AI-Assisted Hypothesis Generation to Address Challenges in Cardiotoxicity Research: Simulation Study Using ChatGPT With GPT-4o
Our study demonstrates that ChatGPT with GPT-4o can generate innovative and potentially impactful hypotheses for overcoming critical challenges in cardiotoxicity research. These findings suggest that artificial intelligence-assisted hypothesis generation could play a crucial role in advancing the field of cardiotoxicity, leading to more accurate predictions, earlier detection, and better patient outcomes.
Authors
- Tengda Gu (ORCID: https://orcid.org/0009-0006-8740-894X)
- Weikuan Gu (ORCID: https://orcid.org/0000-0003-1112-8088)
- Cong‐Yi Wang (ORCID: https://orcid.org/0000-0001-7914-168X)
- Chengyuan Yang (ORCID: https://orcid.org/0000-0001-6101-6290)
- Yilan Li (ORCID: https://orcid.org/0000-0001-5706-0088)
- Lan Yao (ORCID: https://orcid.org/0000-0001-6618-4082)
- Dianjun Sun (ORCID: https://orcid.org/0000-0003-1701-4305)
- Minghui Li (ORCID: https://orcid.org/0000-0003-1909-6260)
Institutions
- Harbin Medical University (CN)
- University of Tennessee Health Science Center (US)
- Memphis VA Medical Center (US)
- Campbell Clinic (US)
- Second Affiliated Hospital of Harbin Medical University (CN)
- Hamad bin Khalifa University (QA)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2025-05-15
- DOI
- https://doi.org/10.2196/66161
- Citations
- 1
- Primary Topic
- Heart Failure Treatment and Management
- Type
- article
- Field-Weighted Citation Impact
- 1.39