcinoma.

Naming and recognizing famous faces in temporal lobe epilepsy.

PubMed

Glosser, G; Salvucci, A E; Chiaravalloti, N D

2003-07-08

To assess naming and recognition of faces of familiar famous people in patients with epilepsy before and after anterior temporal lobectomy (ATL). Color photographs of famous people were presented for naming and description to 63 patients with temporal lobe epilepsy (TLE) either before or after ATL and to 10 healthy age- and education-matched controls. Spontaneous naming of photographed famous people was impaired in all patient groups, but was most abnormal in patients who had undergone left ATL. When allowed to demonstrate knowledge of the famous faces through verbal descriptions, rather than naming, patients with left TLE, left ATL, and right TLE improved to normal levels, but patients with right ATL were still impaired, suggesting a new deficit in identifying famous faces. Naming of famous people was related to naming of other common objects, verbal memory, and perceptual discrimination of faces. Recognition of the identity of pictured famous people was more related to visuospatial perception and memory. Lesions in anterior regions of the right temporal lobe impair recognition of the identities of familiar faces, as well as the learning of new faces. Lesions in the left temporal lobe, especially in anterior regions, disrupt access to the names of known people, but do not affect recognition of the identities of famous faces. Results are consistent with the hypothesized role of lateralized anterior temporal lobe structures in facial recognition and naming of unique entities.

Extracting biomedical events from pairs of text entities

PubMed Central

2015-01-01

Background Huge amounts of electronic biomedical documents, such as molecular biology reports or genomic papers are generated daily. Nowadays, these documents are mainly available in the form of unstructured free texts, which require heavy processing for their registration into organized databases. This organization is instrumental for information retrieval, enabling to answer the advanced queries of researchers and practitioners in biology, medicine, and related fields. Hence, the massive data flow calls for efficient automatic methods of text-mining that extract high-level information, such as biomedical events, from biomedical text. The usual computational tools of Natural Language Processing cannot be readily applied to extract these biomedical events, due to the peculiarities of the domain. Indeed, biomedical documents contain highly domain-specific jargon and syntax. These documents also describe distinctive dependencies, making text-mining in molecular biology a specific discipline. Results We address biomedical event extraction as the classification of pairs of text entities into the classes corresponding to event types. The candidate pairs of text entities are recursively provided to a multiclass classifier relying on Support Vector Machines. This recursive process extracts events involving other events as arguments. Compared to joint models based on Markov Random Fields, our model simplifies inference and hence requires shorter training and prediction times along with lower memory capacity. Compared to usual pipeline approaches, our model passes over a complex intermediate problem, while making a more extensive usage of sophisticated joint features between text entities. Our method focuses on the core event extraction of the Genia task of BioNLP challenges yielding the best result reported so far on the 2013 edition. PMID:26201478

Update on the integrated histopathological and genetic classification of medulloblastoma – a practical diagnostic guideline

PubMed Central

Pietsch, Torsten; Haberler, Christine

2016-01-01

The revised WHO classification of tumors of the CNS 2016 has introduced the concept of the integrated diagnosis. The definition of medulloblastoma entities now requires a combination of the traditional histological information with additional molecular/genetic features. For definition of the histopathological component of the medulloblastoma diagnosis, the tumors should be assigned to one of the four entities classic, desmoplastic/nodular (DNMB), extensive nodular (MBEN), or large cell/anaplastic (LC/A) medulloblastoma. The genetically defined component comprises the four entities WNT-activated, SHH-activated and TP53 wildtype, SHH-activated and TP53 mutant, or non-WNT/non-SHH medulloblastoma. Robust and validated methods are available to allow a precise diagnosis of these medulloblastoma entities according to the updated WHO classification, and for differential diagnostic purposes. A combination of immunohistochemical markers including β-catenin, Yap1, p75-NGFR, Otx2, and p53, in combination with targeted sequencing and copy number assessment such as FISH analysis for MYC genes allows a precise assignment of patients for risk-adapted stratification. It also allows comparison to results of study cohorts in the past and provides a robust basis for further treatment refinement. PMID:27781424

A New Classification of the Dictyostelids.

PubMed

Sheikh, Sanea; Thulin, Mats; Cavender, James C; Escalante, Ricardo; Kawakami, Shin-Ichi; Lado, Carlos; Landolt, John C; Nanjundiah, Vidyanand; Queller, David C; Strassmann, Joan E; Spiegel, Frederick W; Stephenson, Steven L; Vadell, Eduardo M; Baldauf, Sandra L

2018-02-01

Traditional morphology-based taxonomy of dictyostelids is rejected by molecular phylogeny. A new classification is presented based on monophyletic entities with consistent and strong molecular phylogenetic support and that are, as far as possible, morphologically recognizable. All newly named clades are diagnosed with small subunit ribosomal RNA (18S rRNA) sequence signatures plus morphological synapomorphies where possible. The two major molecular clades are given the rank of order, as Acytosteliales ord. nov. and Dictyosteliales. The two major clades within each of these orders are recognized and given the rank of family as, respectively, Acytosteliaceae and Cavenderiaceae fam. nov. in Acytosteliales, and Dictyosteliaceae and Raperosteliaceae fam. nov. in Dictyosteliales. Twelve genera are recognized: Cavenderia gen. nov. in Cavenderiaceae, Acytostelium, Rostrostelium gen. nov. and Heterostelium gen. nov. in Acytosteliaceae, Tieghemostelium gen. nov., Hagiwaraea gen. nov., Raperostelium gen. nov. and Speleostelium gen. nov. in Raperosteliaceae, and Dictyostelium and Polysphondylium in Dictyosteliaceae. The "polycephalum" complex is treated as Coremiostelium gen. nov. (not assigned to family) and the "polycarpum" complex as Synstelium gen. nov. (not assigned to order and family). Coenonia, which may not be a dictyostelid, is treated as a genus incertae sedis. Eighty-eight new combinations are made at species and variety level, and Dictyostelium ammophilum is validated. Copyright © 2017 Elsevier GmbH. All rights reserved.

Evaluating Stream Filtering for Entity Profile Updates in TREC 2012, 2013, and 2014 (KBA Track Overview, Notebook Paper)

DTIC Science & Technology

2014-11-01

possible future directions that build on the KBA experience.   Data Assets   In addition to the three hundred run submissions from diverse systems...form name of an entity and assigning a confidence score based on the number of matches of tokens in the name. See code in github [6]. macro-P...131 64 GENDER 4 2 FoundedBy     56 30 NAME 2 2 DateOfDeath     54 12 TOP_MEMBERS_EMPLOYEES 2 1 EmployeeOf     44 19 WON_AWARD 1 1

78 FR 38537 - Federal Acquisition Regulation; Federal Acquisition Circular 2005-68; Small Entity Compliance Guide

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-26

... Entity Compliance Guide. SUMMARY: This document is issued under the joint authority of DOD, GSA, and NASA... whose name appears in the table below. Please cite FAC 2005-68 and the FAR case number. For information... Listed in FAC 2005-68 Subject FAR Case Analyst *Expansion of Applicability of the Senior Executive...

Galeata: chronic migraine independently considered in a medieval headache classification.

PubMed

Guerrero-Peral, Angel Luís; de Frutos González, Virginia; Pedraza-Hueso, María Isabel

2014-03-21

Chronic migraine is a quite recent concept. However, there are descriptions suggestive of episodic migraine since the beginning of scientific medicine. We aim to review main headache classifications during Classical antiquity and compared them with that proposed in the 11th century by Constantine the African in his Liber Pantegni, one of the most influential texts in medieval medicine. We have carried out a descriptive review of Henricum Petrum's Latin edition, year 1539. Headache classifications proposed by Aretaeus of Cappadocia, Galen of Pergamun and Alexander of Tralles, all of them classifying headaches into three main types, considered an entity (called Heterocrania or Hemicrania), comparable to contemporary episodic migraine.In ninth book of Liber Pantegni, headaches were also classified into three types and one of them, Galeata, consisted on a chronic pain of mild intensity with occasional superimposed exacerbations. In Liber Pantegni we have firstly identified, as a separate entity, a headache comparable to that we currently define as chronic migraine: Galeata.

Galeata: chronic migraine independently considered in a medieval headache classification

PubMed Central

2014-01-01

Background Chronic migraine is a quite recent concept. However, there are descriptions suggestive of episodic migraine since the beginning of scientific medicine. We aim to review main headache classifications during Classical antiquity and compared them with that proposed in the 11th century by Constantine the African in his Liber Pantegni, one of the most influential texts in medieval medicine. Method We have carried out a descriptive review of Henricum Petrum's Latin edition, year 1539. Results Headache classifications proposed by Aretaeus of Cappadocia, Galen of Pergamun and Alexander of Tralles, all of them classifying headaches into three main types, considered an entity (called Heterocrania or Hemicrania), comparable to contemporary episodic migraine. In ninth book of Liber Pantegni, headaches were also classified into three types and one of them, Galeata, consisted on a chronic pain of mild intensity with occasional superimposed exacerbations. Conclusion In Liber Pantegni we have firstly identified, as a separate entity, a headache comparable to that we currently define as chronic migraine: Galeata. PMID:24655582

Classification of Pinus patula, P. tecunumanii, P. oocarpa, P. caribaea var. hondurensis, and Related Taxonomic Entities

Treesearch

A.E. Squillace; Jesse P. Perry

1992-01-01

Stem xylem terpenes of 75 pine populations were studied to determine relationships among taxonomic entities. Typical Pinus patula populations occurring in areas north and west of Oaxaca, Mexico, had very high proportions of 3-phellandrene and low proportions of other constituents. Terpene compositions of populations of variety longipeduncalatain...

31 CFR 575.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 575.303 Section 575.303 Money... CONTROL, DEPARTMENT OF THE TREASURY IRAQI SANCTIONS REGULATIONS General Definitions § 575.303 Entity. The term entity includes a corporation, partnership, association, or other organization. ...

Acquired bilateral telangiectatic macules: a distinct clinical entity.

PubMed

Park, Ji-Hye; Lee, Dong Jun; Lee, Yoo-Jung; Jang, Yong Hyun; Kang, Hee Young; Kim, You Chan

2014-09-01

We evaluated 13 distinct patients with multiple telangiectatic pigmented macules confined mostly to the upper arms to determine if the clinical and histopathological features of these cases might represent a specific clinical entity. We retrospectively investigated the clinical, histopathologic, and immunohistochemical features of 13 patients with multiple telangiectatic pigmented macules on the upper arms who presented between January 2003 and December 2012. Epidermal pigmentation, melanogenic activity, melanocyte number, vascularity, epidermal thickness, and perivascular mast cell number of the specimens were evaluated. Clinically, the condition favored middle-aged men. On histopathologic examination, the lesional skin showed capillary proliferation and telangiectasia in the upper dermis. Histochemical and immunohistochemical analysis revealed basal hyperpigmentation and increased melanogenic activity in the lesional skin (P < .05). No significant difference in epidermal thickness or mast cell number was observed between the normal perilesional skin and the lesional skin. The clinical and histopathologic features of these lesions were relatively consistent in all patients. In addition, the features are quite distinct from other diseases. Based on clinical and histologic features, we suggest the name acquired bilateral telangiectatic macules for this new entity.

7 CFR 1738.16 - Eligible entities.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 11 2010-01-01 2010-01-01 false Eligible entities. 1738.16 Section 1738.16... Eligible entities. (a) RUS makes broadband loans to legally organized entities providing, or proposing to provide, broadband services in eligible rural communities. (1) Types of eligible entities include...

7 CFR 1738.16 - Eligible entities.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 11 2011-01-01 2011-01-01 false Eligible entities. 1738.16 Section 1738.16... Eligible entities. (a) RUS makes broadband loans to legally organized entities providing, or proposing to provide, broadband services in eligible rural communities. (1) Types of eligible entities include...

7 CFR 63.4 - Eligible entity.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 3 2011-01-01 2011-01-01 false Eligible entity. 63.4 Section 63.4 Agriculture Regulations of the Department of Agriculture (Continued) AGRICULTURAL MARKETING SERVICE (Standards... IMPROVEMENT CENTER General Provisions Definitions § 63.4 Eligible entity. Eligible entity means an entity that...

Multi-dimensionality and variability in folk classification of stingless bees (Apidae: Meliponini).

PubMed

Zamudio, Fernando; Hilgert, Norma I

2015-05-23

Not long ago Eugene Hunn suggested using a combination of cognitive, linguistic, ecological and evolutionary theories in order to account for the dynamic character of ethnoecology in the study of folk classification systems. In this way he intended to question certain homogeneity in folk classifications models and deepen in the analysis and interpretation of variability in folk classifications. This paper studies how a rural culturally mixed population of the Atlantic Forest of Misiones (Argentina) classified honey-producing stingless bees according to the linguistic, cognitive and ecological dimensions of folk classification. We also analyze the socio-ecological meaning of binomialization in naming and the meaning of general local variability in the appointment of stingless bees. We used three different approaches: the classical approach developed by Brent Berlin which relies heavily on linguistic criteria, the approach developed by Eleonor Rosch which relies on psychological (cognitive) principles of categorization and finally we have captured the ecological dimension of folk classification in local narratives. For the second approximation, we developed ways of measuring the degree of prototypicality based on a total of 107 comparisons of the type "X is similar to Y" identified in personal narratives. Various logical and grouping strategies coexist and were identified as: graded of lateral linkage, hierarchical and functional. Similarity judgments among folk taxa resulted in an implicit logic of classification graded according to taxa's prototypicality. While there is a high agreement on naming stingless bees with monomial names, a considerable number of underrepresented binomial names and lack of names were observed. Two possible explanations about reported local naming variability are presented. We support the multidimensionality of folk classification systems. This confirms the specificity of local classification systems but also reflects the use of grouping

LPSN—list of prokaryotic names with standing in nomenclature

PubMed Central

Parte, Aidan C.

2014-01-01

The List of Prokaryotic Names with Standing in Nomenclature (LPSN; http://www.bacterio.net) is a database that lists the names of prokaryotes (Bacteria and Archaea) that have been validly published in the International Journal of Systematic and Evolutionary Microbiology directly or by inclusion in a Validation List, under the Rules of International Code of Nomenclature of Bacteria. Currently there are 15 974 taxa listed. In addition, LPSN has an up-to-date classification of prokaryotes and information on prokaryotic nomenclature and culture collections. PMID:24243842

31 CFR 551.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 551.303 Section 551.303 Money... CONTROL, DEPARTMENT OF THE TREASURY SOMALIA SANCTIONS REGULATIONS General Definitions § 551.303 Entity. The term entity means a partnership, association, trust, joint venture, corporation, group, subgroup...

31 CFR 537.304 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 537.304 Section 537.304 Money... CONTROL, DEPARTMENT OF THE TREASURY BURMESE SANCTIONS REGULATIONS General Definitions § 537.304 Entity. The term entity means a partnership, association, trust, joint venture, corporation, group, subgroup...

31 CFR 548.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 548.303 Section 548.303 Money... CONTROL, DEPARTMENT OF THE TREASURY BELARUS SANCTIONS REGULATIONS General Definitions § 548.303 Entity. The term entity means a partnership, association, trust, joint venture, corporation, group, subgroup...

31 CFR 551.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 551.303 Section 551.303 Money... CONTROL, DEPARTMENT OF THE TREASURY SOMALIA SANCTIONS REGULATIONS General Definitions § 551.303 Entity. The term entity means a partnership, association, trust, joint venture, corporation, group, subgroup...

31 CFR 538.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 538.303 Section 538.303 Money... CONTROL, DEPARTMENT OF THE TREASURY SUDANESE SANCTIONS REGULATIONS General Definitions § 538.303 Entity. The term entity means a partnership, association, trust, joint venture, corporation, or other...

31 CFR 538.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 538.303 Section 538.303 Money... CONTROL, DEPARTMENT OF THE TREASURY SUDANESE SANCTIONS REGULATIONS General Definitions § 538.303 Entity. The term entity means a partnership, association, trust, joint venture, corporation, or other...

31 CFR 536.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 536.303 Section 536.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS....303 Entity. The term entity means a partnership, association, corporation, or other organization...

31 CFR 595.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 595.303 Section 595.303 Money... CONTROL, DEPARTMENT OF THE TREASURY TERRORISM SANCTIONS REGULATIONS General Definitions § 595.303 Entity. The term entity means a partnership, association, corporation, or other organization, group or...

31 CFR 545.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 545.303 Section 545.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS....303 Entity. The term entity means a partnership, association, corporation, or other organization...

31 CFR 543.304 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 543.304 Section 543.304 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... Entity. The term entity means a partnership, association, trust, joint venture, corporation, group...

31 CFR 541.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 541.303 Section 541.303 Money... CONTROL, DEPARTMENT OF THE TREASURY ZIMBABWE SANCTIONS REGULATIONS General Definitions § 541.303 Entity. The term entity means a partnership, association, trust, joint venture, corporation, group, subgroup...

31 CFR 537.304 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 537.304 Section 537.304 Money... CONTROL, DEPARTMENT OF THE TREASURY BURMESE SANCTIONS REGULATIONS General Definitions § 537.304 Entity. The term entity means a partnership, association, trust, joint venture, corporation, group, subgroup...

31 CFR 536.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 536.303 Section 536.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS....303 Entity. The term entity means a partnership, association, corporation, or other organization...

31 CFR 595.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 595.303 Section 595.303 Money... CONTROL, DEPARTMENT OF THE TREASURY TERRORISM SANCTIONS REGULATIONS General Definitions § 595.303 Entity. The term entity means a partnership, association, corporation, or other organization, group or...

31 CFR 543.304 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 543.304 Section 543.304 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... Entity. The term entity means a partnership, association, trust, joint venture, corporation, group...

31 CFR 549.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 549.303 Section 549.303 Money... CONTROL, DEPARTMENT OF THE TREASURY LEBANON SANCTIONS REGULATIONS General Definitions § 549.303 Entity. The term entity means a partnership, association, trust, joint venture, corporation, group, subgroup...

31 CFR 548.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 548.303 Section 548.303 Money... CONTROL, DEPARTMENT OF THE TREASURY BELARUS SANCTIONS REGULATIONS General Definitions § 548.303 Entity. The term entity means a partnership, association, trust, joint venture, corporation, group, subgroup...

31 CFR 541.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 541.303 Section 541.303 Money... CONTROL, DEPARTMENT OF THE TREASURY ZIMBABWE SANCTIONS REGULATIONS General Definitions § 541.303 Entity. The term entity means a partnership, association, trust, joint venture, corporation, group, subgroup...

47 CFR 90.1103 - Designated entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 5 2010-10-01 2010-10-01 false Designated entities. 90.1103 Section 90.1103... Designated entities. (a) This section addresses certain issues concerning designated entities in the Location... provisions. (1) A small business is an entity that, together with its affiliates and controlling interests...

47 CFR 90.1103 - Designated entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 5 2011-10-01 2011-10-01 false Designated entities. 90.1103 Section 90.1103... Designated entities. (a) This section addresses certain issues concerning designated entities in the Location... provisions. (1) A small business is an entity that, together with its affiliates and controlling interests...

31 CFR 596.308 - Person; entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Person; entity. 596.308 Section 596... General Definitions § 596.308 Person; entity. (a) The term person means an individual or entity. (b) The term entity means a partnership, association, corporation, or other organization. ...

31 CFR 596.308 - Person; entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Person; entity. 596.308 Section 596... General Definitions § 596.308 Person; entity. (a) The term person means an individual or entity. (b) The term entity means a partnership, association, corporation, or other organization. ...

FamPlex: a resource for entity recognition and relationship resolution of human protein families and complexes in biomedical text mining.

PubMed

Bachman, John A; Gyori, Benjamin M; Sorger, Peter K

2018-06-28

For automated reading of scientific publications to extract useful information about molecular mechanisms it is critical that genes, proteins and other entities be correctly associated with uniform identifiers, a process known as named entity linking or "grounding." Correct grounding is essential for resolving relationships among mined information, curated interaction databases, and biological datasets. The accuracy of this process is largely dependent on the availability of machine-readable resources associating synonyms and abbreviations commonly found in biomedical literature with uniform identifiers. In a task involving automated reading of ∼215,000 articles using the REACH event extraction software we found that grounding was disproportionately inaccurate for multi-protein families (e.g., "AKT") and complexes with multiple subunits (e.g."NF- κB"). To address this problem we constructed FamPlex, a manually curated resource defining protein families and complexes as they are commonly encountered in biomedical text. In FamPlex the gene-level constituents of families and complexes are defined in a flexible format allowing for multi-level, hierarchical membership. To create FamPlex, text strings corresponding to entities were identified empirically from literature and linked manually to uniform identifiers; these identifiers were also mapped to equivalent entries in multiple related databases. FamPlex also includes curated prefix and suffix patterns that improve named entity recognition and event extraction. Evaluation of REACH extractions on a test corpus of ∼54,000 articles showed that FamPlex significantly increased grounding accuracy for families and complexes (from 15 to 71%). The hierarchical organization of entities in FamPlex also made it possible to integrate otherwise unconnected mechanistic information across families, subfamilies, and individual proteins. Applications of FamPlex to the TRIPS/DRUM reading system and the Biocreative VI Bioentity

78 FR 80381 - Federal Acquisition Regulation; Federal Acquisition Circular 2005-72; Small Entity Compliance Guide

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-31

...: Small Entity Compliance Guide. SUMMARY: This document is issued under the joint authority of DOD, GSA..., contact the analyst whose name appears in the table below. Please cite FAC 2005-72 and the FAR case number... 202- 501-4755. Rules Listed in FAC 2005-72 Item Subject FAR Case Analyst *I Service 2010-010 Loeb...

31 CFR 544.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 544.303 Section 544.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... General Definitions § 544.303 Entity. The term entity means a partnership, association, trust, joint...

31 CFR 594.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 594.303 Section 594.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... Entity. The term entity means a partnership, association, corporation, or other organization, group, or...

31 CFR 594.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 594.303 Section 594.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... Entity. The term entity means a partnership, association, corporation, or other organization, group, or...

31 CFR 598.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 598.303 Section 598.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... § 598.303 Entity. The term entity means a partnership, joint venture, association, corporation...

31 CFR 542.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 542.303 Section 542.303 Money... CONTROL, DEPARTMENT OF THE TREASURY SYRIAN SANCTIONS REGULATIONS General Definitions § 542.303 Entity. The term entity means a partnership, association, trust, joint venture, corporation, group, subgroup, or...

31 CFR 592.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 592.303 Section 592.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... Entity. The term entity means a partnership, association, trust, joint venture, corporation, or other...

31 CFR 588.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 588.303 Section 588.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS....303 Entity. The term entity means a partnership, association, trust, joint venture, corporation, group...

31 CFR 561.316 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 561.316 Section 561.316 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... Entity. The term entity means a partnership, association, trust, joint venture, corporation, or other...

31 CFR 585.310 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 585.310 Section 585.310 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... Definitions § 585.310 Entity. The term entity includes a corporation, partnership, association, or other...

31 CFR 588.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 588.303 Section 588.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS....303 Entity. The term entity means a partnership, association, trust, joint venture, corporation, group...

31 CFR 587.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 587.303 Section 587.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... SANCTIONS REGULATIONS General Definitions § 587.303 Entity. The term entity means a partnership, association...

31 CFR 542.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 542.303 Section 542.303 Money... CONTROL, DEPARTMENT OF THE TREASURY SYRIAN SANCTIONS REGULATIONS General Definitions § 542.303 Entity. The term entity means a partnership, association, trust, joint venture, corporation, group, subgroup, or...

31 CFR 562.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 562.303 Section 562.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... § 562.303 Entity. The term entity means a partnership, association, trust, joint venture, corporation...

31 CFR 593.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 593.303 Section 593.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... Definitions § 593.303 Entity. The term entity means a partnership, association, trust, joint venture...

31 CFR 592.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 592.303 Section 592.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... Entity. The term entity means a partnership, association, trust, joint venture, corporation, or other...

31 CFR 586.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 586.303 Section 586.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... REGULATIONS General Definitions § 586.303 Entity. The term entity means a partnership, association, trust...

31 CFR 546.304 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 546.304 Section 546.304 Money... CONTROL, DEPARTMENT OF THE TREASURY DARFUR SANCTIONS REGULATIONS General Definitions § 546.304 Entity. The term entity means a partnership, association, trust, joint venture, corporation, group, subgroup, or...

31 CFR 597.306 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 597.306 Section 597.306 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... Definitions § 597.306 Entity. The term entity includes a partnership, association, corporation, or other...

31 CFR 539.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 539.303 Section 539.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... Definitions § 539.303 Entity. The term entity means a partnership, association, trust, joint venture...

31 CFR 544.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 544.303 Section 544.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... General Definitions § 544.303 Entity. The term entity means a partnership, association, trust, joint...

31 CFR 570.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 570.303 Section 570.303 Money... CONTROL, DEPARTMENT OF THE TREASURY LIBYAN SANCTIONS REGULATIONS General Definitions § 570.303 Entity. The term entity means a partnership, association, trust, joint venture, corporation, group, subgroup, or...

31 CFR 540.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 540.303 Section 540.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... General Definitions § 540.303 Entity. The term entity means a partnership, association, trust, joint...

31 CFR 597.306 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 597.306 Section 597.306 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... Definitions § 597.306 Entity. The term entity includes a partnership, association, corporation, or other...

31 CFR 540.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 540.303 Section 540.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... General Definitions § 540.303 Entity. The term entity means a partnership, association, trust, joint...

31 CFR 539.303 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 539.303 Section 539.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... Definitions § 539.303 Entity. The term entity means a partnership, association, trust, joint venture...

31 CFR 593.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 593.303 Section 593.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... Definitions § 593.303 Entity. The term entity means a partnership, association, trust, joint venture...

31 CFR 576.304 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 576.304 Section 576.304 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... Definitions § 576.304 Entity. The term entity means a partnership, association, trust, joint venture...

31 CFR 598.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 598.303 Section 598.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS... § 598.303 Entity. The term entity means a partnership, joint venture, association, corporation...

43 CFR 426.10 - Public entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 43 Public Lands: Interior 1 2011-10-01 2011-10-01 false Public entities. 426.10 Section 426.10... INTERIOR ACREAGE LIMITATION RULES AND REGULATIONS § 426.10 Public entities. (a) Application of the acreage limitation provisions to public entities. Reclamation does not subject public entities to the acreage...

43 CFR 426.10 - Public entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 43 Public Lands: Interior 1 2010-10-01 2010-10-01 false Public entities. 426.10 Section 426.10... INTERIOR ACREAGE LIMITATION RULES AND REGULATIONS § 426.10 Public entities. (a) Application of the acreage limitation provisions to public entities. Reclamation does not subject public entities to the acreage...

47 CFR 101.1429 - Designated entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 5 2011-10-01 2011-10-01 false Designated entities. 101.1429 Section 101.1429... Designated entities. (a) Eligibility for small business provisions. (1) A very small business is an entity... exceeding $3 million for the preceding three years. (2) A small business is an entity that, together with...

47 CFR 13.7 - Classification of operator licenses and endorsements.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 1 2011-10-01 2011-10-01 false Classification of operator licenses and... OPERATORS General § 13.7 Classification of operator licenses and endorsements. (a) Commercial radio operator... license's ITU classification, if different from its name, is given in parentheses. (1) First Class...

31 CFR 560.305 - Person; entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Person; entity. 560.305 Section 560.305 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF... § 560.305 Person; entity. (a) The term person means an individual or entity. (b) The term entity means a...

18 CFR 46.5 - Covered entities.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 18 Conservation of Power and Water Resources 1 2011-04-01 2011-04-01 false Covered entities. 46.5... FOR PERSONS HOLDING INTERLOCKING POSITIONS § 46.5 Covered entities. Entities to which the general rule..., or a savings and loan association; (b) Any entity which is authorized by law to underwrite or...

46 CFR 67.41 - Governmental entity.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 2 2010-10-01 2010-10-01 false Governmental entity. 67.41 Section 67.41 Shipping COAST... DOCUMENTATION OF VESSELS Citizenship Requirements for Vessel Documentation § 67.41 Governmental entity. A governmental entity is a citizen for the purpose of obtaining a vessel document if it is an entity of the...

46 CFR 67.41 - Governmental entity.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 2 2011-10-01 2011-10-01 false Governmental entity. 67.41 Section 67.41 Shipping COAST... DOCUMENTATION OF VESSELS Citizenship Requirements for Vessel Documentation § 67.41 Governmental entity. A governmental entity is a citizen for the purpose of obtaining a vessel document if it is an entity of the...

18 CFR 46.5 - Covered entities.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Covered entities. 46.5... FOR PERSONS HOLDING INTERLOCKING POSITIONS § 46.5 Covered entities. Entities to which the general rule..., or a savings and loan association; (b) Any entity which is authorized by law to underwrite or...

42 CFR 6.3 - Eligible entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 1 2010-10-01 2010-10-01 false Eligible entities. 6.3 Section 6.3 Public Health... COVERAGE OF CERTAIN GRANTEES AND INDIVIDUALS § 6.3 Eligible entities. (a) Grantees. Entities eligible for coverage under this part are public and nonprofit private entities receiving Federal funds under any of the...

31 CFR 560.305 - Person; entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Person; entity. 560.305 Section 560.305 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF... § 560.305 Person; entity. (a) The term person means an individual or entity. (b) The term entity means a...

42 CFR 6.3 - Eligible entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 1 2011-10-01 2011-10-01 false Eligible entities. 6.3 Section 6.3 Public Health... COVERAGE OF CERTAIN GRANTEES AND INDIVIDUALS § 6.3 Eligible entities. (a) Grantees. Entities eligible for coverage under this part are public and nonprofit private entities receiving Federal funds under any of the...

2 CFR 170.310 - Entity.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 2 Grants and Agreements 1 2013-01-01 2013-01-01 false Entity. 170.310 Section 170.310 Grants and Agreements Office of Management and Budget Guidance for Grants and Agreements OFFICE OF MANAGEMENT AND BUDGET... COMPENSATION INFORMATION Definitions § 170.310 Entity. Entity has the meaning given in 2 CFR part 25. ...

2 CFR 170.310 - Entity.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 2 Grants and Agreements 1 2014-01-01 2014-01-01 false Entity. 170.310 Section 170.310 Grants and Agreements Office of Management and Budget Guidance for Grants and Agreements OFFICE OF MANAGEMENT AND BUDGET... INFORMATION Definitions § 170.310 Entity. Entity has the meaning given in 2 CFR part 25. ...

2 CFR 170.310 - Entity.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 2 Grants and Agreements 1 2012-01-01 2012-01-01 false Entity. 170.310 Section 170.310 Grants and Agreements Office of Management and Budget Guidance for Grants and Agreements OFFICE OF MANAGEMENT AND BUDGET... COMPENSATION INFORMATION Definitions § 170.310 Entity. Entity has the meaning given in 2 CFR part 25. ...

2 CFR 170.310 - Entity.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 2 Grants and Agreements 1 2011-01-01 2011-01-01 false Entity. 170.310 Section 170.310 Grants and Agreements Office of Management and Budget Guidance for Grants and Agreements OFFICE OF MANAGEMENT AND BUDGET... INFORMATION Definitions § 170.310 Entity. Entity has the meaning given in 2 CFR part 25. ...

31 CFR 800.212 - Foreign entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Foreign entity. 800.212 Section 800... TAKEOVERS BY FOREIGN PERSONS Definitions § 800.212 Foreign entity. (a) The term foreign entity means any... majority of the equity interest in such entity is ultimately owned by U.S. nationals is not a foreign...

12 CFR 1229.2 - Determination of a Bank's capital classification.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Determination of a Bank's capital classification. 1229.2 Section 1229.2 Banks and Banking FEDERAL HOUSING FINANCE AGENCY ENTITY REGULATIONS CAPITAL... than the minimum required under this paragraph or make a determination for one or more Banks without...

2 CFR 25.320 - Entity.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 2 Grants and Agreements 1 2011-01-01 2011-01-01 false Entity. 25.320 Section 25.320 Grants and Agreements Office of Management and Budget Guidance for Grants and Agreements OFFICE OF MANAGEMENT AND BUDGET... CONTRACTOR REGISTRATION Definitions § 25.320 Entity. Entity, as it is used in this part, has the meaning...

Recurrent neural networks with specialized word embeddings for health-domain named-entity recognition.

PubMed

Jauregi Unanue, Iñigo; Zare Borzeshi, Ehsan; Piccardi, Massimo

2017-12-01

Previous state-of-the-art systems on Drug Name Recognition (DNR) and Clinical Concept Extraction (CCE) have focused on a combination of text "feature engineering" and conventional machine learning algorithms such as conditional random fields and support vector machines. However, developing good features is inherently heavily time-consuming. Conversely, more modern machine learning approaches such as recurrent neural networks (RNNs) have proved capable of automatically learning effective features from either random assignments or automated word "embeddings". (i) To create a highly accurate DNR and CCE system that avoids conventional, time-consuming feature engineering. (ii) To create richer, more specialized word embeddings by using health domain datasets such as MIMIC-III. (iii) To evaluate our systems over three contemporary datasets. Two deep learning methods, namely the Bidirectional LSTM and the Bidirectional LSTM-CRF, are evaluated. A CRF model is set as the baseline to compare the deep learning systems to a traditional machine learning approach. The same features are used for all the models. We have obtained the best results with the Bidirectional LSTM-CRF model, which has outperformed all previously proposed systems. The specialized embeddings have helped to cover unusual words in DrugBank and MedLine, but not in the i2b2/VA dataset. We present a state-of-the-art system for DNR and CCE. Automated word embeddings has allowed us to avoid costly feature engineering and achieve higher accuracy. Nevertheless, the embeddings need to be retrained over datasets that are adequate for the domain, in order to adequately cover the domain-specific vocabulary. Copyright © 2017 Elsevier Inc. All rights reserved.

41 CFR 105-62.101 - Security classification categories.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 41 Public Contracts and Property Management 3 2013-07-01 2013-07-01 false Security classification... classification categories. As set forth in Executive Order 12065, official information or material which requires... three categories: Namely, Top Secret, Secret, or Confidential, depending on its degree of significance...

41 CFR 105-62.101 - Security classification categories.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 41 Public Contracts and Property Management 3 2012-01-01 2012-01-01 false Security classification... classification categories. As set forth in Executive Order 12065, official information or material which requires... three categories: Namely, Top Secret, Secret, or Confidential, depending on its degree of significance...

41 CFR 105-62.101 - Security classification categories.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 41 Public Contracts and Property Management 3 2014-01-01 2014-01-01 false Security classification... classification categories. As set forth in Executive Order 12065, official information or material which requires... three categories: Namely, Top Secret, Secret, or Confidential, depending on its degree of significance...

Apocrine hidradenocarcinoma of the scalp: a classification conundrum.

PubMed

Cohen, Marc; Cassarino, David S; Shih, Hubert B; Abemayor, Elliot; St John, Maie

2009-03-01

The classification of malignant sweat gland lesions is complex. Traditionally, cutaneous sweat gland tumors have been classified by either eccrine or apocrine features. A case report of a 33-year-old Hispanic man with a left scalp mass diagnosed as a malignancy of adnexal origin preoperatively is discussed. After presentation at our multidisciplinary tumor board, excision with ipsilateral neck dissection was undertaken. Final pathology revealed an apocrine hidradenocarcinoma. The classification and behavior of this entity are discussed in this report. Apocrine hidradenocarcinoma can be viewed as an aggressive malignant lesion of cutaneous sweat glands on a spectrum that involves both eccrine and apoeccrine lesions.

Apocrine Hidradenocarcinoma of the Scalp: A Classification Conundrum

PubMed Central

Cassarino, David S.; Shih, Hubert B.; Abemayor, Elliot; John, Maie St.

2008-01-01

Introduction The classification of malignant sweat gland lesions is complex. Traditionally, cutaneous sweat gland tumors have been classified by either eccrine or apocrine features. Methods A case report of a 33-year-old Hispanic man with a left scalp mass diagnosed as a malignancy of adnexal origin preoperatively is discussed. After presentation at our multidisciplinary tumor board, excision with ipsilateral neck dissection was undertaken. Results Final pathology revealed an apocrine hidradenocarcinoma. The classification and behavior of this entity are discussed in this report. Conclusion Apocrine hidradenocarcinoma can be viewed as an aggressive malignant lesion of cutaneous sweat glands on a spectrum that involves both eccrine and apoeccrine lesions. PMID:20596988

[Nonspecific interstitial pneumonitis: a clinicopathologic entity, histologic pattern or unclassified group of heterogeneous interstitial pneumonitis?].

PubMed

Morais, António; Moura, M Conceição Souto; Cruz, M Rosa; Gomes, Isabel

2004-01-01

Nonspecific interstitial pneumonitis (NSIP) initially described by Katzenstein and Fiorelli in 1994, seems to be a distinct clinicopathologic entity among idiopathic interstitial pneumonitis (IIP). Besides different histologic features from other IIP, NSIP is characterized by a better long-term outcome, associated with a better steroids responsiveness than idiopathic pulmonar fibrosis (IPF), where usually were included. Thus, differentiating NSIP from other IIP, namely IPF is very significant, since it has important therapeutic and prognostic implications. NSIP encloses different pathologies, namely those with inflammatory predominance (cellular subtype) or fibrous predominance (fibrosing subtype). NSIP is reviewed and discussed by the authors, after two clinical cases description.

OCLC Participating Institutions: Arranged by Network and Subarranged by Institution Name.

ERIC Educational Resources Information Center

OCLC Online Computer Library Center, Inc., Dublin, OH.

This directory of institutions participating in the Ohio College Library Center (OCLC) presents the following information for each: assigned OCLC symbol, institution name and address, affiliated network, classification scheme in use, and identification symbol assigned by Library of Congress. (SC)

Chemical name extraction based on automatic training data generation and rich feature set.

PubMed

Yan, Su; Spangler, W Scott; Chen, Ying

2013-01-01

The automation of extracting chemical names from text has significant value to biomedical and life science research. A major barrier in this task is the difficulty of getting a sizable and good quality data to train a reliable entity extraction model. Another difficulty is the selection of informative features of chemical names, since comprehensive domain knowledge on chemistry nomenclature is required. Leveraging random text generation techniques, we explore the idea of automatically creating training sets for the task of chemical name extraction. Assuming the availability of an incomplete list of chemical names, called a dictionary, we are able to generate well-controlled, random, yet realistic chemical-like training documents. We statistically analyze the construction of chemical names based on the incomplete dictionary, and propose a series of new features, without relying on any domain knowledge. Compared to state-of-the-art models learned from manually labeled data and domain knowledge, our solution shows better or comparable results in annotating real-world data with less human effort. Moreover, we report an interesting observation about the language for chemical names. That is, both the structural and semantic components of chemical names follow a Zipfian distribution, which resembles many natural languages.

47 CFR 80.1252 - Designated entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 5 2011-10-01 2011-10-01 false Designated entities. 80.1252 Section 80.1252... MARITIME SERVICES Competitive Bidding Procedures § 80.1252 Designated entities. (a) This section addresses certain issues concerning designated entities in maritime communications services subject to competitive...

47 CFR 80.1252 - Designated entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 5 2010-10-01 2010-10-01 false Designated entities. 80.1252 Section 80.1252... MARITIME SERVICES Competitive Bidding Procedures § 80.1252 Designated entities. (a) This section addresses certain issues concerning designated entities in maritime communications services subject to competitive...

Designing and Implementation of River Classification Assistant Management System

NASA Astrophysics Data System (ADS)

Zhao, Yinjun; Jiang, Wenyuan; Yang, Rujun; Yang, Nan; Liu, Haiyan

2018-03-01

In an earlier publication, we proposed a new Decision Classifier (DCF) for Chinese river classification based on their structures. To expand, enhance and promote the application of the DCF, we build a computer system to support river classification named River Classification Assistant Management System. Based on ArcEngine and ArcServer platform, this system implements many functions such as data management, extraction of river network, river classification, and results publication under combining Client / Server with Browser / Server framework.

31 CFR 543.304 - Entity.

Code of Federal Regulations, 2012 CFR

2012-07-01

... CONTROL, DEPARTMENT OF THE TREASURY CôTE D'IVOIRE SANCTIONS REGULATIONS General Definitions § 543.304 Entity. The term entity means a partnership, association, trust, joint venture, corporation, group...

47 CFR 22.229 - Designated entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 2 2011-10-01 2011-10-01 false Designated entities. 22.229 Section 22.229... Licensing Requirements and Procedures Competitive Bidding Procedures § 22.229 Designated entities. (a) Eligibility for small business provisions. (1) A very small business is an entity that, together with its...

47 CFR 24.321 - Designated entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 2 2011-10-01 2011-10-01 false Designated entities. 24.321 Section 24.321... SERVICES Competitive Bidding Procedures for Narrowband PCS § 24.321 Designated entities. (a) Eligibility for small business provisions. (1) A small business is an entity that, together with its controlling...

47 CFR 22.882 - Designated entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 2 2011-10-01 2011-10-01 false Designated entities. 22.882 Section 22.882...-Ground Radiotelephone Service Commercial Aviation Air-Ground Systems § 22.882 Designated entities. (a... business is an entity that, together with its affiliates, its controlling interests and the affiliates of...

47 CFR 27.1218 - Designated entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 2 2011-10-01 2011-10-01 false Designated entities. 27.1218 Section 27.1218... COMMUNICATIONS SERVICES Broadband Radio Service and Educational Broadband Service § 27.1218 Designated entities. (a) Eligibility for small business provisions. (1) A small business is an entity that, together with...

47 CFR 24.321 - Designated entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Designated entities. 24.321 Section 24.321... SERVICES Competitive Bidding Procedures for Narrowband PCS § 24.321 Designated entities. (a) Eligibility for small business provisions. (1) A small business is an entity that, together with its controlling...

The naming of the cranial nerves: a historical review.

PubMed

Davis, Matthew C; Griessenauer, Christoph J; Bosmia, Anand N; Tubbs, R Shane; Shoja, Mohammadali M

2014-01-01

The giants of medicine and anatomy have each left their mark on the history of the cranial nerves, and much of the history of anatomic study can be viewed through the lens of how the cranial nerves were identified and named. A comprehensive literature review on the classification of the cranial names was performed. The identification of the cranial nerves began with Galen in the 2nd century AD and evolved up through the mid-20th century. In 1778, Samuel Sömmerring, a German anatomist, classified the 12 cranial nerves as we recognize them today. This review expands on the excellent investigations of Flamm, Shaw, and Simon et al., with discussion of the historical identification as well as the process of naming the human cranial nerves. Copyright © 2013 Wiley Periodicals, Inc.

[CLINICAL ENTITIES AND CHARACTERISTICS OF PAIN IN PATIENTS WITH RHEUMATIC DISEASES].

PubMed

Prus, Višnja; Kardum, Željka

Musculoskeletal pain is the most common symptom present in almost all rheumatic diseases. Rheumatic diseases include more than 150 clinical entities. There is no uniform classification of rheumatic diseases. In general, we distinguish inflammatory rheumatic diseases, non-inflammatory degenerative articular diseases, systemic connective tissue diseases, metabolic disorders with articular manifestations, and regional and extended pain syndromes. According to the International Association for the Study of Pain (IASP), pain is defined as an unpleasant sensation associated with tissue damage or reported simultaneously with such damage. Pain has a physical, mental, and social component. In rheumatic diseases the pain is mostly chronic and may severely impair the patient’s general condition. The defining criteria involve a period of more than 3 or 6 months, and according to some definitions more than 6 weeks. In most cases the pain is nociceptive rather than neuropathic. Musculoskeletal pain, especially chronic pain, is a global public health problem because of its prevalence, as well as the frequently associated muslculoskeletal function impairment and development of chronic pain syndrome, which can be considered as a separate clinical entity and requires a biopsychosocial treatment approach.

47 CFR 101.538 - Designated entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 5 2011-10-01 2011-10-01 false Designated entities. 101.538 Section 101.538... SERVICES 24 GHz Service and Digital Electronic Message Service § 101.538 Designated entities. (a) Eligibility for small business provisions. (1) A very small business is an entity that, together with its...

47 CFR 27.906 - Designated entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Designated entities. 27.906 Section 27.906... COMMUNICATIONS SERVICES 1670-1675 MHz Band § 27.906 Designated entities. (a) Eligibility for small business provisions. (1) A very small business is an entity that, together with its controlling interests and...

46 CFR 403.110 - Accounting entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 8 2011-10-01 2011-10-01 false Accounting entities. 403.110 Section 403.110 Shipping... ACCOUNTING SYSTEM General § 403.110 Accounting entities. Each Association shall be a separate accounting entity. However, the records shall be maintained with sufficient particularity to allocate items to each...

47 CFR 27.702 - Designated entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 2 2011-10-01 2011-10-01 false Designated entities. 27.702 Section 27.702... COMMUNICATIONS SERVICES Competitive Bidding Procedures for the 698-746 MHz Band § 27.702 Designated entities. (a) Eligibility for small business provisions. (1) An entrepreneur is an entity that, together with its...

47 CFR 27.906 - Designated entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 2 2011-10-01 2011-10-01 false Designated entities. 27.906 Section 27.906... COMMUNICATIONS SERVICES 1670-1675 MHz Band § 27.906 Designated entities. (a) Eligibility for small business provisions. (1) A very small business is an entity that, together with its controlling interests and...

47 CFR 22.223 - Designated entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Designated entities. 22.223 Section 22.223... Licensing Requirements and Procedures Competitive Bidding Procedures § 22.223 Designated entities. (a) Scope... sections. (b) A small business is an entity that either: (1) Together with its affiliates and controlling...

47 CFR 22.223 - Designated entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 2 2011-10-01 2011-10-01 false Designated entities. 22.223 Section 22.223... Licensing Requirements and Procedures Competitive Bidding Procedures § 22.223 Designated entities. (a) Scope... sections. (b) A small business is an entity that either: (1) Together with its affiliates and controlling...

Applying Suffix Rules to Organization Name Recognition

NASA Astrophysics Data System (ADS)

Inui, Takashi; Murakami, Koji; Hashimoto, Taiichi; Utsumi, Kazuo; Ishikawa, Masamichi

This paper presents a method for boosting the performance of the organization name recognition, which is a part of named entity recognition (NER). Although gazetteers (lists of the NEs) have been known as one of the effective features for supervised machine learning approaches on the NER task, the previous methods which have applied the gazetteers to the NER were very simple. The gazetteers have been used just for searching the exact matches between input text and NEs included in them. The proposed method generates regular expression rules from gazetteers, and, with these rules, it can realize a high-coverage searches based on looser matches between input text and NEs. To generate these rules, we focus on the two well-known characteristics of NE expressions; 1) most of NE expressions can be divided into two parts, class-reference part and instance-reference part, 2) for most of NE expressions the class-reference parts are located at the suffix position of them. A pattern mining algorithm runs on the set of NEs in the gazetteers, and some frequent word sequences from which NEs are constructed are found. Then, we employ only word sequences which have the class-reference part at the suffix position as suffix rules. Experimental results showed that our proposed method improved the performance of the organization name recognition, and achieved the 84.58 F-value for evaluation data.

Family-group names in Coleoptera (Insecta)

PubMed Central

Bouchard, Patrice; Bousquet, Yves; Davies, Anthony E.; Alonso-Zarazaga, Miguel A.; Lawrence, John F.; Lyal, Chris H. C.; Newton, Alfred F.; Reid, Chris A. M.; Schmitt, Michael; Ślipiński, S. Adam; Smith, Andrew B. T.

2011-01-01

Abstract We synthesize data on all known extant and fossil Coleoptera family-group names for the first time. A catalogue of 4887 family-group names (124 fossil, 4763 extant) based on 4707 distinct genera in Coleoptera is given. A total of 4492 names are available, 183 of which are permanently invalid because they are based on a preoccupied or a suppressed type genus. Names are listed in a classification framework. We recognize as valid 24 superfamilies, 211 families, 541 subfamilies, 1663 tribes and 740 subtribes. For each name, the original spelling, author, year of publication, page number, correct stem and type genus are included. The original spelling and availability of each name were checked from primary literature. A list of necessary changes due to Priority and Homonymy problems, and actions taken, is given. Current usage of names was conserved, whenever possible, to promote stability of the classification. New synonymies (family-group names followed by genus-group names): Agronomina Gistel, 1848 syn. nov. of Amarina Zimmermann, 1832 (Carabidae), Hylepnigalioini Gistel, 1856 syn. nov. of Melandryini Leach, 1815 (Melandryidae), Polycystophoridae Gistel, 1856 syn. nov. of Malachiinae Fleming, 1821 (Melyridae), Sclerasteinae Gistel, 1856 syn. nov. of Ptilininae Shuckard, 1839 (Ptinidae), Phloeonomini Ádám, 2001 syn. nov. of Omaliini MacLeay, 1825 (Staphylinidae), Sepedophilini Ádám, 2001 syn. nov. of Tachyporini MacLeay, 1825 (Staphylinidae), Phibalini Gistel, 1856 syn. nov. of Cteniopodini Solier, 1835 (Tenebrionidae); Agronoma Gistel 1848 (type species Carabus familiaris Duftschmid, 1812, designated herein) syn. nov. of Amara Bonelli, 1810 (Carabidae), Hylepnigalio Gistel, 1856 (type species Chrysomela caraboides Linnaeus, 1760, by monotypy) syn. nov. of Melandrya Fabricius, 1801 (Melandryidae), Polycystophorus Gistel, 1856 (type species Cantharis aeneus Linnaeus, 1758, designated herein) syn. nov. of Malachius Fabricius, 1775 (Melyridae), Sclerastes

47 CFR 27.502 - Designated entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Designated entities. 27.502 Section 27.502... COMMUNICATIONS SERVICES Competitive Bidding Procedures for the 698-806 MHz Band § 27.502 Designated entities. Eligibility for small business provisions: (a)(1) A small business is an entity that, together with its...

47 CFR 27.502 - Designated entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 2 2011-10-01 2011-10-01 false Designated entities. 27.502 Section 27.502... COMMUNICATIONS SERVICES Competitive Bidding Procedures for the 698-806 MHz Band § 27.502 Designated entities. Eligibility for small business provisions: (a)(1) A small business is an entity that, together with its...

Evaluation Methods of The Text Entities

ERIC Educational Resources Information Center

Popa, Marius

2006-01-01

The paper highlights some evaluation methods to assess the quality characteristics of the text entities. The main concepts used in building and evaluation processes of the text entities are presented. Also, some aggregated metrics for orthogonality measurements are presented. The evaluation process for automatic evaluation of the text entities is…

47 CFR 101.1429 - Designated entities.

Code of Federal Regulations, 2012 CFR

2012-10-01

... Designated entities. (a) Eligibility for small business provisions. (1) A very small business is an entity... exceeding $3 million for the preceding three years. (2) A small business is an entity that, together with... three years. (b) Bidding credits. A winning bidder that qualifies as a very small business, as defined...

47 CFR 101.1429 - Designated entities.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Designated entities. (a) Eligibility for small business provisions. (1) A very small business is an entity... exceeding $3 million for the preceding three years. (2) A small business is an entity that, together with... three years. (b) Bidding credits. A winning bidder that qualifies as a very small business, as defined...

47 CFR 101.1429 - Designated entities.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Designated entities. (a) Eligibility for small business provisions. (1) A very small business is an entity... exceeding $3 million for the preceding three years. (2) A small business is an entity that, together with... three years. (b) Bidding credits. A winning bidder that qualifies as a very small business, as defined...

Contextually guided very-high-resolution imagery classification with semantic segments

NASA Astrophysics Data System (ADS)

Zhao, Wenzhi; Du, Shihong; Wang, Qiao; Emery, William J.

2017-10-01

Contextual information, revealing relationships and dependencies between image objects, is one of the most important information for the successful interpretation of very-high-resolution (VHR) remote sensing imagery. Over the last decade, geographic object-based image analysis (GEOBIA) technique has been widely used to first divide images into homogeneous parts, and then to assign semantic labels according to the properties of image segments. However, due to the complexity and heterogeneity of VHR images, segments without semantic labels (i.e., semantic-free segments) generated with low-level features often fail to represent geographic entities (such as building roofs usually be partitioned into chimney/antenna/shadow parts). As a result, it is hard to capture contextual information across geographic entities when using semantic-free segments. In contrast to low-level features, "deep" features can be used to build robust segments with accurate labels (i.e., semantic segments) in order to represent geographic entities at higher levels. Based on these semantic segments, semantic graphs can be constructed to capture contextual information in VHR images. In this paper, semantic segments were first explored with convolutional neural networks (CNN) and a conditional random field (CRF) model was then applied to model the contextual information between semantic segments. Experimental results on two challenging VHR datasets (i.e., the Vaihingen and Beijing scenes) indicate that the proposed method is an improvement over existing image classification techniques in classification performance (overall accuracy ranges from 82% to 96%).

42 CFR 438.808 - Exclusion of entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 4 2010-10-01 2010-10-01 false Exclusion of entities. 438.808 Section 438.808... Exclusion of entities. (a) General rule. FFP is available in payments under MCO contracts only if the State excludes from the contracts any entities described in paragraph (b) of this section. (b) Entities that must...

42 CFR 438.808 - Exclusion of entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 4 2011-10-01 2011-10-01 false Exclusion of entities. 438.808 Section 438.808... Exclusion of entities. (a) General rule. FFP is available in payments under MCO contracts only if the State excludes from the contracts any entities described in paragraph (b) of this section. (b) Entities that must...

16 CFR 801.50 - Formation of unincorporated entities.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 16 Commercial Practices 1 2010-01-01 2010-01-01 false Formation of unincorporated entities. 801.50... of unincorporated entities. (a) In the formation of an unincorporated entity (other than in... entity and the unincorporated entity itself may, in the formation transaction, be both acquiring and...

16 CFR 801.50 - Formation of unincorporated entities.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 16 Commercial Practices 1 2011-01-01 2011-01-01 false Formation of unincorporated entities. 801.50... of unincorporated entities. (a) In the formation of an unincorporated entity (other than in... entity and the unincorporated entity itself may, in the formation transaction, be both acquiring and...

Entitymetrics: Measuring the Impact of Entities

PubMed Central

Ding, Ying; Song, Min; Han, Jia; Yu, Qi; Yan, Erjia; Lin, Lili; Chambers, Tamy

2013-01-01

This paper proposes entitymetrics to measure the impact of knowledge units. Entitymetrics highlight the importance of entities embedded in scientific literature for further knowledge discovery. In this paper, we use Metformin, a drug for diabetes, as an example to form an entity-entity citation network based on literature related to Metformin. We then calculate the network features and compare the centrality ranks of biological entities with results from Comparative Toxicogenomics Database (CTD). The comparison demonstrates the usefulness of entitymetrics to detect most of the outstanding interactions manually curated in CTD. PMID:24009660

47 CFR 27.807 - Designated entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 2 2011-10-01 2011-10-01 false Designated entities. 27.807 Section 27.807... COMMUNICATIONS SERVICES 1.4 GHz Band § 27.807 Designated entities. (a) Eligibility for small business provisions...-1392 MHz band. (1) A very small business is an entity that, together with its controlling interests and...

47 CFR 27.807 - Designated entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 2 2010-10-01 2010-10-01 false Designated entities. 27.807 Section 27.807... COMMUNICATIONS SERVICES 1.4 GHz Band § 27.807 Designated entities. (a) Eligibility for small business provisions...-1392 MHz band. (1) A very small business is an entity that, together with its controlling interests and...

New insights into the classification and nomenclature of cortical GABAergic interneurons.

PubMed

DeFelipe, Javier; López-Cruz, Pedro L; Benavides-Piccione, Ruth; Bielza, Concha; Larrañaga, Pedro; Anderson, Stewart; Burkhalter, Andreas; Cauli, Bruno; Fairén, Alfonso; Feldmeyer, Dirk; Fishell, Gord; Fitzpatrick, David; Freund, Tamás F; González-Burgos, Guillermo; Hestrin, Shaul; Hill, Sean; Hof, Patrick R; Huang, Josh; Jones, Edward G; Kawaguchi, Yasuo; Kisvárday, Zoltán; Kubota, Yoshiyuki; Lewis, David A; Marín, Oscar; Markram, Henry; McBain, Chris J; Meyer, Hanno S; Monyer, Hannah; Nelson, Sacha B; Rockland, Kathleen; Rossier, Jean; Rubenstein, John L R; Rudy, Bernardo; Scanziani, Massimo; Shepherd, Gordon M; Sherwood, Chet C; Staiger, Jochen F; Tamás, Gábor; Thomson, Alex; Wang, Yun; Yuste, Rafael; Ascoli, Giorgio A

2013-03-01

A systematic classification and accepted nomenclature of neuron types is much needed but is currently lacking. This article describes a possible taxonomical solution for classifying GABAergic interneurons of the cerebral cortex based on a novel, web-based interactive system that allows experts to classify neurons with pre-determined criteria. Using Bayesian analysis and clustering algorithms on the resulting data, we investigated the suitability of several anatomical terms and neuron names for cortical GABAergic interneurons. Moreover, we show that supervised classification models could automatically categorize interneurons in agreement with experts' assignments. These results demonstrate a practical and objective approach to the naming, characterization and classification of neurons based on community consensus.

42 CFR 425.104 - Legal entity.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 42 Public Health 3 2012-10-01 2012-10-01 false Legal entity. 425.104 Section 425.104 Public Health....104 Legal entity. (a) An ACO must be a legal entity, formed under applicable State, Federal, or Tribal... in this part. (b) An ACO formed by two or more otherwise independent ACO participants must be a legal...

42 CFR 425.104 - Legal entity.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 42 Public Health 3 2014-10-01 2014-10-01 false Legal entity. 425.104 Section 425.104 Public Health....104 Legal entity. (a) An ACO must be a legal entity, formed under applicable State, Federal, or Tribal... in this part. (b) An ACO formed by two or more otherwise independent ACO participants must be a legal...

42 CFR 425.104 - Legal entity.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 42 Public Health 3 2013-10-01 2013-10-01 false Legal entity. 425.104 Section 425.104 Public Health....104 Legal entity. (a) An ACO must be a legal entity, formed under applicable State, Federal, or Tribal... in this part. (b) An ACO formed by two or more otherwise independent ACO participants must be a legal...

CNN-based ranking for biomedical entity normalization.

PubMed

Li, Haodi; Chen, Qingcai; Tang, Buzhou; Wang, Xiaolong; Xu, Hua; Wang, Baohua; Huang, Dong

2017-10-03

Most state-of-the-art biomedical entity normalization systems, such as rule-based systems, merely rely on morphological information of entity mentions, but rarely consider their semantic information. In this paper, we introduce a novel convolutional neural network (CNN) architecture that regards biomedical entity normalization as a ranking problem and benefits from semantic information of biomedical entities. The CNN-based ranking method first generates candidates using handcrafted rules, and then ranks the candidates according to their semantic information modeled by CNN as well as their morphological information. Experiments on two benchmark datasets for biomedical entity normalization show that our proposed CNN-based ranking method outperforms traditional rule-based method with state-of-the-art performance. We propose a CNN architecture that regards biomedical entity normalization as a ranking problem. Comparison results show that semantic information is beneficial to biomedical entity normalization and can be well combined with morphological information in our CNN architecture for further improvement.

Soil geomorphic classification, soil taxonomy, and effects on soil richness assessments

Treesearch

Jonathan D. Phillips; Daniel A. Marion

2007-01-01

The study of pedodiversity and soil richness depends on the notion of soils as discrete entities. Soil classifications are often criticized in this regard because they depend in part on arbitrary or subjective criteria. In this study soils were categorized on the basis of the presence or absence of six lithological and morphological characteristics. Richness vs. area...

New insights into the classification and nomenclature of cortical GABAergic interneurons

PubMed Central

DeFelipe, Javier; López-Cruz, Pedro L.; Benavides-Piccione, Ruth; Bielza, Concha; Larrañaga, Pedro; Anderson, Stewart; Burkhalter, Andreas; Cauli, Bruno; Fairén, Alfonso; Feldmeyer, Dirk; Fishell, Gord; Fitzpatrick, David; Freund, Tamás F.; González-Burgos, Guillermo; Hestrin, Shaul; Hill, Sean; Hof, Patrick R.; Huang, Josh; Jones, Edward G.; Kawaguchi, Yasuo; Kisvárday, Zoltán; Kubota, Yoshiyuki; Lewis, David A.; Marín, Oscar; Markram, Henry; McBain, Chris J.; Meyer, Hanno S.; Monyer, Hannah; Nelson, Sacha B.; Rockland, Kathleen; Rossier, Jean; Rubenstein, John L. R.; Rudy, Bernardo; Scanziani, Massimo; Shepherd, Gordon M.; Sherwood, Chet C.; Staiger, Jochen F.; Tamás, Gábor; Thomson, Alex; Wang, Yun; Yuste, Rafael; Ascoli, Giorgio A.

2013-01-01

A systematic classification and accepted nomenclature of neuron types is much needed but is currently lacking. This article describes a possible taxonomical solution for classifying GABAergic interneurons of the cerebral cortex based on a novel, web-based interactive system that allows experts to classify neurons with pre-determined criteria. Using Bayesian analysis and clustering algorithms on the resulting data, we investigated the suitability of several anatomical terms and neuron names for cortical GABAergic interneurons. Moreover, we show that supervised classification models could automatically categorize interneurons in agreement with experts’ assignments. These results demonstrate a practical and objective approach to the naming, characterization and classification of neurons based on community consensus. PMID:23385869

Rule-guided human classification of Volunteered Geographic Information

NASA Astrophysics Data System (ADS)

Ali, Ahmed Loai; Falomir, Zoe; Schmid, Falko; Freksa, Christian

2017-05-01

During the last decade, web technologies and location sensing devices have evolved generating a form of crowdsourcing known as Volunteered Geographic Information (VGI). VGI acted as a platform of spatial data collection, in particular, when a group of public participants are involved in collaborative mapping activities: they work together to collect, share, and use information about geographic features. VGI exploits participants' local knowledge to produce rich data sources. However, the resulting data inherits problematic data classification. In VGI projects, the challenges of data classification are due to the following: (i) data is likely prone to subjective classification, (ii) remote contributions and flexible contribution mechanisms in most projects, and (iii) the uncertainty of spatial data and non-strict definitions of geographic features. These factors lead to various forms of problematic classification: inconsistent, incomplete, and imprecise data classification. This research addresses classification appropriateness. Whether the classification of an entity is appropriate or inappropriate is related to quantitative and/or qualitative observations. Small differences between observations may be not recognizable particularly for non-expert participants. Hence, in this paper, the problem is tackled by developing a rule-guided classification approach. This approach exploits data mining techniques of Association Classification (AC) to extract descriptive (qualitative) rules of specific geographic features. The rules are extracted based on the investigation of qualitative topological relations between target features and their context. Afterwards, the extracted rules are used to develop a recommendation system able to guide participants to the most appropriate classification. The approach proposes two scenarios to guide participants towards enhancing the quality of data classification. An empirical study is conducted to investigate the classification of grass

76 FR 78146 - Addition of Certain Persons to the Entity List; and Implementation of Entity List Annual Review...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-16

... of the annual review, and revises the entry concerning one person located in Malaysia to add an... Entity List. This rule implements the results of the annual review for entities located in Malaysia... during the annual review, this rule amends one entry currently on the Entity List under Malaysia by...

Leveraging Pattern Semantics for Extracting Entities in Enterprises.

PubMed

Tao, Fangbo; Zhao, Bo; Fuxman, Ariel; Li, Yang; Han, Jiawei

2015-05-01

Entity Extraction is a process of identifying meaningful entities from text documents. In enterprises, extracting entities improves enterprise efficiency by facilitating numerous applications, including search, recommendation, etc. However, the problem is particularly challenging on enterprise domains due to several reasons. First, the lack of redundancy of enterprise entities makes previous web-based systems like NELL and OpenIE not effective, since using only high-precision/low-recall patterns like those systems would miss the majority of sparse enterprise entities, while using more low-precision patterns in sparse setting also introduces noise drastically. Second, semantic drift is common in enterprises ("Blue" refers to "Windows Blue"), such that public signals from the web cannot be directly applied on entities. Moreover, many internal entities never appear on the web. Sparse internal signals are the only source for discovering them. To address these challenges, we propose an end-to-end framework for extracting entities in enterprises, taking the input of enterprise corpus and limited seeds to generate a high-quality entity collection as output. We introduce the novel concept of Semantic Pattern Graph to leverage public signals to understand the underlying semantics of lexical patterns, reinforce pattern evaluation using mined semantics, and yield more accurate and complete entities. Experiments on Microsoft enterprise data show the effectiveness of our approach.

77 FR 31843 - Unnamed Entity

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-30

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. EL12-70-000] Unnamed Entity v. California Independent System Operator Corp.; Notice of Complaint Take notice that on May 21... Commission's Rules of Practice and Procedure, 18 CFR part 206, Unnamed Entity (Complainant) filed a formal...

ADM. Service Building (TAN603). Floor plan. Names of functional areas. ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

ADM. Service Building (TAN-603). Floor plan. Names of functional areas. Ralph M. Parsons 902-2-ANY-603-A 43. Date: December 1952. Approved by INEEL Classification Office for public release. INEEL index code no. 033-0603-00-693-106718 - Idaho National Engineering Laboratory, Test Area North, Scoville, Butte County, ID

ADM. Change House (TAN606). Elevations and floor plan. Room Names. ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

ADM. Change House (TAN-606). Elevations and floor plan. Room Names. Ralph M. Parsons 902-2-ANP-606-A 65. Date: December 1952. Approved by INEEL Classification Office for public release. INEEL index code no. 035-0606-00-693-106733 - Idaho National Engineering Laboratory, Test Area North, Scoville, Butte County, ID

45 CFR 160.310 - Responsibilities of covered entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 45 Public Welfare 1 2010-10-01 2010-10-01 false Responsibilities of covered entities. 160.310... Responsibilities of covered entities. (a) Provide records and compliance reports. A covered entity must keep such... entity has complied or is complying with the applicable administrative simplification provisions. (b...

22 CFR 96.103 - Oversight by accrediting entities.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 22 Foreign Relations 1 2011-04-01 2011-04-01 false Oversight by accrediting entities. 96.103... Relating to Temporary Accreditation § 96.103 Oversight by accrediting entities. (a) The accrediting entity... agency's application for full accreditation when it is filed. The accrediting entity must also...

22 CFR 96.103 - Oversight by accrediting entities.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Oversight by accrediting entities. 96.103... Relating to Temporary Accreditation § 96.103 Oversight by accrediting entities. (a) The accrediting entity... agency's application for full accreditation when it is filed. The accrediting entity must also...

45 CFR 160.310 - Responsibilities of covered entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 45 Public Welfare 1 2011-10-01 2011-10-01 false Responsibilities of covered entities. 160.310... Responsibilities of covered entities. (a) Provide records and compliance reports. A covered entity must keep such... entity has complied or is complying with the applicable administrative simplification provisions. (b...

Classification of diffuse lung diseases: why and how.

PubMed

Hansell, David M

2013-09-01

The understanding of complex lung diseases, notably the idiopathic interstitial pneumonias and small airways diseases, owes as much to repeated attempts over the years to classify them as to any single conceptual breakthrough. One of the many benefits of a successful classification scheme is that it allows workers, within and between disciplines, to be clear that they are discussing the same disease. This may be of particular importance in the recruitment of individuals for a clinical trial that requires a standardized and homogeneous study population. Different specialties require fundamentally different things from a classification: for epidemiologic studies, a classification that requires categorization of individuals according to histopathologic pattern is not usually practicable. Conversely, a scheme that simply divides diffuse parenchymal disease into inflammatory and noninflammatory categories is unlikely to further the understanding about the pathogenesis of disease. Thus, for some disease groupings, for example, pulmonary vasculopathies, there may be several appropriate classifications, each with its merits and demerits. There has been an interesting shift in the past few years, from the accepted primacy of histopathology as the sole basis on which the classification of parenchymal lung disease has rested, to new ways of considering how these entities relate to each other. Some inventive thinking has resulted in new classifications that undoubtedly benefit patients and clinicians in their endeavor to improve management and outcome. The challenge of understanding the logic behind current classifications and their shortcomings are explored in various examples of lung diseases.

Treatment-Based Classification versus Usual Care for Management of Low Back Pain

DTIC Science & Technology

2017-10-01

AWARD NUMBER: W81XWH-11-1-0657 TITLE: Treatment-Based Classification versus Usual Care for Management of Low Back Pain PRINCIPAL INVESTIGATOR...Treatment-Based Classification versus Usual Care for Management of Low Back Pain 5b. GRANT NUMBER W81XWH-11-1-0657 5c. PROGRAM ELEMENT NUMBER 6...AUTHOR(S) MAJ Daniel Rhon – daniel_rhon@baylor.edu 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S

31 CFR 546.304 - Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Entity. 546.304 Section 546.304 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS CONTROL, DEPARTMENT OF THE TREASURY DARFUR SANCTIONS REGULATIONS General Definitions § 546.304 Entity. The...

31 CFR 510.303 - Entity.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 31 Money and Finance:Treasury 3 2013-07-01 2013-07-01 false Entity. 510.303 Section 510.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS CONTROL, DEPARTMENT OF THE TREASURY NORTH KOREA SANCTIONS REGULATIONS General Definitions § 510.303 Entity...

31 CFR 510.303 - Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Entity. 510.303 Section 510.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS CONTROL, DEPARTMENT OF THE TREASURY NORTH KOREA SANCTIONS REGULATIONS General Definitions § 510.303 Entity...

31 CFR 510.303 - Entity.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 31 Money and Finance:Treasury 3 2014-07-01 2014-07-01 false Entity. 510.303 Section 510.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS CONTROL, DEPARTMENT OF THE TREASURY NORTH KOREA SANCTIONS REGULATIONS General Definitions § 510.303 Entity...

31 CFR 510.303 - Entity.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 31 Money and Finance:Treasury 3 2012-07-01 2012-07-01 false Entity. 510.303 Section 510.303 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF FOREIGN ASSETS CONTROL, DEPARTMENT OF THE TREASURY NORTH KOREA SANCTIONS REGULATIONS General Definitions § 510.303 Entity...

Recognition of chemical entities: combining dictionary-based and grammar-based approaches.

PubMed

Akhondi, Saber A; Hettne, Kristina M; van der Horst, Eelke; van Mulligen, Erik M; Kors, Jan A

2015-01-01

The past decade has seen an upsurge in the number of publications in chemistry. The ever-swelling volume of available documents makes it increasingly hard to extract relevant new information from such unstructured texts. The BioCreative CHEMDNER challenge invites the development of systems for the automatic recognition of chemicals in text (CEM task) and for ranking the recognized compounds at the document level (CDI task). We investigated an ensemble approach where dictionary-based named entity recognition is used along with grammar-based recognizers to extract compounds from text. We assessed the performance of ten different commercial and publicly available lexical resources using an open source indexing system (Peregrine), in combination with three different chemical compound recognizers and a set of regular expressions to recognize chemical database identifiers. The effect of different stop-word lists, case-sensitivity matching, and use of chunking information was also investigated. We focused on lexical resources that provide chemical structure information. To rank the different compounds found in a text, we used a term confidence score based on the normalized ratio of the term frequencies in chemical and non-chemical journals. The use of stop-word lists greatly improved the performance of the dictionary-based recognition, but there was no additional benefit from using chunking information. A combination of ChEBI and HMDB as lexical resources, the LeadMine tool for grammar-based recognition, and the regular expressions, outperformed any of the individual systems. On the test set, the F-scores were 77.8% (recall 71.2%, precision 85.8%) for the CEM task and 77.6% (recall 71.7%, precision 84.6%) for the CDI task. Missed terms were mainly due to tokenization issues, poor recognition of formulas, and term conjunctions. We developed an ensemble system that combines dictionary-based and grammar-based approaches for chemical named entity recognition, outperforming

Recognition of chemical entities: combining dictionary-based and grammar-based approaches

PubMed Central

2015-01-01

Background The past decade has seen an upsurge in the number of publications in chemistry. The ever-swelling volume of available documents makes it increasingly hard to extract relevant new information from such unstructured texts. The BioCreative CHEMDNER challenge invites the development of systems for the automatic recognition of chemicals in text (CEM task) and for ranking the recognized compounds at the document level (CDI task). We investigated an ensemble approach where dictionary-based named entity recognition is used along with grammar-based recognizers to extract compounds from text. We assessed the performance of ten different commercial and publicly available lexical resources using an open source indexing system (Peregrine), in combination with three different chemical compound recognizers and a set of regular expressions to recognize chemical database identifiers. The effect of different stop-word lists, case-sensitivity matching, and use of chunking information was also investigated. We focused on lexical resources that provide chemical structure information. To rank the different compounds found in a text, we used a term confidence score based on the normalized ratio of the term frequencies in chemical and non-chemical journals. Results The use of stop-word lists greatly improved the performance of the dictionary-based recognition, but there was no additional benefit from using chunking information. A combination of ChEBI and HMDB as lexical resources, the LeadMine tool for grammar-based recognition, and the regular expressions, outperformed any of the individual systems. On the test set, the F-scores were 77.8% (recall 71.2%, precision 85.8%) for the CEM task and 77.6% (recall 71.7%, precision 84.6%) for the CDI task. Missed terms were mainly due to tokenization issues, poor recognition of formulas, and term conjunctions. Conclusions We developed an ensemble system that combines dictionary-based and grammar-based approaches for chemical named

45 CFR 162.923 - Requirements for covered entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 45 Public Welfare 1 2011-10-01 2011-10-01 false Requirements for covered entities. 162.923 Section... Requirements for covered entities. (a) General rule. Except as otherwise provided in this part, if a covered entity conducts, with another covered entity that is required to comply with a transaction standard...

45 CFR 150.307 - Notice to responsible entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 45 Public Welfare 1 2011-10-01 2011-10-01 false Notice to responsible entities. 150.307 Section... and Non-Federal Governmental Plans-Civil Money Penalties § 150.307 Notice to responsible entities. If... responsible entity or entities identified under § 150.305. The notice does the following: (a) Describes the...

45 CFR 162.923 - Requirements for covered entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 45 Public Welfare 1 2010-10-01 2010-10-01 false Requirements for covered entities. 162.923 Section... Requirements for covered entities. (a) General rule. Except as otherwise provided in this part, if a covered entity conducts, with another covered entity that is required to comply with a transaction standard...

45 CFR 150.307 - Notice to responsible entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 45 Public Welfare 1 2010-10-01 2010-10-01 false Notice to responsible entities. 150.307 Section... and Non-Federal Governmental Plans-Civil Money Penalties § 150.307 Notice to responsible entities. If... responsible entity or entities identified under § 150.305. The notice does the following: (a) Describes the...

12 CFR 1237.10 - Limited-life regulated entities.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 12 Banks and Banking 10 2014-01-01 2014-01-01 false Limited-life regulated entities. 1237.10... RECEIVERSHIP Limited-Life Regulated Entities § 1237.10 Limited-life regulated entities. (a) Status. The United... liquidity portfolio of a limited-life regulated entity. (c) Policies and procedures. The Agency may draft...

12 CFR 1237.10 - Limited-life regulated entities.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 12 Banks and Banking 9 2013-01-01 2013-01-01 false Limited-life regulated entities. 1237.10... RECEIVERSHIP Limited-Life Regulated Entities § 1237.10 Limited-life regulated entities. (a) Status. The United... liquidity portfolio of a limited-life regulated entity. (c) Policies and procedures. The Agency may draft...

12 CFR 1237.10 - Limited-life regulated entities.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 12 Banks and Banking 9 2012-01-01 2012-01-01 false Limited-life regulated entities. 1237.10... RECEIVERSHIP Limited-Life Regulated Entities § 1237.10 Limited-life regulated entities. (a) Status. The United... liquidity portfolio of a limited-life regulated entity. (c) Policies and procedures. The Agency may draft...

Text Classification for Organizational Researchers

PubMed Central

Kobayashi, Vladimer B.; Mol, Stefan T.; Berkers, Hannah A.; Kismihók, Gábor; Den Hartog, Deanne N.

2017-01-01

Organizations are increasingly interested in classifying texts or parts thereof into categories, as this enables more effective use of their information. Manual procedures for text classification work well for up to a few hundred documents. However, when the number of documents is larger, manual procedures become laborious, time-consuming, and potentially unreliable. Techniques from text mining facilitate the automatic assignment of text strings to categories, making classification expedient, fast, and reliable, which creates potential for its application in organizational research. The purpose of this article is to familiarize organizational researchers with text mining techniques from machine learning and statistics. We describe the text classification process in several roughly sequential steps, namely training data preparation, preprocessing, transformation, application of classification techniques, and validation, and provide concrete recommendations at each step. To help researchers develop their own text classifiers, the R code associated with each step is presented in a tutorial. The tutorial draws from our own work on job vacancy mining. We end the article by discussing how researchers can validate a text classification model and the associated output. PMID:29881249

Survey-based naming conventions for use in OBO Foundry ontology development

PubMed Central

Schober, Daniel; Smith, Barry; Lewis, Suzanna E; Kusnierczyk, Waclaw; Lomax, Jane; Mungall, Chris; Taylor, Chris F; Rocca-Serra, Philippe; Sansone, Susanna-Assunta

2009-01-01

Background A wide variety of ontologies relevant to the biological and medical domains are available through the OBO Foundry portal, and their number is growing rapidly. Integration of these ontologies, while requiring considerable effort, is extremely desirable. However, heterogeneities in format and style pose serious obstacles to such integration. In particular, inconsistencies in naming conventions can impair the readability and navigability of ontology class hierarchies, and hinder their alignment and integration. While other sources of diversity are tremendously complex and challenging, agreeing a set of common naming conventions is an achievable goal, particularly if those conventions are based on lessons drawn from pooled practical experience and surveys of community opinion. Results We summarize a review of existing naming conventions and highlight certain disadvantages with respect to general applicability in the biological domain. We also present the results of a survey carried out to establish which naming conventions are currently employed by OBO Foundry ontologies and to determine what their special requirements regarding the naming of entities might be. Lastly, we propose an initial set of typographic, syntactic and semantic conventions for labelling classes in OBO Foundry ontologies. Conclusion Adherence to common naming conventions is more than just a matter of aesthetics. Such conventions provide guidance to ontology creators, help developers avoid flaws and inaccuracies when editing, and especially when interlinking, ontologies. Common naming conventions will also assist consumers of ontologies to more readily understand what meanings were intended by the authors of ontologies used in annotating bodies of data. PMID:19397794

Leveraging Pattern Semantics for Extracting Entities in Enterprises

PubMed Central

Tao, Fangbo; Zhao, Bo; Fuxman, Ariel; Li, Yang; Han, Jiawei

2015-01-01

Entity Extraction is a process of identifying meaningful entities from text documents. In enterprises, extracting entities improves enterprise efficiency by facilitating numerous applications, including search, recommendation, etc. However, the problem is particularly challenging on enterprise domains due to several reasons. First, the lack of redundancy of enterprise entities makes previous web-based systems like NELL and OpenIE not effective, since using only high-precision/low-recall patterns like those systems would miss the majority of sparse enterprise entities, while using more low-precision patterns in sparse setting also introduces noise drastically. Second, semantic drift is common in enterprises (“Blue” refers to “Windows Blue”), such that public signals from the web cannot be directly applied on entities. Moreover, many internal entities never appear on the web. Sparse internal signals are the only source for discovering them. To address these challenges, we propose an end-to-end framework for extracting entities in enterprises, taking the input of enterprise corpus and limited seeds to generate a high-quality entity collection as output. We introduce the novel concept of Semantic Pattern Graph to leverage public signals to understand the underlying semantics of lexical patterns, reinforce pattern evaluation using mined semantics, and yield more accurate and complete entities. Experiments on Microsoft enterprise data show the effectiveness of our approach. PMID:26705540

Wishart Deep Stacking Network for Fast POLSAR Image Classification.

PubMed

Jiao, Licheng; Liu, Fang

2016-05-11

Inspired by the popular deep learning architecture - Deep Stacking Network (DSN), a specific deep model for polarimetric synthetic aperture radar (POLSAR) image classification is proposed in this paper, which is named as Wishart Deep Stacking Network (W-DSN). First of all, a fast implementation of Wishart distance is achieved by a special linear transformation, which speeds up the classification of POLSAR image and makes it possible to use this polarimetric information in the following Neural Network (NN). Then a single-hidden-layer neural network based on the fast Wishart distance is defined for POLSAR image classification, which is named as Wishart Network (WN) and improves the classification accuracy. Finally, a multi-layer neural network is formed by stacking WNs, which is in fact the proposed deep learning architecture W-DSN for POLSAR image classification and improves the classification accuracy further. In addition, the structure of WN can be expanded in a straightforward way by adding hidden units if necessary, as well as the structure of the W-DSN. As a preliminary exploration on formulating specific deep learning architecture for POLSAR image classification, the proposed methods may establish a simple but clever connection between POLSAR image interpretation and deep learning. The experiment results tested on real POLSAR image show that the fast implementation of Wishart distance is very efficient (a POLSAR image with 768000 pixels can be classified in 0.53s), and both the single-hidden-layer architecture WN and the deep learning architecture W-DSN for POLSAR image classification perform well and work efficiently.

Headache classification: criticism and suggestions.

PubMed

Manzoni, G C; Torelli, P

2004-10-01

The International Classification of Headache Disorders 2nd Edition (ICHD-II), published in 2004, marks an unquestionable progress from the preceding 1988 edition, but the in-depth analysis it offers is not immune from drawbacks and shortcomings. First of all, it is still basically a classification of attacks and not of syndromes. For the migraine group, while the revised classification more accurately characterises migraine with aura, it fails to provide a sufficiently structured description of those forms of migraine without aura that over the years evolve to so-called daily chronic forms. These forms are not adequately recognised as chronic migraine, which ICHD-II includes among the complications of migraine. The inclusion of short-lasting unilateral neuralgiform headache attacks with conjunctival injection and tearing (SUNCT) in the cluster headache group is bound to generate some perplexity, while the recognition of new daily persistent headache (NDPH) included in the group of other primary headaches as a separate clinical entity appears somewhat premature. Doubts are also raised by the actual existence of triptan-overuse headache, which ICHD-II includes in Group 8 among medication-overuse headaches. Finally, the addition of headache attributed to psychiatric disorder, which is certainly a good option in perspective, is not yet supported by an adequate systematisation.

22 CFR 96.8 - Fees charged by accrediting entities.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Fees charged by accrediting entities. 96.8... Duties of Accrediting Entities § 96.8 Fees charged by accrediting entities. (a) An accrediting entity may... fees approved by the Secretary. Before approving a schedule of fees proposed by an accrediting entity...

A web-based land cover classification system based on ontology model of different classification systems

NASA Astrophysics Data System (ADS)

Lin, Y.; Chen, X.

2016-12-01

Land cover classification systems used in remote sensing image data have been developed to meet the needs for depicting land covers in scientific investigations and policy decisions. However, accuracy assessments of a spate of data sets demonstrate that compared with the real physiognomy, each of the thematic map of specific land cover classification system contains some unavoidable flaws and unintended deviation. This work proposes a web-based land cover classification system, an integrated prototype, based on an ontology model of various classification systems, each of which is assigned the same weight in the final determination of land cover type. Ontology, a formal explication of specific concepts and relations, is employed in this prototype to build up the connections among different systems to resolve the naming conflicts. The process is initialized by measuring semantic similarity between terminologies in the systems and the search key to produce certain set of satisfied classifications, and carries on through searching the predefined relations in concepts of all classification systems to generate classification maps with user-specified land cover type highlighted, based on probability calculated by votes from data sets with different classification system adopted. The present system is verified and validated by comparing the classification results with those most common systems. Due to full consideration and meaningful expression of each classification system using ontology and the convenience that the web brings with itself, this system, as a preliminary model, proposes a flexible and extensible architecture for classification system integration and data fusion, thereby providing a strong foundation for the future work.

42 CFR 417.484 - Requirement applicable to related entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 3 2011-10-01 2011-10-01 false Requirement applicable to related entities. 417.484... entities. (a) Definition. As used in this section, related entity means any entity that is related to the... agrees to require all related entities to agree that— (1) HHS, the Comptroller General, or their...

42 CFR 417.484 - Requirement applicable to related entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 3 2010-10-01 2010-10-01 false Requirement applicable to related entities. 417.484... entities. (a) Definition. As used in this section, related entity means any entity that is related to the... agrees to require all related entities to agree that— (1) HHS, the Comptroller General, or their...

17 CFR 45.6 - Legal entity identifiers

Code of Federal Regulations, 2014 CFR

2014-04-01

... 17 Commodity and Securities Exchanges 2 2014-04-01 2014-04-01 false Legal entity identifiers 45.6... RECORDKEEPING AND REPORTING REQUIREMENTS § 45.6 Legal entity identifiers Each counterparty to any swap subject... reporting pursuant to this part by means of a single legal entity identifier as specified in this section...

31 CFR 535.301 - Iran; Iranian Entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Iran; Iranian Entity. 535.301 Section 535.301 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF... § 535.301 Iran; Iranian Entity. (a) The term Iran and Iranian Entity includes: (1) The state and the...

31 CFR 535.301 - Iran; Iranian Entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Iran; Iranian Entity. 535.301 Section 535.301 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued) OFFICE OF... § 535.301 Iran; Iranian Entity. (a) The term Iran and Iranian Entity includes: (1) The state and the...

Classifications for carcinogenesis of antitumoral drugs.

PubMed

Binetti, R; Costamagna, F M; Marcello, I

2003-12-01

The aim of this review is to support the medical staff engaged in tumor therapy with the carcinogenicity, mutagenicity, developmental toxicity classification of a large number of chemiotherapic drugs by national and international Agencies; it also gives their rationale and the few cases for which the classification varies among, for example, the European Union and the United States of America. A large list of such drugs, producers, commercial names, CAS numbers and chemical names is reported. This list is subject to changes for the quick development in this field: many drugs are retired and many more are introduced in clinical practice. The list is updated to the summer 2003 and retains many drugs which have more than one use or have limited use. The protection of the medical personnel using antitumor chemiotherapics can need retrospective epidemiological investigations and obsolete drugs are of importance for some of the past exposures.

31 CFR 535.301 - Iran; Iranian Entity.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 31 Money and Finance:Treasury 3 2013-07-01 2013-07-01 false Iran; Iranian Entity. 535.301 Section... § 535.301 Iran; Iranian Entity. (a) The term Iran and Iranian Entity includes: (1) The state and the Government of Iran as well as any political subdivision, agency, or instrumentality thereof or any territory...

31 CFR 535.301 - Iran; Iranian Entity.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 31 Money and Finance:Treasury 3 2012-07-01 2012-07-01 false Iran; Iranian Entity. 535.301 Section... § 535.301 Iran; Iranian Entity. (a) The term Iran and Iranian Entity includes: (1) The state and the Government of Iran as well as any political subdivision, agency, or instrumentality thereof or any territory...

31 CFR 535.301 - Iran; Iranian Entity.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 31 Money and Finance:Treasury 3 2014-07-01 2014-07-01 false Iran; Iranian Entity. 535.301 Section... § 535.301 Iran; Iranian Entity. (a) The term Iran and Iranian Entity includes: (1) The state and the Government of Iran as well as any political subdivision, agency, or instrumentality thereof or any territory...

[Classification of memory systems: a revision].

PubMed

Agrest, M

2001-12-01

The present paper exposes the arguments against considering memory as a monolytic entity and how is it to be divided into several systems in order to understand its operation. Historically this division was acknowledge by different authors but in the last few decades it received the confirmation from the scientific research. The most accepted taxonomy establishes the existence of two major memory systems: declarative and non declarative memory. The article also presents the arguments for and against this kind of division, as well as an alternative classification in five major systems: procedural, perceptual representation, semantic, primary and episodic.

14 CFR Sec. 1-6 - Accounting entities.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 4 2011-01-01 2011-01-01 false Accounting entities. Sec. 1-6 Section 1-6... Provisions Sec. 1-6 Accounting entities. (a) Separate accounting records shall be maintained for each air transport entity for which separate reports to the BTS are required to be made by sections 21(g) and for...

47 CFR 27.1218 - Designated entities.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 47 Telecommunication 2 2014-10-01 2014-10-01 false Designated entities. 27.1218 Section 27.1218 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES MISCELLANEOUS WIRELESS COMMUNICATIONS SERVICES Broadband Radio Service and Educational Broadband Service § 27.1218 Designated entities...

47 CFR 27.1218 - Designated entities.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 47 Telecommunication 2 2013-10-01 2013-10-01 false Designated entities. 27.1218 Section 27.1218 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) COMMON CARRIER SERVICES MISCELLANEOUS WIRELESS COMMUNICATIONS SERVICES Broadband Radio Service and Educational Broadband Service § 27.1218 Designated entities...

78 FR 22270 - Special Fraud Alert: Physician-Owned Entities

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-15

...] Special Fraud Alert: Physician-Owned Entities AGENCY: Office of Inspector General (OIG), HHS. ACTION... Physician-Owned Entities. Specifically, the Special Fraud Alert addressed physician-owned entities that... publication of the Special Fraud Alert on Physician-Owned Entities, an inadvertent error appeared in the DATES...

The 2017 World Health Organization classification of tumors of the pituitary gland: a summary.

PubMed

Lopes, M Beatriz S

2017-10-01

The 4th edition of the World Health Organization (WHO) classification of endocrine tumors has been recently released. In this new edition, major changes are recommended in several areas of the classification of tumors of the anterior pituitary gland (adenophypophysis). The scope of the present manuscript is to summarize these recommended changes, emphasizing a few significant topics. These changes include the following: (1) a novel approach for classifying pituitary neuroendocrine tumors according to pituitary adenohypophyseal cell lineages; (2) changes to the histological grading of pituitary neuroendocrine tumors with the elimination of the term "atypical adenoma;" and (3) introduction of new entities like the pituitary blastoma and re-definition of old entities like the null-cell adenoma. This new classification is very practical and mostly based on immunohistochemistry for pituitary hormones, pituitary-specific transcription factors, and other immunohistochemical markers commonly used in pathology practice, not requiring routine ultrastructural analysis of the tumors. Evaluation of tumor proliferation potential, by mitotic count and Ki-67 labeling index, and tumor invasion is strongly recommended on individual case basis to identify clinically aggressive adenomas. In addition, the classification offers the treating clinical team information on tumor prognosis by identifying specific variants of adenomas associated with an elevated risk for recurrence. Changes in the classification of non-neuroendocrine tumors are also proposed, in particular those tumors arising in the posterior pituitary including pituicytoma, granular cell tumor of the posterior pituitary, and spindle cell oncocytoma. These changes endorse those previously published in the 2016 WHO classification of CNS tumors. Other tumors arising in the sellar region are also reviewed in detail including craniopharyngiomas, mesenchymal and stromal tumors, germ cell tumors, and hematopoietic tumors. It is

Classification of mental disorders*

PubMed Central

Stengel, E.

1959-01-01

One of the fundamental difficulties in devising a classification of mental disorders is the lack of agreement among psychiatrists regarding the concepts upon which it should be based: diagnoses can rarely be verified objectively and the same or similar conditions are described under a confusing variety of names. This situation militates against the ready exchange of ideas and experiences and hampers progress. As a first step towards remedying this state of affairs, the author of the article below has undertaken a critical survey of existing classifications. He shows how some of the difficulties created by lack of knowledge regarding pathology and etiology may be overcome by the use of “operational definitions” and outlines the basic principles on which he believes a generally acceptable international classification might be constructed. If this can be done it should lead to a greater measure of agreement regarding the value of specific treatments for mental disorders and greatly facilitate a broad epidemiological approach to psychiatric research. PMID:13834299

Chemical entity recognition in patents by combining dictionary-based and statistical approaches

PubMed Central

Akhondi, Saber A.; Pons, Ewoud; Afzal, Zubair; van Haagen, Herman; Becker, Benedikt F.H.; Hettne, Kristina M.; van Mulligen, Erik M.; Kors, Jan A.

2016-01-01

We describe the development of a chemical entity recognition system and its application in the CHEMDNER-patent track of BioCreative 2015. This community challenge includes a Chemical Entity Mention in Patents (CEMP) recognition task and a Chemical Passage Detection (CPD) classification task. We addressed both tasks by an ensemble system that combines a dictionary-based approach with a statistical one. For this purpose the performance of several lexical resources was assessed using Peregrine, our open-source indexing engine. We combined our dictionary-based results on the patent corpus with the results of tmChem, a chemical recognizer using a conditional random field classifier. To improve the performance of tmChem, we utilized three additional features, viz. part-of-speech tags, lemmas and word-vector clusters. When evaluated on the training data, our final system obtained an F-score of 85.21% for the CEMP task, and an accuracy of 91.53% for the CPD task. On the test set, the best system ranked sixth among 21 teams for CEMP with an F-score of 86.82%, and second among nine teams for CPD with an accuracy of 94.23%. The differences in performance between the best ensemble system and the statistical system separately were small. Database URL: http://biosemantics.org/chemdner-patents PMID:27141091

Classification of chemical substances, reactions, and interactions: The effect of expertise

NASA Astrophysics Data System (ADS)

Stains, Marilyne Nicole Olivia

2007-12-01

This project explored the strategies that undergraduate and graduate chemistry students engaged in when solving classification tasks involving microscopic (particulate) representations of chemical substances and microscopic and symbolic representations of different chemical reactions. We were specifically interested in characterizing the basic features to which students pay attention while classifying, identifying the patterns of reasoning that they follow, and comparing the performance of students with different levels of preparation in the discipline. In general, our results suggest that advanced levels of expertise in chemical classification do not necessarily evolve in a linear and continuous way with academic training. Novice students had a tendency to reduce the cognitive demand of the task and rely on common-sense reasoning; they had difficulties differentiating concepts (conceptual undifferentiation) and based their classification decisions on only one variable (reduction). These ways of thinking lead them to consider extraneous features, pay more attention to explicit or surface features than implicit features and to overlook important and relevant features. However, unfamiliar levels of representations (microscopic level) seemed to trigger deeper and more meaningful thinking processes. On the other hand, expert students classified entities using a specific set of rules that they applied throughout the classification tasks. They considered a larger variety of implicit features and the unfamiliarity with the microscopic level of representation did not affect their reasoning processes. Consequently, novices created numerous small groups, few of them being chemically meaningful, while experts created few but large chemically meaningful groups. Novices also had difficulties correctly classifying entities in chemically meaningful groups. Finally, expert chemists in our study used classification schemes that are not necessarily traditionally taught in classroom

Data mining for clustering naming of the village at Java Island

NASA Astrophysics Data System (ADS)

Setiawan Abdullah, Atje; Nurani Ruchjana, Budi; Hidayat, Akik; Akmal; Setiana, Deni

2017-10-01

Clustering of query based data mining to identify the meaning of the naming of the village in Java island, done by exploring the database village with three categories namely: prefix in the naming of the village, syllables contained in the naming of the village, and full word naming of the village which is actually used. While syllables contained in the naming of the village are classified by the behaviour of the culture and character of each province that describes the business, feelings, circumstances, places, nature, respect, plants, fruits, and animals. Sources of data used for the clustering of the naming of the village on the island of Java was obtained from Geospatial Information Agency (BIG) in the form of a complete village name data with the coordinates in six provinces in Java, which is arranged in a hierarchy of provinces, districts / cities, districts and villages. The research method using KDD (Knowledge Discovery in Database) through the process of preprocessing, data mining and postprocessing to obtain knowledge. In this study, data mining applications to facilitate the search query based on the name of the village, using Java software. While the contours of a map is processed using ArcGIS software. The results of the research can give recommendations to stakeholders such as the Department of Tourism to describe the meaning of the classification of naming the village according to the character in each province at Java island.

Processing new and repeated names: Effects of coreference on repetition priming with speech and fast RSVP

PubMed Central

Camblin, C. Christine; Ledoux, Kerry; Boudewyn, Megan; Gordon, Peter C.; Swaab, Tamara Y.

2006-01-01

Previous research has shown that the process of establishing coreference with a repeated name can affect basic repetition priming. Specifically, repetition priming on some measures can be eliminated for repeated names that corefer with an entity that is prominent in the discourse model. However, the exact nature and timing of this modulating effect of discourse are not yet understood. Here, we present two ERP studies that further probe the nature of repeated name coreference by using naturally produced connected speech and fast-rate RSVP methods of presentation. With speech we found that repetition priming was eliminated for repeated names that coreferred with a prominent antecedent. In contrast, with fast-rate RSVP, we found a main effect of repetition that did not interact with sentence context. This indicates that the creation of a discourse model during comprehension can affect repetition priming, but the nature of this effect may depend on input speed. PMID:16904078

14 CFR 1-6 - Accounting entities.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 4 2012-01-01 2012-01-01 false Accounting entities. Sec. 1-6 Section Sec. 1-6 Aeronautics and Space OFFICE OF THE SECRETARY, DEPARTMENT OF TRANSPORTATION (AVIATION... General Accounting Provisions Sec. 1-6 Accounting entities. (a) Separate accounting records shall be...

46 CFR 403.110 - Accounting entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 8 2010-10-01 2010-10-01 false Accounting entities. 403.110 Section 403.110 Shipping COAST GUARD (GREAT LAKES PILOTAGE), DEPARTMENT OF HOMELAND SECURITY GREAT LAKES PILOTAGE UNIFORM ACCOUNTING SYSTEM General § 403.110 Accounting entities. Each Association shall be a separate accounting...

42 CFR 410.145 - Requirements for entities.

Code of Federal Regulations, 2014 CFR

2014-10-01

... PROGRAM SUPPLEMENTARY MEDICAL INSURANCE (SMI) BENEFITS Outpatient Diabetes Self-Management Training and Diabetes Outcome Measurements § 410.145 Requirements for entities. (a) Deemed entities. (1) Except as...

42 CFR 410.145 - Requirements for entities.

Code of Federal Regulations, 2013 CFR

2013-10-01

... PROGRAM SUPPLEMENTARY MEDICAL INSURANCE (SMI) BENEFITS Outpatient Diabetes Self-Management Training and Diabetes Outcome Measurements § 410.145 Requirements for entities. (a) Deemed entities. (1) Except as...

42 CFR 410.145 - Requirements for entities.

Code of Federal Regulations, 2012 CFR

2012-10-01

... PROGRAM SUPPLEMENTARY MEDICAL INSURANCE (SMI) BENEFITS Outpatient Diabetes Self-Management Training and Diabetes Outcome Measurements § 410.145 Requirements for entities. (a) Deemed entities. (1) Except as...

Primary Immunodeficiency Diseases: An Update on the Classification from the International Union of Immunological Societies Expert Committee for Primary Immunodeficiency

PubMed Central

Al-Herz, Waleed; Bousfiha, Aziz; Casanova, Jean-Laurent; Chapel, Helen; Conley, Mary Ellen; Cunningham-Rundles, Charlotte; Etzioni, Amos; Fischer, Alain; Franco, Jose Luis; Geha, Raif S.; Hammarström, Lennart; Nonoyama, Shigeaki; Notarangelo, Luigi Daniele; Ochs, Hans Dieter; Puck, Jennifer M.; Roifman, Chaim M.; Seger, Reinhard; Tang, Mimi L. K.

2011-01-01

We report the updated classification of primary immunodeficiency diseases, compiled by the ad hoc Expert Committee of the International Union of Immunological Societies. As compared to the previous edition, more than 15 novel disease entities have been added in the updated version. For each disorders, the key clinical and laboratory features are provided. This updated classification is meant to help in the diagnostic approach to patients with these diseases. PMID:22566844

17 CFR 202.8 - Small entity compliance guides.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 17 Commodity and Securities Exchanges 2 2010-04-01 2010-04-01 false Small entity compliance guides. 202.8 Section 202.8 Commodity and Securities Exchanges SECURITIES AND EXCHANGE COMMISSION INFORMAL AND OTHER PROCEDURES § 202.8 Small entity compliance guides. The following small entity compliance guides...

17 CFR 202.8 - Small entity compliance guides.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 17 Commodity and Securities Exchanges 2 2011-04-01 2011-04-01 false Small entity compliance guides. 202.8 Section 202.8 Commodity and Securities Exchanges SECURITIES AND EXCHANGE COMMISSION INFORMAL AND OTHER PROCEDURES § 202.8 Small entity compliance guides. The following small entity compliance guides...

31 CFR 537.312 - Nongovernmental entity in Burma.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 31 Money and Finance: Treasury 3 2010-07-01 2010-07-01 false Nongovernmental entity in Burma. 537.312 Section 537.312 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued... Definitions § 537.312 Nongovernmental entity in Burma. The term nongovernmental entity in Burma means a...

31 CFR 537.312 - Nongovernmental entity in Burma.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 31 Money and Finance:Treasury 3 2011-07-01 2011-07-01 false Nongovernmental entity in Burma. 537.312 Section 537.312 Money and Finance: Treasury Regulations Relating to Money and Finance (Continued... Definitions § 537.312 Nongovernmental entity in Burma. The term nongovernmental entity in Burma means a...

26 CFR 301.7701-5 - Domestic and foreign business entities.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 26 Internal Revenue 18 2010-04-01 2010-04-01 false Domestic and foreign business entities. 301... foreign business entities. (a) Domestic and foreign business entities. A business entity (including an entity that is disregarded as separate from its owner under § 301.7701-2(c)) is domestic if it is created...

26 CFR 301.7701-5 - Domestic and foreign business entities.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 26 Internal Revenue 18 2011-04-01 2011-04-01 false Domestic and foreign business entities. 301... foreign business entities. (a) Domestic and foreign business entities. A business entity (including an entity that is disregarded as separate from its owner under § 301.7701-2(c)) is domestic if it is created...

Refinement of diagnosis and disease classification in psychiatry.

PubMed

Lecrubier, Yves

2008-03-01

Knowledge concerning the classification of mental disorders progressed substantially with the use of DSM III-IV and IDCD 10 because it was based on observed data, with precise definitions. These classifications a priori avoided to generate definitions related to etiology or treatment response. They are based on a categorical approach where diagnostic entities share common phenomenological features. Modifications proposed or discussed are related to the weak validity of the classification strategy described above. (a) Disorders are supposed to be independent but the current coexistence of two or more disorders is the rule; (b) They also are supposed to have stability, however anxiety disorders most of the time precede major depression. For GAD age at onset, family history, biology and symptomatology are close to those of depression. As a consequence broader entities such as depression-GAD spectrum, panic-phobias spectrum and OCD spectrum including eating disorders and pathological gambling are taken into consideration; (c) Diagnostic categories use thresholds to delimitate a border with normals. This creates "subthreshold" conditions. The relevance of such conditions is well documented. Measuring the presence and severity of different dimensions, independent from a threshold, will improve the relevance of the description of patients pathology. In addition, this dimensional approach will improve the problems posed by the mutually exclusive diagnoses (depression and GAD, schizophrenia and depression); (d) Some disorders are based on the coexistence of different dimensions. Patients may present only one set of symptoms and have different characteristics, evolution and response to treatment. An example would be negative symptoms in Schizophrenia; (e) Because no etiological model is available and most measures are subjective, objective measures (cognitive, biological) and genetics progresses created important hopes. None of these measures is pathognomonic and most appear

26 CFR 1.892-5 - Controlled commercial entity.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 26 Internal Revenue 9 2010-04-01 2010-04-01 false Controlled commercial entity. 1.892-5 Section 1... (CONTINUED) INCOME TAXES Miscellaneous Provisions § 1.892-5 Controlled commercial entity. (a)-(a)(2...)(B), the term entity means and includes a corporation, a partnership, a trust (including a pension...

26 CFR 1.892-5 - Controlled commercial entity.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 26 Internal Revenue 9 2011-04-01 2011-04-01 false Controlled commercial entity. 1.892-5 Section 1... (CONTINUED) INCOME TAXES (CONTINUED) Miscellaneous Provisions § 1.892-5 Controlled commercial entity. (a)-(a... section 892(a)(2)(B), the term entity means and includes a corporation, a partnership, a trust (including...

22 CFR 96.21 - Choosing an accrediting entity.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Choosing an accrediting entity. 96.21 Section... Accreditation and Approval § 96.21 Choosing an accrediting entity. (a) An agency that seeks to become accredited must apply to an accrediting entity that is designated to provide accreditation services and that has...

22 CFR 96.21 - Choosing an accrediting entity.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 22 Foreign Relations 1 2011-04-01 2011-04-01 false Choosing an accrediting entity. 96.21 Section... Accreditation and Approval § 96.21 Choosing an accrediting entity. (a) An agency that seeks to become accredited must apply to an accrediting entity that is designated to provide accreditation services and that has...

Hypochromic vitiligo: delineation of a new entity.

PubMed

Ezzedine, K; Mahé, A; van Geel, N; Cardot-Leccia, N; Gauthier, Y; Descamps, V; Al Issa, A; Ly, F; Chosidow, O; Taïeb, A; Passeron, T

2015-03-01

Hypochromic vitiligo is a rare entity that has been reported only twice under the term 'vitiligo minor', with an absence of clear delineation. To delineate hypochromic vitiligo through a case series of patients with typical bilateral hypopigmented lesions affecting the face and trunk. This is a retrospective multicentric evaluation study conducted in eight departments of dermatology in France, Belgium, Senegal and Saudi Arabia. Twenty-four cases of hypochromic vitiligo were identified. Fourteen were men and 10 women. The mean age at diagnosis was 35·4 years (range 8-66). Strikingly, all patients were dark skinned, with skin types V and VI. The pattern of distribution was highly similar in most of the patients (18 of 24), with involvement of the face and neck area predominating on seborrhoeic areas associated with multiple isolated hypopigmented macules involving predominantly the scalp. The retrospective nature of this study is its main limitation. Hypochromic vitiligo is not yet part of a conventional classification. The disease seems to be limited to individuals with dark skin types. Hypopigmented seborrhoeic face and neck involvement associated with hypopigmented macules of the trunk and scalp is the hallmark of the disease. © 2014 British Association of Dermatologists.

77 FR 24587 - Addition of Certain Persons to the Entity List; and Implementation of Entity List Annual Review...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-04-25

...; --Mahtab Technical Engineering Company; --Composite Propellant Missile Industry; and --Sanaye Sokhte... entity; 0 (i) By removing the ``Country'' column for South Korea, including the South Korean entity... Technical Engineering Company;. --Composite Propellant Missile Industry; and. --Sanaye Sokhte Morakab (SSM...

76 FR 63184 - Addition of Certain Persons on the Entity List; Implementation of Entity List Annual Review...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-12

... as a result of requests for removal submitted by each of these three persons, a review of information...-country) to entities identified on the Entity List require a license from the Bureau of Industry and... effective October 12, 2011. FOR FURTHER INFORMATION CONTACT: Karen Nies-Vogel, Chair, End-User Review...

45 CFR 158.603 - Notice to responsible entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 45 Public Welfare 1 2011-10-01 2011-10-01 false Notice to responsible entities. 158.603 Section... Notice to responsible entities. If HHS learns of a potential violation described in § 158.602 of this... violation. (b) Provide 30 days from the date of the notice for the responsible entity to respond and to...

Spatio-structural granularity of biological material entities

PubMed Central

2010-01-01

Background With the continuously increasing demands on knowledge- and data-management that databases have to meet, ontologies and the theories of granularity they use become more and more important. Unfortunately, currently used theories and schemes of granularity unnecessarily limit the performance of ontologies due to two shortcomings: (i) they do not allow the integration of multiple granularity perspectives into one granularity framework; (ii) they are not applicable to cumulative-constitutively organized material entities, which cover most of the biomedical material entities. Results The above mentioned shortcomings are responsible for the major inconsistencies in currently used spatio-structural granularity schemes. By using the Basic Formal Ontology (BFO) as a top-level ontology and Keet's general theory of granularity, a granularity framework is presented that is applicable to cumulative-constitutively organized material entities. It provides a scheme for granulating complex material entities into their constitutive and regional parts by integrating various compositional and spatial granularity perspectives. Within a scale dependent resolution perspective, it even allows distinguishing different types of representations of the same material entity. Within other scale dependent perspectives, which are based on specific types of measurements (e.g. weight, volume, etc.), the possibility of organizing instances of material entities independent of their parthood relations and only according to increasing measures is provided as well. All granularity perspectives are connected to one another through overcrossing granularity levels, together forming an integrated whole that uses the compositional object perspective as an integrating backbone. This granularity framework allows to consistently assign structural granularity values to all different types of material entities. Conclusions The here presented framework provides a spatio-structural granularity framework

New classification of epilepsy-related neoplasms: The clinical perspective.

PubMed

Kasper, Burkhard S; Kasper, Ekkehard M

2017-02-01

Neoplastic CNS lesions are a common cause of focal epilepsy refractory to anticonvulsant treatment, i.e. long-term epilepsy-associated tumors (LEATs). Epileptogenic tumors encompass a variety of intriguing lesions, e.g. dysembryoplastic neuroepithelial tumors or gangliogliomas, which differ from more common CNS neoplasms in their clinical context as well as on histopathology. Long-term epilepsy-associated tumor classification is a rapidly evolving issue in surgical neuropathology, with new entities still being elucidated. One major issue to be resolved is the inconsistent tissue criteria applied to LEAT accounting for high diagnostic variability between individual centers and studies, a problem recently leading to a proposal for a new histopathological classification by Blümcke et al. in Acta Neuropathol. 2014; 128: 39-54. While a new approach to tissue diagnosis is appreciated and needed, histomorphological criteria alone will not suffice and we here approach the situation of encountering a neoplastic lesion in an epilepsy patient from a clinical perspective. Clinical scenarios to be supported by an advanced LEAT classification will be illustrated and discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

14 CFR 252.19 - Single-entity charters.

Code of Federal Regulations, 2010 CFR

2010-01-01

...) ECONOMIC REGULATIONS SMOKING ABOARD AIRCRAFT § 252.19 Single-entity charters. On single-entity charters... flights is given notice of the smoking procedures for the flight at the time he or she first makes...

14 CFR 252.19 - Single-entity charters.

Code of Federal Regulations, 2011 CFR

2011-01-01

...) ECONOMIC REGULATIONS SMOKING ABOARD AIRCRAFT § 252.19 Single-entity charters. On single-entity charters... flights is given notice of the smoking procedures for the flight at the time he or she first makes...

14 CFR 252.19 - Single-entity charters.

Code of Federal Regulations, 2013 CFR

2013-01-01

...) ECONOMIC REGULATIONS SMOKING ABOARD AIRCRAFT § 252.19 Single-entity charters. On single-entity charters... flights is given notice of the smoking procedures for the flight at the time he or she first makes...

14 CFR 252.19 - Single-entity charters.

Code of Federal Regulations, 2014 CFR

2014-01-01

...) ECONOMIC REGULATIONS SMOKING ABOARD AIRCRAFT § 252.19 Single-entity charters. On single-entity charters... flights is given notice of the smoking procedures for the flight at the time he or she first makes...

14 CFR 252.19 - Single-entity charters.

Code of Federal Regulations, 2012 CFR

2012-01-01

...) ECONOMIC REGULATIONS SMOKING ABOARD AIRCRAFT § 252.19 Single-entity charters. On single-entity charters... flights is given notice of the smoking procedures for the flight at the time he or she first makes...

Development of a database of health insurance claims: standardization of disease classifications and anonymous record linkage.

PubMed

Kimura, Shinya; Sato, Toshihiko; Ikeda, Shunya; Noda, Mitsuhiko; Nakayama, Takeo

2010-01-01

Health insurance claims (ie, receipts) record patient health care treatments and expenses and, although created for the health care payment system, are potentially useful for research. Combining different types of receipts generated for the same patient would dramatically increase the utility of these receipts. However, technical problems, including standardization of disease names and classifications, and anonymous linkage of individual receipts, must be addressed. In collaboration with health insurance societies, all information from receipts (inpatient, outpatient, and pharmacy) was collected. To standardize disease names and classifications, we developed a computer-aided post-entry standardization method using a disease name dictionary based on International Classification of Diseases (ICD)-10 classifications. We also developed an anonymous linkage system by using an encryption code generated from a combination of hash values and stream ciphers. Using different sets of the original data (data set 1: insurance certificate number, name, and sex; data set 2: insurance certificate number, date of birth, and relationship status), we compared the percentage of successful record matches obtained by using data set 1 to generate key codes with the percentage obtained when both data sets were used. The dictionary's automatic conversion of disease names successfully standardized 98.1% of approximately 2 million new receipts entered into the database. The percentage of anonymous matches was higher for the combined data sets (98.0%) than for data set 1 (88.5%). The use of standardized disease classifications and anonymous record linkage substantially contributed to the construction of a large, chronologically organized database of receipts. This database is expected to aid in epidemiologic and health services research using receipt information.

[Mucosal Schwann cells hamartoma: Review of a recently described entity].

PubMed

García-Molina, Francisco; Ruíz-Macia, José Antonio; Sola, Joaquin

Neural lesions of the colon may be masses (schwannomas and neurofibromas) or, more frequently, small polyps including perineuromas, ganglioneuromas and granular cell tumors. Some neural lesions are associated with congenital syndromes (neurofibromatosis-1, multiple endocrine neoplasia-2B). Recently, a new entity has been described named mucosal Schwann cell hamartoma, consisting of an intramucosal neural proliferation; to date, less than forty cases have been reported. We report a further case in a patient from whom a polyp was extirpated during colonoscopy screening. Histologically, the polyp showed a lamina propia that contained spindle-shaped cells of neural aspect which could only be identified after a histochemical and immunohistochemical study. Copyright © 2017 Sociedad Española de Anatomía Patológica. Publicado por Elsevier España, S.L.U. All rights reserved.

Gas Classification Using Deep Convolutional Neural Networks.

PubMed

Peng, Pai; Zhao, Xiaojin; Pan, Xiaofang; Ye, Wenbin

2018-01-08

In this work, we propose a novel Deep Convolutional Neural Network (DCNN) tailored for gas classification. Inspired by the great success of DCNN in the field of computer vision, we designed a DCNN with up to 38 layers. In general, the proposed gas neural network, named GasNet, consists of: six convolutional blocks, each block consist of six layers; a pooling layer; and a fully-connected layer. Together, these various layers make up a powerful deep model for gas classification. Experimental results show that the proposed DCNN method is an effective technique for classifying electronic nose data. We also demonstrate that the DCNN method can provide higher classification accuracy than comparable Support Vector Machine (SVM) methods and Multiple Layer Perceptron (MLP).

Gas Classification Using Deep Convolutional Neural Networks

PubMed Central

Peng, Pai; Zhao, Xiaojin; Pan, Xiaofang; Ye, Wenbin

2018-01-01

In this work, we propose a novel Deep Convolutional Neural Network (DCNN) tailored for gas classification. Inspired by the great success of DCNN in the field of computer vision, we designed a DCNN with up to 38 layers. In general, the proposed gas neural network, named GasNet, consists of: six convolutional blocks, each block consist of six layers; a pooling layer; and a fully-connected layer. Together, these various layers make up a powerful deep model for gas classification. Experimental results show that the proposed DCNN method is an effective technique for classifying electronic nose data. We also demonstrate that the DCNN method can provide higher classification accuracy than comparable Support Vector Machine (SVM) methods and Multiple Layer Perceptron (MLP). PMID:29316723

Identification and classification of similar looking food grains

NASA Astrophysics Data System (ADS)

Anami, B. S.; Biradar, Sunanda D.; Savakar, D. G.; Kulkarni, P. V.

2013-01-01

This paper describes the comparative study of Artificial Neural Network (ANN) and Support Vector Machine (SVM) classifiers by taking a case study of identification and classification of four pairs of similar looking food grains namely, Finger Millet, Mustard, Soyabean, Pigeon Pea, Aniseed, Cumin-seeds, Split Greengram and Split Blackgram. Algorithms are developed to acquire and process color images of these grains samples. The developed algorithms are used to extract 18 colors-Hue Saturation Value (HSV), and 42 wavelet based texture features. Back Propagation Neural Network (BPNN)-based classifier is designed using three feature sets namely color - HSV, wavelet-texture and their combined model. SVM model for color- HSV model is designed for the same set of samples. The classification accuracies ranging from 93% to 96% for color-HSV, ranging from 78% to 94% for wavelet texture model and from 92% to 97% for combined model are obtained for ANN based models. The classification accuracy ranging from 80% to 90% is obtained for color-HSV based SVM model. Training time required for the SVM based model is substantially lesser than ANN for the same set of images.

78 FR 3317 - Removal of Persons From the Entity List Based on Removal Request; Implementation of Entity List...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-01-16

... the Entity List. The ERC's decision to remove these two persons took into account their cooperation... INFORMATION CONTACT: Karen Nies-Vogel, Chair, End-User Review Committee, Office of the Assistant Secretary..., Fax: (202) 482-3911, Email: [email protected] . SUPPLEMENTARY INFORMATION: Background The Entity List...

The INNs and outs of antibody nonproprietary names

PubMed Central

Jones, Tim D.; Carter, Paul J.; Plückthun, Andreas; Vásquez, Max; Holgate, Robert G.E.; Hötzel, Isidro; Popplewell, Andrew G.; Parren, Paul W.H.I.; Enzelberger, Markus; Rademaker, Hendrik J.; Clark, Michael R.; Lowe, David C.; Dahiyat, Bassil I.; Smith, Victoria; Lambert, John M.; Wu, Herren; Reilly, Mary; Haurum, John S.; Dübel, Stefan; Huston, James S.; Schirrmann, Thomas; Janssen, Richard A.J.; Steegmaier, Martin; Gross, Jane A.; Bradbury, Andrew R.M.; Burton, Dennis R.; Dimitrov, Dimiter S.; Chester, Kerry A.; Glennie, Martin J.; Davies, Julian; Walker, Adam; Martin, Steve; McCafferty, John; Baker, Matthew P.

2016-01-01

An important step in drug development is the assignment of an International Nonproprietary Name (INN) by the World Health Organization (WHO) that provides healthcare professionals with a unique and universally available designated name to identify each pharmaceutical substance. Monoclonal antibody INNs comprise a –mab suffix preceded by a substem indicating the antibody type, e.g., chimeric (-xi-), humanized (-zu-), or human (-u-). The WHO publishes INN definitions that specify how new monoclonal antibody therapeutics are categorized and adapts the definitions to new technologies. However, rapid progress in antibody technologies has blurred the boundaries between existing antibody categories and created a burgeoning array of new antibody formats. Thus, revising the INN system for antibodies is akin to aiming for a rapidly moving target. The WHO recently revised INN definitions for antibodies now to be based on amino acid sequence identity. These new definitions, however, are critically flawed as they are ambiguous and go against decades of scientific literature. A key concern is the imposition of an arbitrary threshold for identity against human germline antibody variable region sequences. This leads to inconsistent classification of somatically mutated human antibodies, humanized antibodies as well as antibodies derived from semi-synthetic/synthetic libraries and transgenic animals. Such sequence-based classification implies clear functional distinction between categories (e.g., immunogenicity). However, there is no scientific evidence to support this. Dialog between the WHO INN Expert Group and key stakeholders is needed to develop a new INN system for antibodies and to avoid confusion and miscommunication between researchers and clinicians prescribing antibodies. PMID:26716992

Chemical entity recognition in patents by combining dictionary-based and statistical approaches.

PubMed

Akhondi, Saber A; Pons, Ewoud; Afzal, Zubair; van Haagen, Herman; Becker, Benedikt F H; Hettne, Kristina M; van Mulligen, Erik M; Kors, Jan A

2016-01-01

We describe the development of a chemical entity recognition system and its application in the CHEMDNER-patent track of BioCreative 2015. This community challenge includes a Chemical Entity Mention in Patents (CEMP) recognition task and a Chemical Passage Detection (CPD) classification task. We addressed both tasks by an ensemble system that combines a dictionary-based approach with a statistical one. For this purpose the performance of several lexical resources was assessed using Peregrine, our open-source indexing engine. We combined our dictionary-based results on the patent corpus with the results of tmChem, a chemical recognizer using a conditional random field classifier. To improve the performance of tmChem, we utilized three additional features, viz. part-of-speech tags, lemmas and word-vector clusters. When evaluated on the training data, our final system obtained an F-score of 85.21% for the CEMP task, and an accuracy of 91.53% for the CPD task. On the test set, the best system ranked sixth among 21 teams for CEMP with an F-score of 86.82%, and second among nine teams for CPD with an accuracy of 94.23%. The differences in performance between the best ensemble system and the statistical system separately were small.Database URL: http://biosemantics.org/chemdner-patents. © The Author(s) 2016. Published by Oxford University Press.

[WHO classification of head and neck tumours 2017: Main novelties and update of diagnostic methods].

PubMed

Sarradin, Victor; Siegfried, Aurore; Uro-Coste, Emmanuelle; Delord, Jean-Pierre

2018-06-01

The publication of the new WHO classification of head and neck tumours in 2017 brought major modifications. Especially, a new chapter is dedicated to the oropharynx, focusing on the description of squamous cell carcinoma induced by the virus Human Papilloma Virus (HPV), and new entities of tumors are described in nasal cavities and sinuses. In this article are presented the novelties and main changes of this new classification, as well as the updates of the diagnostic methods (immunohistochemistry, cytogenetics or molecular biology). Copyright © 2018 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

DNA methylation-based classification of central nervous system tumours.

PubMed

Capper, David; Jones, David T W; Sill, Martin; Hovestadt, Volker; Schrimpf, Daniel; Sturm, Dominik; Koelsche, Christian; Sahm, Felix; Chavez, Lukas; Reuss, David E; Kratz, Annekathrin; Wefers, Annika K; Huang, Kristin; Pajtler, Kristian W; Schweizer, Leonille; Stichel, Damian; Olar, Adriana; Engel, Nils W; Lindenberg, Kerstin; Harter, Patrick N; Braczynski, Anne K; Plate, Karl H; Dohmen, Hildegard; Garvalov, Boyan K; Coras, Roland; Hölsken, Annett; Hewer, Ekkehard; Bewerunge-Hudler, Melanie; Schick, Matthias; Fischer, Roger; Beschorner, Rudi; Schittenhelm, Jens; Staszewski, Ori; Wani, Khalida; Varlet, Pascale; Pages, Melanie; Temming, Petra; Lohmann, Dietmar; Selt, Florian; Witt, Hendrik; Milde, Till; Witt, Olaf; Aronica, Eleonora; Giangaspero, Felice; Rushing, Elisabeth; Scheurlen, Wolfram; Geisenberger, Christoph; Rodriguez, Fausto J; Becker, Albert; Preusser, Matthias; Haberler, Christine; Bjerkvig, Rolf; Cryan, Jane; Farrell, Michael; Deckert, Martina; Hench, Jürgen; Frank, Stephan; Serrano, Jonathan; Kannan, Kasthuri; Tsirigos, Aristotelis; Brück, Wolfgang; Hofer, Silvia; Brehmer, Stefanie; Seiz-Rosenhagen, Marcel; Hänggi, Daniel; Hans, Volkmar; Rozsnoki, Stephanie; Hansford, Jordan R; Kohlhof, Patricia; Kristensen, Bjarne W; Lechner, Matt; Lopes, Beatriz; Mawrin, Christian; Ketter, Ralf; Kulozik, Andreas; Khatib, Ziad; Heppner, Frank; Koch, Arend; Jouvet, Anne; Keohane, Catherine; Mühleisen, Helmut; Mueller, Wolf; Pohl, Ute; Prinz, Marco; Benner, Axel; Zapatka, Marc; Gottardo, Nicholas G; Driever, Pablo Hernáiz; Kramm, Christof M; Müller, Hermann L; Rutkowski, Stefan; von Hoff, Katja; Frühwald, Michael C; Gnekow, Astrid; Fleischhack, Gudrun; Tippelt, Stephan; Calaminus, Gabriele; Monoranu, Camelia-Maria; Perry, Arie; Jones, Chris; Jacques, Thomas S; Radlwimmer, Bernhard; Gessi, Marco; Pietsch, Torsten; Schramm, Johannes; Schackert, Gabriele; Westphal, Manfred; Reifenberger, Guido; Wesseling, Pieter; Weller, Michael; Collins, Vincent Peter; Blümcke, Ingmar; Bendszus, Martin; Debus, Jürgen; Huang, Annie; Jabado, Nada; Northcott, Paul A; Paulus, Werner; Gajjar, Amar; Robinson, Giles W; Taylor, Michael D; Jaunmuktane, Zane; Ryzhova, Marina; Platten, Michael; Unterberg, Andreas; Wick, Wolfgang; Karajannis, Matthias A; Mittelbronn, Michel; Acker, Till; Hartmann, Christian; Aldape, Kenneth; Schüller, Ulrich; Buslei, Rolf; Lichter, Peter; Kool, Marcel; Herold-Mende, Christel; Ellison, David W; Hasselblatt, Martin; Snuderl, Matija; Brandner, Sebastian; Korshunov, Andrey; von Deimling, Andreas; Pfister, Stefan M

2018-03-22

Accurate pathological diagnosis is crucial for optimal management of patients with cancer. For the approximately 100 known tumour types of the central nervous system, standardization of the diagnostic process has been shown to be particularly challenging-with substantial inter-observer variability in the histopathological diagnosis of many tumour types. Here we present a comprehensive approach for the DNA methylation-based classification of central nervous system tumours across all entities and age groups, and demonstrate its application in a routine diagnostic setting. We show that the availability of this method may have a substantial impact on diagnostic precision compared to standard methods, resulting in a change of diagnosis in up to 12% of prospective cases. For broader accessibility, we have designed a free online classifier tool, the use of which does not require any additional onsite data processing. Our results provide a blueprint for the generation of machine-learning-based tumour classifiers across other cancer entities, with the potential to fundamentally transform tumour pathology.

Symbolic emblems of the Levantine Aurignacians as a regional entity identifier (Hayonim Cave, Lower Galilee, Israel).

PubMed

Tejero, José-Miguel; Belfer-Cohen, Anna; Bar-Yosef, Ofer; Gutkin, Vitaly; Rabinovich, Rivka

2018-05-15

The Levantine Aurignacian is a unique phenomenon in the local Upper Paleolithic sequence, showing greater similarity to the West European classic Aurignacian than to the local Levantine archaeological entities preceding and following it. Herewith we highlight another unique characteristic of this entity, namely, the presence of symbolic objects in the form of notched bones (mostly gazelle scapulae) from the Aurignacian levels of Hayonim Cave, Lower Galilee, Israel. Through both macroscopic and microscopic analyses of the items, we suggest that they are not mere cut marks but rather are intentional (decorative?) human-made markings. The significance of this evidence for symbolic behavior is discussed in its chrono-cultural and geographical contexts. Notched bones are among the oldest symbolic expressions of anatomically modern humans. However, unlike other Paleolithic sites where such findings were reported in single numbers, the number of these items recovered at Hayonim Cave is sufficient to assume they possibly served as an emblem of the Levantine Aurignacian.

Proposal for a revised taxonomy of the family Filoviridae: classification, names of taxa and viruses, and virus abbreviations

PubMed Central

Kuhn, Jens H.; Becker, Stephan; Ebihara, Hideki; Geisbert, Thomas W.; Johnson, Karl M.; Kawaoka, Yoshihiro; Lipkin, W. Ian; Negredo, Ana I.; Netesov, Sergey V.; Nichol, Stuart T.; Palacios, Gustavo; Peters, Clarence J.; Tenorio, Antonio; Volchkov, Viktor E.; Jahrling, Peter B.

2011-01-01

The taxonomy of the family Filoviridae (marburgviruses and ebolaviruses) has changed several times since the discovery of its members, resulting in a plethora of species and virus names and abbreviations. The current taxonomy has only been partially accepted by most laboratory virologists. Confusion likely arose for several reasons: species names that consist of several words or which (should) contain diacritical marks, the current orthographic identity of species and virus names, and the similar pronunciation of several virus abbreviations in the absence of guidance for the correct use of vernacular names. To rectify this problem, we suggest (1) to retain the current species names Reston ebolavirus, Sudan ebolavirus, and Zaire ebolavirus, but to replace the name Cote d'Ivoire ebolavirus [sic] with Taï Forest ebolavirus and Lake Victoria marburgvirus with Marburg marburgvirus; (2) to revert the virus names of the type marburgviruses and ebolaviruses to those used for decades in the field (Marburg virus instead of Lake Victoria marburgvirus and Ebola virus instead of Zaire ebolavirus); (3) to introduce names for the remaining viruses reminiscent of jargon used by laboratory virologists but nevertheless different from species names (Reston virus, Sudan virus, Taï Forest virus), and (4) to introduce distinct abbreviations for the individual viruses (RESTV for Reston virus, SUDV for Sudan virus, and TAFV for Taï Forest virus), while retaining that for Marburg virus (MARV) and reintroducing that used over decades for Ebola virus (EBOV). Paying tribute to developments in the field, we propose (a) to create a new ebolavirus species (Bundibugyo ebolavirus) for one member virus (Bundibugyo virus, BDBV); (b) to assign a second virus to the species Marburg marburgvirus (Ravn virus, RAVV) for better reflection of now available high-resolution phylogeny; and (c) to create a new tentative genus (Cuevavirus) with one tentative species (Lloviu cuevavirus) for the recently

Proposal for a revised taxonomy of the family Filoviridae: classification, names of taxa and viruses, and virus abbreviations.

PubMed

Kuhn, Jens H; Becker, Stephan; Ebihara, Hideki; Geisbert, Thomas W; Johnson, Karl M; Kawaoka, Yoshihiro; Lipkin, W Ian; Negredo, Ana I; Netesov, Sergey V; Nichol, Stuart T; Palacios, Gustavo; Peters, Clarence J; Tenorio, Antonio; Volchkov, Viktor E; Jahrling, Peter B

2010-12-01

The taxonomy of the family Filoviridae (marburgviruses and ebolaviruses) has changed several times since the discovery of its members, resulting in a plethora of species and virus names and abbreviations. The current taxonomy has only been partially accepted by most laboratory virologists. Confusion likely arose for several reasons: species names that consist of several words or which (should) contain diacritical marks, the current orthographic identity of species and virus names, and the similar pronunciation of several virus abbreviations in the absence of guidance for the correct use of vernacular names. To rectify this problem, we suggest (1) to retain the current species names Reston ebolavirus, Sudan ebolavirus, and Zaire ebolavirus, but to replace the name Cote d'Ivoire ebolavirus [sic] with Taï Forest ebolavirus and Lake Victoria marburgvirus with Marburg marburgvirus; (2) to revert the virus names of the type marburgviruses and ebolaviruses to those used for decades in the field (Marburg virus instead of Lake Victoria marburgvirus and Ebola virus instead of Zaire ebolavirus); (3) to introduce names for the remaining viruses reminiscent of jargon used by laboratory virologists but nevertheless different from species names (Reston virus, Sudan virus, Taï Forest virus), and (4) to introduce distinct abbreviations for the individual viruses (RESTV for Reston virus, SUDV for Sudan virus, and TAFV for Taï Forest virus), while retaining that for Marburg virus (MARV) and reintroducing that used over decades for Ebola virus (EBOV). Paying tribute to developments in the field, we propose (a) to create a new ebolavirus species (Bundibugyo ebolavirus) for one member virus (Bundibugyo virus, BDBV); (b) to assign a second virus to the species Marburg marburgvirus (Ravn virus, RAVV) for better reflection of now available high-resolution phylogeny; and (c) to create a new tentative genus (Cuevavirus) with one tentative species (Lloviu cuevavirus) for the recently

12 CFR 1238.7 - Publication of results by regulated entities.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 12 Banks and Banking 10 2014-01-01 2014-01-01 false Publication of results by regulated entities... TESTING OF REGULATED ENTITIES § 1238.7 Publication of results by regulated entities. (a) Public disclosure of results required for stress tests of regulated entities. The Enterprises must disclose publicly a...

The 2015 WHO Classification of Tumors of the Thymus: Continuity and Changes

PubMed Central

Marx, Alexander; Chan, John K.C.; Coindre, Jean-Michel; Detterbeck, Frank; Girard, Nicolas; Harris, Nancy L.; Jaffe, Elaine S.; Kurrer, Michael O.; Marom, Edith M.; Moreira, Andre L.; Mukai, Kiyoshi; Orazi, Attilio; Ströbel, Philipp

2015-01-01

This overview of the 4th edition of the WHO Classification of thymic tumors has two aims. First, to comprehensively list the established and new tumour entities and variants that are described in the new WHO Classification of thymic epithelial tumors, germ cell tumors, lymphomas, dendritic cell and myeloid neoplasms, and soft tissue tumors of the thymus and mediastinum; second, to highlight major differences in the new WHO Classification that result from the progress that has been made since the 3rd edition in 2004 at immunohistochemical, genetic and conceptual levels. Refined diagnostic criteria for type A, AB, B1–B3 thymomas and thymic squamous cell carcinoma are given and will hopefully improve the reproducibility of the classification and its clinical relevance. The clinical perspective of the classification has been strengthened by involving experts from radiology, thoracic surgery and oncology; by incorporating state-of-the-art PET/CT images; and by depicting prototypic cytological specimens. This makes the thymus section of the new WHO Classification of Tumours of the Lung, Pleura, Thymus and Heart a valuable tool for pathologists, cytologists and clinicians alike. The impact of the new WHO Classification on therapeutic decisions is exemplified in this overview for thymic epithelial tumors and mediastinal lymphomas, and future perspectives and challenges are discussed. PMID:26295375

Exophytic oral verrucous hyperplasia: a new entity.

PubMed

Patil, Shankargouda; Warnakulasuriya, Saman; Raj, Thirumal; Sanketh, D S; Rao, Roopa S

2016-11-01

Exophytic oral verrucous hyperplasia (OVH) is a new entity described by an expert working group from South Asia. First reported in Taiwan, there are no reports so far from an Indian population. The aim was to use the microscopic features described by the expert group to differentiate OVH from other oral verruco-papillary lesions in an Indian archive. In a retrospective multicentre study, using pathology archives, 188 verruco-papillary lesions were retrieved from pathology archives. A proforma listing histopathological criteria for OVH based on published guidelines (Annals of Dentistry, University of Malaya, 2013) was used. Patients' demographic and clinical data were transcribed from patient charts. The Pearson chi-square test was used to determine associations between clinical and histopathological features. Of 188 oral verruco-papillary lesions that were evaluated, based on microscopic features the cases were reclassified as OVH (57), verrucous carcinoma (VC) (84), oral squamous cell carcinoma (16), and other verruco-papillary lesions (31). Both OVH (70%) and VC (60%) showed male predominance and commonly affected buccal mucosa (OVH 74% and VC 57%). Absence of downward growth of the hyperplastic epithelium into lamina propria when compared with the level of the basement membrane of the adjacent normal epithelium was a distinct feature in OVH. Keratin plugging, epithelial dysplasia and subepithelial lymphocytic infiltration were found to be significantly different (P < 0.05) in OVH versus VC. The sample size of other verruco-papillary lesions was insufficient for statistical comparison. Apart from the absence of an endophytic growth pattern in OVH, we noted the presence of dysplasia in OVH. This significant observation does institute a debate as to whether this enigmatic lesion could possibly be a precedent of oral squamous or verrucous carcinoma. We propose OVH is a distinct entity in our Indian population and should be considered in the classification of oral

37 CFR 381.2 - Definition of public broadcasting entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... broadcasting entity. 381.2 Section 381.2 Patents, Trademarks, and Copyrights COPYRIGHT ROYALTY BOARD, LIBRARY... WITH NONCOMMERCIAL EDUCATIONAL BROADCASTING § 381.2 Definition of public broadcasting entity. As used in this part, the term public broadcasting entity means a noncommercial educational broadcast station...

37 CFR 253.2 - Definition of public broadcasting entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... broadcasting entity. 253.2 Section 253.2 Patents, Trademarks, and Copyrights COPYRIGHT OFFICE, LIBRARY OF... CONNECTION WITH NONCOMMERCIAL EDUCATIONAL BROADCASTING § 253.2 Definition of public broadcasting entity. As used in this part, the term public broadcasting entity means a noncommercial educational broadcast...

37 CFR 381.2 - Definition of public broadcasting entity.

Code of Federal Regulations, 2011 CFR

2011-07-01

... broadcasting entity. 381.2 Section 381.2 Patents, Trademarks, and Copyrights COPYRIGHT ROYALTY BOARD, LIBRARY... WITH NONCOMMERCIAL EDUCATIONAL BROADCASTING § 381.2 Definition of public broadcasting entity. As used in this part, the term public broadcasting entity means a noncommercial educational broadcast station...

37 CFR 253.2 - Definition of public broadcasting entity.

Code of Federal Regulations, 2010 CFR

2010-07-01

... broadcasting entity. 253.2 Section 253.2 Patents, Trademarks, and Copyrights COPYRIGHT OFFICE, LIBRARY OF... CONNECTION WITH NONCOMMERCIAL EDUCATIONAL BROADCASTING § 253.2 Definition of public broadcasting entity. As used in this part, the term public broadcasting entity means a noncommercial educational broadcast...

Lauren classification and individualized chemotherapy in gastric cancer.

PubMed

Ma, Junli; Shen, Hong; Kapesa, Linda; Zeng, Shan

2016-05-01

Gastric cancer is one of the most common malignancies worldwide. During the last 50 years, the histological classification of gastric carcinoma has been largely based on Lauren's criteria, in which gastric cancer is classified into two major histological subtypes, namely intestinal type and diffuse type adenocarcinoma. This classification was introduced in 1965, and remains currently widely accepted and employed, since it constitutes a simple and robust classification approach. The two histological subtypes of gastric cancer proposed by the Lauren classification exhibit a number of distinct clinical and molecular characteristics, including histogenesis, cell differentiation, epidemiology, etiology, carcinogenesis, biological behaviors and prognosis. Gastric cancer exhibits varied sensitivity to chemotherapy drugs and significant heterogeneity; therefore, the disease may be a target for individualized therapy. The Lauren classification may provide the basis for individualized treatment for advanced gastric cancer, which is increasingly gaining attention in the scientific field. However, few studies have investigated individualized treatment that is guided by pathological classification. The aim of the current review is to analyze the two major histological subtypes of gastric cancer, as proposed by the Lauren classification, and to discuss the implications of this for personalized chemotherapy.

12 CFR 1238.6 - Post-assessment actions by regulated entities.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 12 Banks and Banking 10 2014-01-01 2014-01-01 false Post-assessment actions by regulated entities... TESTING OF REGULATED ENTITIES § 1238.6 Post-assessment actions by regulated entities. Each regulated entity shall take the results of the stress test conducted under § 1238.3 into account in making changes...

22 CFR 140.9 - Other non-governmental entities and individuals.

Code of Federal Regulations, 2014 CFR

2014-04-01

.... Section 140.9 applies to private voluntary agencies, educational institutions, for-profit firms, other non-governmental entities and private individuals. A non-governmental entity that is not organized under the laws... suspect that a proposed U.S. non-governmental entity or a key individual of such entity may be or may have...

22 CFR 140.9 - Other non-governmental entities and individuals.

Code of Federal Regulations, 2012 CFR

2012-04-01

.... Section 140.9 applies to private voluntary agencies, educational institutions, for-profit firms, other non-governmental entities and private individuals. A non-governmental entity that is not organized under the laws... suspect that a proposed U.S. non-governmental entity or a key individual of such entity may be or may have...

22 CFR 140.9 - Other non-governmental entities and individuals.

Code of Federal Regulations, 2013 CFR

2013-04-01

.... Section 140.9 applies to private voluntary agencies, educational institutions, for-profit firms, other non-governmental entities and private individuals. A non-governmental entity that is not organized under the laws... suspect that a proposed U.S. non-governmental entity or a key individual of such entity may be or may have...

18 CFR 39.8 - Delegation to a Regional Entity.

Code of Federal Regulations, 2011 CFR

2011-04-01

... Regional Entity. 39.8 Section 39.8 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY... OF ELECTRIC RELIABILITY STANDARDS § 39.8 Delegation to a Regional Entity. (a) The Electric Reliability Organization may enter into an agreement to delegate authority to a Regional Entity for the...

49 CFR 37.29 - Private entities providing taxi service.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 1 2010-10-01 2010-10-01 false Private entities providing taxi service. 37.29... INDIVIDUALS WITH DISABILITIES (ADA) Applicability § 37.29 Private entities providing taxi service. (a) Providers of taxi service are subject to the requirements of this part for private entities primarily...

45 CFR 162.510 - Full implementation requirements: Covered entities.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 45 Public Welfare 1 2013-10-01 2013-10-01 false Full implementation requirements: Covered entities. 162.510 Section 162.510 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES ADMINISTRATIVE DATA... Plans § 162.510 Full implementation requirements: Covered entities. (a) A covered entity must use an...

7 CFR 25.401 - Responsibility of lead managing entity.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 1 2013-01-01 2013-01-01 false Responsibility of lead managing entity. 25.401 Section... COMMUNITIES Post-Designation Requirements § 25.401 Responsibility of lead managing entity. (a) Financial. The lead managing entity will be responsible for strategic plan program activities and monitoring the...

7 CFR 25.401 - Responsibility of lead managing entity.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 1 2012-01-01 2012-01-01 false Responsibility of lead managing entity. 25.401 Section... COMMUNITIES Post-Designation Requirements § 25.401 Responsibility of lead managing entity. (a) Financial. The lead managing entity will be responsible for strategic plan program activities and monitoring the...

7 CFR 25.401 - Responsibility of lead managing entity.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 1 2014-01-01 2014-01-01 false Responsibility of lead managing entity. 25.401 Section... COMMUNITIES Post-Designation Requirements § 25.401 Responsibility of lead managing entity. (a) Financial. The lead managing entity will be responsible for strategic plan program activities and monitoring the...

49 CFR 37.29 - Private entities providing taxi service.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 1 2011-10-01 2011-10-01 false Private entities providing taxi service. 37.29... INDIVIDUALS WITH DISABILITIES (ADA) Applicability § 37.29 Private entities providing taxi service. (a) Providers of taxi service are subject to the requirements of this part for private entities primarily...

Anatomical entity mention recognition at literature scale

PubMed Central

Pyysalo, Sampo; Ananiadou, Sophia

2014-01-01

Motivation: Anatomical entities ranging from subcellular structures to organ systems are central to biomedical science, and mentions of these entities are essential to understanding the scientific literature. Despite extensive efforts to automatically analyze various aspects of biomedical text, there have been only few studies focusing on anatomical entities, and no dedicated methods for learning to automatically recognize anatomical entity mentions in free-form text have been introduced. Results: We present AnatomyTagger, a machine learning-based system for anatomical entity mention recognition. The system incorporates a broad array of approaches proposed to benefit tagging, including the use of Unified Medical Language System (UMLS)- and Open Biomedical Ontologies (OBO)-based lexical resources, word representations induced from unlabeled text, statistical truecasing and non-local features. We train and evaluate the system on a newly introduced corpus that substantially extends on previously available resources, and apply the resulting tagger to automatically annotate the entire open access scientific domain literature. The resulting analyses have been applied to extend services provided by the Europe PubMed Central literature database. Availability and implementation: All tools and resources introduced in this work are available from http://nactem.ac.uk/anatomytagger. Contact: sophia.ananiadou@manchester.ac.uk Supplementary Information: Supplementary data are available at Bioinformatics online. PMID:24162468

7 CFR 1486.202 - Are there any ineligible entities?

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 10 2010-01-01 2010-01-01 false Are there any ineligible entities? 1486.202 Section... Eligibility, Applications, and Funding § 1486.202 Are there any ineligible entities? Foreign organizations, whether government or private, may participate as third parties in activities carried out by U.S. entities...

45 CFR 162.610 - Implementation specifications for covered entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 45 Public Welfare 1 2011-10-01 2011-10-01 false Implementation specifications for covered entities... Implementation specifications for covered entities. (a) The standard unique employer identifier of an employer of... Statement, from the employer. (b) A covered entity must use the standard unique employer identifier (EIN) of...

7 CFR 760.115 - Deceased individuals or dissolved entities.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 7 2010-01-01 2010-01-01 false Deceased individuals or dissolved entities. 760.115... Agricultural Disaster Assistance Programs § 760.115 Deceased individuals or dissolved entities. (a) Payments... or is a dissolved entity if a representative, who currently has authority to enter into a contract...

7 CFR 1486.202 - Are there any ineligible entities?

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 10 2011-01-01 2011-01-01 false Are there any ineligible entities? 1486.202 Section... Eligibility, Applications, and Funding § 1486.202 Are there any ineligible entities? Foreign organizations, whether government or private, may participate as third parties in activities carried out by U.S. entities...

45 CFR 162.610 - Implementation specifications for covered entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 45 Public Welfare 1 2010-10-01 2010-10-01 false Implementation specifications for covered entities... Implementation specifications for covered entities. (a) The standard unique employer identifier of an employer of... Statement, from the employer. (b) A covered entity must use the standard unique employer identifier (EIN) of...

42 CFR 422.592 - Reconsideration by an independent entity.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 3 2011-10-01 2011-10-01 false Reconsideration by an independent entity. 422.592... and Appeals § 422.592 Reconsideration by an independent entity. (a) When the MA organization affirms... be reviewed and resolved by an independent, outside entity that contracts with CMS. (b) The...

42 CFR 422.592 - Reconsideration by an independent entity.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 3 2010-10-01 2010-10-01 false Reconsideration by an independent entity. 422.592... and Appeals § 422.592 Reconsideration by an independent entity. (a) When the MA organization affirms... be reviewed and resolved by an independent, outside entity that contracts with CMS. (b) The...

7 CFR 760.115 - Deceased individuals or dissolved entities.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 7 2012-01-01 2012-01-01 false Deceased individuals or dissolved entities. 760.115... Agricultural Disaster Assistance Programs § 760.115 Deceased individuals or dissolved entities. (a) Payments... or is a dissolved entity if a representative, who currently has authority to enter into a contract...

7 CFR 760.115 - Deceased individuals or dissolved entities.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 7 2013-01-01 2013-01-01 false Deceased individuals or dissolved entities. 760.115... Agricultural Disaster Assistance Programs § 760.115 Deceased individuals or dissolved entities. (a) Payments... or is a dissolved entity if a representative, who currently has authority to enter into a contract...

7 CFR 760.115 - Deceased individuals or dissolved entities.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 7 2014-01-01 2014-01-01 false Deceased individuals or dissolved entities. 760.115... Agricultural Disaster Assistance Programs § 760.115 Deceased individuals or dissolved entities. (a) Payments... or is a dissolved entity if a representative, who currently has authority to enter into a contract...

7 CFR 760.115 - Deceased individuals or dissolved entities.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 7 2011-01-01 2011-01-01 false Deceased individuals or dissolved entities. 760.115... Agricultural Disaster Assistance Programs § 760.115 Deceased individuals or dissolved entities. (a) Payments... or is a dissolved entity if a representative, who currently has authority to enter into a contract...

42 CFR 410.145 - Requirements for entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... PROGRAM SUPPLEMENTARY MEDICAL INSURANCE (SMI) BENEFITS Outpatient Diabetes Self-Management Training and... documentation and is fully accredited (and periodically reaccredited) by an organization approved by CMS under § 410.142. (ii) The entity is not accredited by an organization that owns or controls the entity. (2...

42 CFR 410.145 - Requirements for entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... PROGRAM SUPPLEMENTARY MEDICAL INSURANCE (SMI) BENEFITS Outpatient Diabetes Self-Management Training and... documentation and is fully accredited (and periodically reaccredited) by an organization approved by CMS under § 410.142. (ii) The entity is not accredited by an organization that owns or controls the entity. (2...

Entity- Version 1.0

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

Hart, Brian; Oppel, Fred; Rigdon, Brian

2012-09-13

This package contains classes that capture high-level aspects of characters and vehicles. Vehicles manage seats and riders. Vehicles and characters now can be configured to compose different behaviors and have certain capabilities, by adding them through xml data. These behaviors and capabilities are not included in this package, but instead are part of other packages such as mobility behavior, path planning, sight, sound. Entity is not dependent on these other packages. This package also contains the icons used for Umbra applications Dante Scenario Editor, Dante Tabletop and OpShed. This assertion includes a managed C++ wrapper code (EntityWrapper) to enable C#more » applications, such as Dante Scenario Editor, Dante Tabletop, and OpShed, to incorporate this library.« less

Classification Algorithms for Big Data Analysis, a Map Reduce Approach

NASA Astrophysics Data System (ADS)

Ayma, V. A.; Ferreira, R. S.; Happ, P.; Oliveira, D.; Feitosa, R.; Costa, G.; Plaza, A.; Gamba, P.

2015-03-01

Since many years ago, the scientific community is concerned about how to increase the accuracy of different classification methods, and major achievements have been made so far. Besides this issue, the increasing amount of data that is being generated every day by remote sensors raises more challenges to be overcome. In this work, a tool within the scope of InterIMAGE Cloud Platform (ICP), which is an open-source, distributed framework for automatic image interpretation, is presented. The tool, named ICP: Data Mining Package, is able to perform supervised classification procedures on huge amounts of data, usually referred as big data, on a distributed infrastructure using Hadoop MapReduce. The tool has four classification algorithms implemented, taken from WEKA's machine learning library, namely: Decision Trees, Naïve Bayes, Random Forest and Support Vector Machines (SVM). The results of an experimental analysis using a SVM classifier on data sets of different sizes for different cluster configurations demonstrates the potential of the tool, as well as aspects that affect its performance.

12 CFR 607.4 - Assessment of other System entities.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 12 Banks and Banking 6 2011-01-01 2011-01-01 false Assessment of other System entities. 607.4... APPORTIONMENT OF ADMINISTRATIVE EXPENSES § 607.4 Assessment of other System entities. (a)(1) Unless otherwise... section, other System entities will be assessed for estimated direct expenses plus an allocated portion of...

12 CFR 607.4 - Assessment of other System entities.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Assessment of other System entities. 607.4... APPORTIONMENT OF ADMINISTRATIVE EXPENSES § 607.4 Assessment of other System entities. (a)(1) Unless otherwise... section, other System entities will be assessed for estimated direct expenses plus an allocated portion of...

7 CFR 760.908 - Deceased individuals or dissolved entities.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 7 2010-01-01 2010-01-01 false Deceased individuals or dissolved entities. 760.908... § 760.908 Deceased individuals or dissolved entities. (a) Payments may be made for eligible losses suffered by an eligible participant who is now a deceased individual or is a dissolved entity if a...

7 CFR 1413.113 - Deceased individuals or dissolved entities.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 10 2011-01-01 2011-01-01 false Deceased individuals or dissolved entities. 1413.113... PROGRAMS Durum Wheat Quality Program § 1413.113 Deceased individuals or dissolved entities. (a) Payment may... individual or is a dissolved entity if a representative who currently has authority to enter into a contract...

7 CFR 760.908 - Deceased individuals or dissolved entities.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 7 2013-01-01 2013-01-01 false Deceased individuals or dissolved entities. 760.908... § 760.908 Deceased individuals or dissolved entities. (a) Payments may be made for eligible losses suffered by an eligible participant who is now a deceased individual or is a dissolved entity if a...

7 CFR 1413.113 - Deceased individuals or dissolved entities.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 10 2012-01-01 2012-01-01 false Deceased individuals or dissolved entities. 1413.113... PROGRAMS Durum Wheat Quality Program § 1413.113 Deceased individuals or dissolved entities. (a) Payment may... individual or is a dissolved entity if a representative who currently has authority to enter into a contract...

7 CFR 760.908 - Deceased individuals or dissolved entities.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 7 2012-01-01 2012-01-01 false Deceased individuals or dissolved entities. 760.908... § 760.908 Deceased individuals or dissolved entities. (a) Payments may be made for eligible losses suffered by an eligible participant who is now a deceased individual or is a dissolved entity if a...

7 CFR 1413.113 - Deceased individuals or dissolved entities.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 10 2013-01-01 2013-01-01 false Deceased individuals or dissolved entities. 1413.113... PROGRAMS Durum Wheat Quality Program § 1413.113 Deceased individuals or dissolved entities. (a) Payment may... individual or is a dissolved entity if a representative who currently has authority to enter into a contract...

7 CFR 760.908 - Deceased individuals or dissolved entities.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 7 2014-01-01 2014-01-01 false Deceased individuals or dissolved entities. 760.908... § 760.908 Deceased individuals or dissolved entities. (a) Payments may be made for eligible losses suffered by an eligible participant who is now a deceased individual or is a dissolved entity if a...

7 CFR 1413.113 - Deceased individuals or dissolved entities.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 10 2014-01-01 2014-01-01 false Deceased individuals or dissolved entities. 1413.113... PROGRAMS Durum Wheat Quality Program § 1413.113 Deceased individuals or dissolved entities. (a) Payment may... individual or is a dissolved entity if a representative who currently has authority to enter into a contract...

7 CFR 760.908 - Deceased individuals or dissolved entities.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 7 2011-01-01 2011-01-01 false Deceased individuals or dissolved entities. 760.908... § 760.908 Deceased individuals or dissolved entities. (a) Payments may be made for eligible losses suffered by an eligible participant who is now a deceased individual or is a dissolved entity if a...

42 CFR 410.144 - Quality standards for deemed entities.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 42 Public Health 2 2013-10-01 2013-10-01 false Quality standards for deemed entities. 410.144...-Management Training and Diabetes Outcome Measurements § 410.144 Quality standards for deemed entities. An organization approved and recognized by CMS may accredit an entity to meet one of the following sets of quality...

42 CFR 410.144 - Quality standards for deemed entities.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 42 Public Health 2 2012-10-01 2012-10-01 false Quality standards for deemed entities. 410.144...-Management Training and Diabetes Outcome Measurements § 410.144 Quality standards for deemed entities. An organization approved and recognized by CMS may accredit an entity to meet one of the following sets of quality...

42 CFR 410.144 - Quality standards for deemed entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false Quality standards for deemed entities. 410.144...-Management Training and Diabetes Outcome Measurements § 410.144 Quality standards for deemed entities. An organization approved and recognized by CMS may accredit an entity to meet one of the following sets of quality...

42 CFR 410.144 - Quality standards for deemed entities.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 42 Public Health 2 2014-10-01 2014-10-01 false Quality standards for deemed entities. 410.144...-Management Training and Diabetes Outcome Measurements § 410.144 Quality standards for deemed entities. An organization approved and recognized by CMS may accredit an entity to meet one of the following sets of quality...

42 CFR 410.144 - Quality standards for deemed entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false Quality standards for deemed entities. 410.144...-Management Training and Diabetes Outcome Measurements § 410.144 Quality standards for deemed entities. An organization approved and recognized by CMS may accredit an entity to meet one of the following sets of quality...

42 CFR 6.5 - Deeming process for eligible entities.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 1 2010-10-01 2010-10-01 false Deeming process for eligible entities. 6.5 Section 6.5 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PROVISIONS... entities. Eligible entities will be covered by this part only on and after the effective date of a...

42 CFR 6.5 - Deeming process for eligible entities.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 1 2011-10-01 2011-10-01 false Deeming process for eligible entities. 6.5 Section 6.5 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL PROVISIONS... entities. Eligible entities will be covered by this part only on and after the effective date of a...

7 CFR 1415.18 - Easement transfer to eligible entities.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 10 2011-01-01 2011-01-01 false Easement transfer to eligible entities. 1415.18... § 1415.18 Easement transfer to eligible entities. (a) NRCS may transfer title of ownership to an easement to an eligible entity to hold and enforce an easement if: (1) The Chief determines that transfer will...

Classification of lymphoid neoplasms: the microscope as a tool for disease discovery

PubMed Central

Harris, Nancy Lee; Stein, Harald; Isaacson, Peter G.

2008-01-01

In the past 50 years, we have witnessed explosive growth in the understanding of normal and neoplastic lymphoid cells. B-cell, T-cell, and natural killer (NK)–cell neoplasms in many respects recapitulate normal stages of lymphoid cell differentiation and function, so that they can be to some extent classified according to the corresponding normal stage. Likewise, the molecular mechanisms involved the pathogenesis of lymphomas and lymphoid leukemias are often based on the physiology of the lymphoid cells, capitalizing on deregulated normal physiology by harnessing the promoters of genes essential for lymphocyte function. The clinical manifestations of lymphomas likewise reflect the normal function of lymphoid cells in vivo. The multiparameter approach to classification adopted by the World Health Organization (WHO) classification has been validated in international studies as being highly reproducible, and enhancing the interpretation of clinical and translational studies. In addition, accurate and precise classification of disease entities facilitates the discovery of the molecular basis of lymphoid neoplasms in the basic science laboratory. PMID:19029456

The DTW-based representation space for seismic pattern classification

NASA Astrophysics Data System (ADS)

Orozco-Alzate, Mauricio; Castro-Cabrera, Paola Alexandra; Bicego, Manuele; Londoño-Bonilla, John Makario

2015-12-01

Distinguishing among the different seismic volcanic patterns is still one of the most important and labor-intensive tasks for volcano monitoring. This task could be lightened and made free from subjective bias by using automatic classification techniques. In this context, a core but often overlooked issue is the choice of an appropriate representation of the data to be classified. Recently, it has been suggested that using a relative representation (i.e. proximities, namely dissimilarities on pairs of objects) instead of an absolute one (i.e. features, namely measurements on single objects) is advantageous to exploit the relational information contained in the dissimilarities to derive highly discriminant vector spaces, where any classifier can be used. According to that motivation, this paper investigates the suitability of a dynamic time warping (DTW) dissimilarity-based vector representation for the classification of seismic patterns. Results show the usefulness of such a representation in the seismic pattern classification scenario, including analyses of potential benefits from recent advances in the dissimilarity-based paradigm such as the proper selection of representation sets and the combination of different dissimilarity representations that might be available for the same data.

22 CFR 140.6 - Foreign government entities.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 22 Foreign Relations 1 2013-04-01 2013-04-01 false Foreign government entities. 140.6 Section 140... Enforcement § 140.6 Foreign government entities. (a) Determination Procedures. (1) The Country Narcotics... allegations that a key individual who is a senior government official of the host nation has been convicted of...

22 CFR 140.6 - Foreign government entities.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 22 Foreign Relations 1 2012-04-01 2012-04-01 false Foreign government entities. 140.6 Section 140... Enforcement § 140.6 Foreign government entities. (a) Determination Procedures. (1) The Country Narcotics... allegations that a key individual who is a senior government official of the host nation has been convicted of...

22 CFR 140.6 - Foreign government entities.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 22 Foreign Relations 1 2011-04-01 2011-04-01 false Foreign government entities. 140.6 Section 140... Enforcement § 140.6 Foreign government entities. (a) Determination Procedures. (1) The Country Narcotics... allegations that a key individual who is a senior government official of the host nation has been convicted of...

14 CFR Sec. 1-6 - Accounting entities.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 4 2010-01-01 2010-01-01 false Accounting entities. Sec. 1-6 Section 1-6... REGULATIONS UNIFORM SYSTEM OF ACCOUNTS AND REPORTS FOR LARGE CERTIFICATED AIR CARRIERS General Accounting Provisions Sec. 1-6 Accounting entities. (a) Separate accounting records shall be maintained for each air...

7 CFR 795.6 - Multiple individuals or other entities.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 7 2010-01-01 2010-01-01 false Multiple individuals or other entities. 795.6 Section... Multiple individuals or other entities. The rules in §§ 795.5 through 795.16 shall be used to determine whether certain multiple individuals or legal entities are to be treated as one person or as separate...

Time to Redefine the Intramammary Lymph Node as a Separate Entity?

PubMed