AIMC Topic: Unified Medical Language System

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Boosting Social Determinants of Health Extraction with Semantic Knowledge Augmented Large Language Model.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Social determinants of health (SDoH) significantly impacts health outcomes and contributes to perpetuating health disparities across healthcare applications. However, automatic extraction of SDoH information from Electronic Health Records (EHRs) is c...

LeafAI: query generator for clinical cohort discovery rivaling a human programmer.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Identifying study-eligible patients within clinical databases is a critical step in clinical research. However, accurate query design typically requires extensive technical and biomedical expertise. We sought to create a system capable of ...

Two complementary AI approaches for predicting UMLS semantic group assignment: heuristic reasoning and deep learning.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Use heuristic, deep learning (DL), and hybrid AI methods to predict semantic group (SG) assignments for new UMLS Metathesaurus atoms, with target accuracy ≥95%.

Masked Language Modeling for Resource Constrained Biological Natural Language Processing.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Recent advances in Natural Language Processing (NLP) have produced state of the art results on several sequence to sequence (seq2seq) tasks. Enhancements in embedders and their training methodologies have shown significant improvement on downstream t...

Digital Health Data Capture with a Controlled Natural Language.

Studies in health technology and informatics
Written text has been the preferred medium for storing health data ever since Hippocrates, and the medical narrative is what enables a humanized clinical relationship. Can't we admit natural language as a user-accepted technology that has stood again...

Classifiers of Medical Eponymy in Scientific Texts.

Studies in health technology and informatics
Many concepts in the medical literature are named after persons. Frequent ambiguities and spelling varieties, however, complicate the automatic recognition of such eponyms with natural language processing (NLP) tools. Recently developed methods inclu...

A survey of automated methods for biomedical text simplification.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Plain language in medicine has long been advocated as a way to improve patient understanding and engagement. As the field of Natural Language Processing has progressed, increasingly sophisticated methods have been explored for the automati...

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...