AIMC Topic: Unified Medical Language System
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Two complementary AI approaches for predicting UMLS semantic group assignment: heuristic reasoning and deep learning.
Journal of the American Medical Informatics Association : JAMIA
Nov 17, 2023
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
Jul 1, 2023
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
May 18, 2023
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
May 18, 2023
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
Oct 7, 2022
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
Jun 29, 2022
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
Jun 6, 2022
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
Jun 6, 2022
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
Jun 6, 2022
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.
Clustering Nursing Sentences - Comparing Three Sentence Embedding Methods.
Studies in health technology and informatics
May 25, 2022
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...
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