Deciphering Diagnoses: How Large Language Models Explanations Influence Clinical Decision Making

• URL: http://arxiv.org/abs/2310.01708v1
• Date: Tue, 3 Oct 2023 00:08:23 GMT
• Title: Deciphering Diagnoses: How Large Language Models Explanations Influence Clinical Decision Making
• Authors: D.Umerenkov, G.Zubkova, A.Nesterov
• Abstract summary: Large Language Models (LLMs) are emerging as a promising tool to generate plain-text explanations for medical decisions. This study explores the effectiveness and reliability of LLMs in generating explanations for diagnoses based on patient complaints.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Clinical Decision Support Systems (CDSS) utilize evidence-based knowledge and patient data to offer real-time recommendations, with Large Language Models (LLMs) emerging as a promising tool to generate plain-text explanations for medical decisions. This study explores the effectiveness and reliability of LLMs in generating explanations for diagnoses based on patient complaints. Three experienced doctors evaluated LLM-generated explanations of the connection between patient complaints and doctor and model-assigned diagnoses across several stages. Experimental results demonstrated that LLM explanations significantly increased doctors' agreement rates with given diagnoses and highlighted potential errors in LLM outputs, ranging from 5% to 30%. The study underscores the potential and challenges of LLMs in healthcare and emphasizes the need for careful integration and evaluation to ensure patient safety and optimal clinical utility.

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