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Unified Medical Language System

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Leveraging Semantic Type Dependencies for Clinical Named Entity Recognition.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Previous work on clinical relation extraction from free-text sentences leveraged information about semantic types from clinical knowledge bases as a part of entity representations. In this paper, we exploit additional evidence by also making use of ....

MedLexSp - a medical lexicon for Spanish medical natural language processing.

Journal of biomedical semantics
BACKGROUND: Medical lexicons enable the natural language processing (NLP) of health texts. Lexicons gather terms and concepts from thesauri and ontologies, and linguistic data for part-of-speech (PoS) tagging, lemmatization or natural language genera...

Combine Factual Medical Knowledge and Distributed Word Representation to Improve Clinical Named Entity Recognition.

AMIA ... Annual Symposium proceedings. AMIA Symposium
There has been an increasing interest in developing deep learning methods to recognize clinical concepts from narrative clinical text. Recently, several studies have reported that Recurrent Neural Networks (RNNs) outperformed traditional machine lear...

A Computable Phenotype for Acute Respiratory Distress Syndrome Using Natural Language Processing and Machine Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Acute Respiratory Distress Syndrome (ARDS) is a syndrome of respiratory failure that may be identified using text from radiology reports. The objective of this study was to determine whether natural language processing (NLP) with machine learning per...

Automatic Extraction and Post-coordination of Spatial Relations in Consumer Language.

AMIA ... Annual Symposium proceedings. AMIA Symposium
To incorporate ontological concepts in natural language processing (NLP) it is often necessary to combine simple concepts into complex concepts (post-coordination). This is especially true in consumer language, where a more limited vocabulary forces ...

A Study of Concept Extraction Across Different Types of Clinical Notes.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Our research investigates methods for creating effective concept extractors for specialty clinical notes. First, we present three new "specialty area" datasets consisting of Cardiology, Neurology, and Orthopedics clinical notes manually annotated wit...

COHeRE: Cross-Ontology Hierarchical Relation Examination for Ontology Quality Assurance.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Biomedical ontologies play a vital role in healthcare information management, data integration, and decision support. Ontology quality assurance (OQA) is an indispensable part of the ontology engineering cycle. Most existing OQA methods are based on ...

A multilingual gold-standard corpus for biomedical concept recognition: the Mantra GSC.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To create a multilingual gold-standard corpus for biomedical concept recognition.

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

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Analysis of narrative (text) data from electronic health records (EHRs) can improve population-scale phenotyping for clinical and genetic research. Currently, selection of text features for phenotyping algorithms is slow and laborious, req...

Identifying named entities from PubMed for enriching semantic categories.

BMC bioinformatics
BACKGROUND: Controlled vocabularies such as the Unified Medical Language System (UMLS) and Medical Subject Headings (MeSH) are widely used for biomedical natural language processing (NLP) tasks. However, the standard terminology in such collections s...