Strategies for integrating ChatGPT and generative AI into clinical studies
10.1007/s44313-024-00045-3
- Author:
Jeong‑Moo LEE
1
Author Information
1. Department of Surgery, Division of HBP Surgery, Seoul National University Hospital, Seoul National University College of Medicine, 101 Daehak‑ro, Jongno‑Gu, Seoul 03080, Republic of Korea
- Publication Type:REVIEW
- From:Blood Research
2024;59():45-
- CountryRepublic of Korea
- Language:English
-
Abstract:
Large language models, specifically ChatGPT, are revolutionizing clinical research by improving content creation and providing specific useful features. These technologies can transform clinical research, including data collection, analysis, interpretation, and results sharing. However, integrating these technologies into the academic writing work‑ flow poses significant challenges. In this review, I investigated the integration of large-language model-based AI tools into clinical research, focusing on practical implementation strategies and addressing the ethical considerations asso‑ ciated with their use. Additionally, I provide examples of the safe and sound use of generative AI in clinical research and emphasize the need to ensure that AI-generated outputs are reliable and valid in scholarly writing settings. In conclusion, large language models are a powerful tool for organizing and expressing ideas efficiently; however, they have limitations. Writing an academic paper requires critical analysis and intellectual input from the authors. Moreo‑ ver, AI-generated text must be carefully reviewed to reflect the authors’ insights. These AI tools significantly enhance the efficiency of repetitive research tasks, although challenges related to plagiarism detection and ethical use persist.
