AIMC Topic: Unified Medical Language System
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Enriching UMLS-Based Phenotyping of Rare Diseases Using Deep-Learning: Evaluation on Jeune Syndrome.
Studies in health technology and informatics
May 25, 2022
The wide adoption of Electronic Health Records (EHR) in hospitals provides unique opportunities for high throughput phenotyping of patients. The phenotype extraction from narrative reports can be performed by using either dictionary-based or data-dri...
Evaluation of Domain-Specific Word Vectors for Biomedical Word Sense Disambiguation.
Studies in health technology and informatics
May 16, 2022
Among medical applications of natural language processing (NLP), word sense disambiguation (WSD) estimates alternative meanings from text around homonyms. Recently developed NLP methods include word vectors that combine easy computability with nuance...
Something New and Different: The Unified Medical Language System.
Studies in health technology and informatics
Feb 1, 2022
Donald A.B. Lindberg M.D. arrived at the U.S. National Library of Medicine in 1984 and quickly launched the Unified Medical Language System (UMLS) research and development project to help computer understand biomedical meaning and to enable retrieval...
Distantly supervised biomedical relation extraction using piecewise attentive convolutional neural network and reinforcement learning.
Journal of the American Medical Informatics Association : JAMIA
Nov 25, 2021
OBJECTIVE: There have been various methods to deal with the erroneous training data in distantly supervised relation extraction (RE), however, their performance is still far from satisfaction. We aimed to deal with the insufficient modeling problem o...
UMLS-based data augmentation for natural language processing of clinical research literature.
Journal of the American Medical Informatics Association : JAMIA
Mar 18, 2021
OBJECTIVE: The study sought to develop and evaluate a knowledge-based data augmentation method to improve the performance of deep learning models for biomedical natural language processing by overcoming training data scarcity.
Clinical concept normalization with a hybrid natural language processing system combining multilevel matching and machine learning ranking.
Journal of the American Medical Informatics Association : JAMIA
Oct 1, 2020
OBJECTIVE: Normalizing clinical mentions to concepts in standardized medical terminologies, in general, is challenging due to the complexity and variety of the terms in narrative medical records. In this article, we introduce our work on a clinical n...
The impact of learning Unified Medical Language System knowledge embeddings in relation extraction from biomedical texts.
Journal of the American Medical Informatics Association : JAMIA
Oct 1, 2020
OBJECTIVE: We explored how knowledge embeddings (KEs) learned from the Unified Medical Language System (UMLS) Metathesaurus impact the quality of relation extraction on 2 diverse sets of biomedical texts.
Use of word and graph embedding to measure semantic relatedness between Unified Medical Language System concepts.
Journal of the American Medical Informatics Association : JAMIA
Oct 1, 2020
OBJECTIVE: The study sought to explore the use of deep learning techniques to measure the semantic relatedness between Unified Medical Language System (UMLS) concepts.
The 2019 National Natural language processing (NLP) Clinical Challenges (n2c2)/Open Health NLP (OHNLP) shared task on clinical concept normalization for clinical records.
Journal of the American Medical Informatics Association : JAMIA
Oct 1, 2020
OBJECTIVE: The 2019 National Natural language processing (NLP) Clinical Challenges (n2c2)/Open Health NLP (OHNLP) shared task track 3, focused on medical concept normalization (MCN) in clinical records. This track aimed to assess the state of the art...
Assessing the enrichment of dietary supplement coverage in the Unified Medical Language System.
Journal of the American Medical Informatics Association : JAMIA
Oct 1, 2020
OBJECTIVE: We sought to assess the need for additional coverage of dietary supplements (DS) in the Unified Medical Language System (UMLS) by investigating (1) the overlap between the integrated DIetary Supplements Knowledge base (iDISK) DS ingredient...
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