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Unified Medical Language System

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Explaining Contextualized Word Embeddings in Biomedical Research - A Qualitative Investigation.

Studies in health technology and informatics
Contextualized word embeddings proved to be highly successful quantitative representations of words that allow to efficiently solve various tasks such as clinical entity normalization in unstructured texts. In this paper, we investigate how the Sauss...

Bottom-Up Natural Language Processing Based Evaluation of the Fitness of UMLS as a Semantic Source for a Computer Interpretable Guidelines Ontology.

Studies in health technology and informatics
BACKGROUND: CIGs languages consist of approach specific concepts. More widely used concepts, such as those in UMLS are not typically used.

Comparison of MetaMap, cTAKES, SIFR, and ECMT to Annotate Breast Cancer Patient Summaries.

Studies in health technology and informatics
Most clinical texts including breast cancer patient summaries (BCPSs) are elaborated as narrative documents difficult to process by decision support systems. Annotators have been developed to extract the relevant content of such documents, e.g., Meta...

Adding an Attention Layer Improves the Performance of a Neural Network Architecture for Synonymy Prediction in the UMLS Metathesaurus.

Studies in health technology and informatics
BACKGROUND: Terminology integration at the scale of the UMLS Metathesaurus (i.e., over 200 source vocabularies) remains challenging despite recent advances in ontology alignment techniques based on neural networks.

Multilabel classification of medical concepts for patient clinical profile identification.

Artificial intelligence in medicine
BACKGROUND: The development of electronic health records has provided a large volume of unstructured biomedical information. Extracting patient characteristics from these data has become a major challenge, especially in languages other than English.

Clustering Nursing Sentences - Comparing Three Sentence Embedding Methods.

Studies in health technology and informatics
In health sciences, high-quality text embeddings may augment qualitative data analysis of large amounts of text by enabling, e.g., searching and clustering of health information. This study aimed to evaluate three different sentence-level embedding m...

Enriching UMLS-Based Phenotyping of Rare Diseases Using Deep-Learning: Evaluation on Jeune Syndrome.

Studies in health technology and informatics
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
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
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...

CODER: Knowledge-infused cross-lingual medical term embedding for term normalization.

Journal of biomedical informatics
OBJECTIVE: This paper aims to propose knowledge-aware embedding, a critical tool for medical term normalization.