MedHalu: Hallucinations in Responses to Healthcare Queries by Large Language Models

University of Surrey · Georgia Institute of Technology

Indexed inarxivcrossrefdatacite

Abstract

Large language models (LLMs) are starting to complement traditional information seeking mechanisms such as web search. LLM-powered chatbots like ChatGPT are gaining prominence among the general public. AI chatbots are also increasingly producing content on social media platforms. However, LLMs are also prone to hallucinations, generating plausible yet factually incorrect or fabricated information. This becomes a critical problem when laypeople start seeking information about sensitive issues such as healthcare. Existing works in LLM hallucinations in the medical domain mainly focus on testing the medical knowledge of LLMs through standardized medical exam questions which are often well-defined and clear-cut…

Citation impact

8
total citations
FWCI
46.61
Percentile
99%
References
0
Citations per year

Authors

6

Topics & keywords

Keywords
  • Health care
  • Psychology
  • Computer science
  • Mental healthcare
  • Cognitive psychology
  • Natural language processing
  • Psychiatry
  • Economics
No related works found for this paper.