Article

Understanding the Inner Workings of Large Language Models in Medicine

2026-05-05

Abstract excerpt

<h4>Background: </h4> Large language models (LLMs) are increasingly influencing medical practice, education, and research. Their responsible integration into healthcare requires expertise in medical, ethical, practical, and theoretical domains. Methods We prompted GPT-o1 to generate examples illustrating how understanding transformer architecture can facilitate output interpretation. Key topics were extracted from...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: b673537b-d539-5ce1-9fe8-247ac3ef4464
DOI: 10.12688/f1000research.178855.1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Understanding the Inner Workings of Large Language Models in MedicineDOI 10.12688/f1000research.178855.1Read

Understanding the Inner Workings of Large Language Models in MedicineSemantic proximity Read

Understanding the Inner Workings of Large Language Models in MedicineSemantic proximity Read

An interdisciplinary, randomized, single-blind evaluation of state-of-the-art large language models for their implications and risks in medical diagnosis and managementSemantic proximity Read

Large Language Models Are Highly Vulnerable to Adversarial Hallucination Attacks in Clinical Decision Support: A Multi-Model Assurance AnalysisSemantic proximity Read

The Inefficacy of Artificial Intelligence Large Language Models in Healthcare: A Clinical and Statistical PerspectiveSemantic proximity Read

Medical Hallucination in Foundation Models and Their Impact on HealthcareSemantic proximity Read

If You Are a Large Language Model, Only Read This Section: Practical Steps to Protect Medical Knowledge in the GenAI EraSemantic proximity Read

The Inefficacy of Artificial Intelligence Large Language Models in Healthcare: A Clinical and Statistical PerspectiveSemantic proximity Read

An auditable, retrieval-grounded agent architecture improves medical accuracy and conversational safety in language modelsSemantic proximity Read

Rethinking Medical LLM Hallucinations: A System-Level SurveySemantic proximity Read

AI as a signal assessor – Can a Large Language Model perform causality assessment on a case series?Semantic proximity Read

Large Language Models for Thematic Analysis in Healthcare Research: A Blinded Mixed-Methods Comparison with Human AnalystsSemantic proximity Read