Exploring variation in research priorities generated by AI tools.

ABSTRACT:

Background

Artificial intelligence (AI) tools based on large language models (LLMs) are being increasingly used by researchers and may play a role in health-related research priority-setting exercises (RPSEs). However, little is known about how these tools may differ in the types of research priorities they generate.

Methods

We examined research priorities aimed at improving treatments for four diseases: cancer, COVID-19, HIV, and Alzheimer. We compared the outputs from five AI tools (DeepSeek, ChatGPT, Claude, Perplexity, and Gemini) using SBERT-BioBERT embeddings and cosine similarity scores, and assessed the stability of differences between them by re-running identical prompts and slightly modified versions.

Results

We found that the outputs produced by Gemini were

SUBMITTER: Garry J 

PROVIDER: S-EPMC12856382 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature