Comparison of Large Language Models in Answering Immuno-Oncology Questions: A Cross-Sectional Study.

ABSTRACT:

Background

The capability of large language models (LLMs) to understand and generate human-readable text has prompted the investigation of their potential as educational and management tools for patients with cancer and healthcare providers.

Materials and methods

We conducted a cross-sectional study aimed at evaluating the ability of ChatGPT-4, ChatGPT-3.5, and Google Bard to answer questions related to 4 domains of immuno-oncology (Mechanisms, Indications, Toxicities, and Prognosis). We generated 60 open-ended questions (15 for each section). Questions were manually submitted to LLMs, and responses were collected on June 30, 2023. Two reviewers evaluated the answers independently.

Results

ChatGPT-4 and ChatGPT-3.5 answered all questions, whereas Google Bard answered

SUBMITTER: Iannantuono GM 

PROVIDER: S-EPMC11067804 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature