Diagnostic performance of generative artificial intelligences for a series of complex case reports.

ABSTRACT:

Background

Diagnostic performance of generative artificial intelligences (AIs) using large language models (LLMs) across comprehensive medical specialties is still unknown.

Objective

We aimed to evaluate the diagnostic performance of generative AIs using LLMs in complex case series across comprehensive medical fields.

Methods

We analyzed published case reports from the American Journal of Case Reports from January 2022 to March 2023. We excluded pediatric cases and those primarily focused on management. We utilized three generative AIs to generate the top 10 differential-diagnosis (DDx) lists from case descriptions: the fourth-generation chat generative pre-trained transformer (ChatGPT-4), Google Gemini (previously Bard), and LLM Meta AI 2 (LLaMA2) chatbot. Two

SUBMITTER: Hirosawa T 

PROVIDER: S-EPMC11369864 | biostudies-literature | 2024 Jan-Dec

REPOSITORIES: biostudies-literature