Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 14,261 to 14,270 of 211,815 articles

A Study of Classification Methods for Structural Changes in Japanese Medical Institutions Using Generative AI.

Studies in health technology and informatics May 21, 2026
This study examines the use of generative AI to classify structural changes in Japanese medical institutions, where institution code changes hinder longitudinal analysis. Using Ministry of Health data (2020-2024), cases of code change were assessed. ... read more 

Integrating Large Language Models into Thematic Analysis Workflows for Healthcare Research.

Studies in health technology and informatics May 21, 2026
Large language models (LLMs) can accelerate the early stages of thematic analysis while preserving rigor. We piloted a lightweight, open-source LLM pipeline on a single semi-structured interview from a mixed-methods case study of Québec's electronic ... read more 

Uncovering Topics in Dutch Patient Messages in Inflammatory Bowel Disease: A Comparative Study of Embedding Models for Neural Topic Modeling.

Studies in health technology and informatics May 21, 2026
This study applied natural language processing to identify common topics in 12,054 Dutch patient-provider messages in inflammatory bowel disease. Using the BERTopic framework, three embedding models were evaluated with topic diversity, Cv coherence, ... read more 

Combining Anti-Hallucination Strategies for Reliable LLM-Based Clinical Information Extraction.

Studies in health technology and informatics May 21, 2026
We present a novel LLM-based approach for medical concept extraction that combines multiple anti-hallucination strategies. Our Streamlit web application enables flexible pipeline configuration through ensemble methods, Chain-of-Verification, contextu... read more 

MINE: An Interactive Platform for Expert-Guided Medical Information Extraction.

Studies in health technology and informatics May 21, 2026
Clinical reports contain valuable patient information but are difficult to use due to their unstructured format and privacy constraints. We present MINE, a secure and interactive platform that enables experts to collaboratively develop, evaluate, and... read more 

From Unstructured to Structured Nursing Documentation for Myocardial Infarction Patients Using Clinical Practice Guidelines and SNOMED CT.

Studies in health technology and informatics May 21, 2026
This study aims to analyze unstructured nursing documentation of myocardial infarction patients using clinical practice guidelines and SNOMED CT. A total of 72,234 records from 491 patients were annotated using 17 domains derived from the CCCN and AH... read more 

OMOP Extraction of Medical Text Using LLMs: Preliminary Results.

Studies in health technology and informatics May 21, 2026
We used medium-sized LLMs to extract medication data from German discharge letters into the OMOP CDM, achieving >85% accuracy and >75% F1-score, demonstrating the feasibility of OMOP extraction with medium-sized models. read more 

A Federated Benchmark for Clinical Natural Language Processing (FedDRAGON).

Studies in health technology and informatics May 21, 2026
We introduce the FedDRAGON challenge, a federated learning benchmark for clinical natural language processing. The challenge includes 12 information extraction tasks where data is extracted from clinical reports from 4 Dutch care centers. Baseline re... read more 

Co-Designing AI-Supported Clinical Documentation for Rehabilitation.

Studies in health technology and informatics May 21, 2026
Clinical documentation is vital for continuity of care but increasingly burdensome due to administrative demands. This study applies a co-design approach grounded in human-centered AI principles to inform AI-supported documentation system for rehabil... read more 

Language Models for Automatic Clinical Coding in Veterinary Texts: Experimental Results.

Studies in health technology and informatics May 21, 2026
We evaluated six medium-sized generative models (Autoregressive Transformers and a Diffusion Language Model) on automated veterinary ICD-11 coding. Gemma 3n consistently outperformed the others, demonstrating the highest reliability across all metric... read more 
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