AIMC Topic: PubMed

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Text mining for case report articles on "peritoneal dialysis" from PubMed database.

Therapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy
INTRODUCTION: The number of published medical articles on peritoneal dialysis (PD) has been increasing, and efficiently selecting information from numerous articles can be difficult. In this study, we examined whether artificial intelligence (AI) tex...

Predicting drug-gene relations via analogy tasks with word embeddings.

Scientific reports
Natural language processing is utilized in a wide range of fields, where words in text are typically transformed into feature vectors called embeddings. BioConceptVec is a specific example of embeddings tailored for biology, trained on approximately ...

Utility of word embeddings from large language models in medical diagnosis.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: This study evaluates the utility of word embeddings, generated by large language models (LLMs), for medical diagnosis by comparing the semantic proximity of symptoms to their eponymic disease embedding ("eponymic condition") and the mean o...

Representation of Social Determinants of Health terminology in medical subject headings: impact of added terms.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: To enhance and evaluate the quality of PubMed search results for Social Determinants of Health (SDoH) through the addition of new SDoH terms to Medical Subject Headings (MeSH).

Trends of "Artificial Intelligence, Machine Learning, Virtual Reality, and Radiomics in Urolithiasis" over the Last 30 Years (1994-2023) as Published in the Literature (PubMed): A Comprehensive Review.

Journal of endourology
To analyze the bibliometric publication trend on the application of "Artificial Intelligence (AI) and its subsets (Machine Learning-ML, Virtual reality-VR, Radiomics) in Urolithiasis" over 3 decades. We looked at the publication trends associated wi...

Extracting Drug-Protein Relation from Literature Using Ensembles of Biomedical Transformers.

Studies in health technology and informatics
Automatic extraction of relations between drugs/chemicals and proteins from ever-growing biomedical literature is required to build up-to-date knowledge bases in biomedicine. To promote the development of automated methods, BioCreative-VII organized ...

Publication Type Tagging using Transformer Models and Multi-Label Classification.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Indexing articles by their publication type and study design is essential for efficient search and filtering of the biomedical literature, but is understudied compared to indexing by MeSH topical terms. In this study, we leveraged the human-curated p...

Clinfo.ai: An Open-Source Retrieval-Augmented Large Language Model System for Answering Medical Questions using Scientific Literature.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
The quickly-expanding nature of published medical literature makes it challenging for clinicians and researchers to keep up with and summarize recent, relevant findings in a timely manner. While several closed-source summarization tools based on larg...

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...

AIONER: all-in-one scheme-based biomedical named entity recognition using deep learning.

Bioinformatics (Oxford, England)
MOTIVATION: Biomedical named entity recognition (BioNER) seeks to automatically recognize biomedical entities in natural language text, serving as a necessary foundation for downstream text mining tasks and applications such as information extraction...