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Enhancing Physician-Patient Communication in Oncology Using GPT-4 Through Simplified Radiology Reports: Multicenter Quantitative Study

Enhancing Physician-Patient Communication in Oncology Using GPT-4 Through Simplified Radiology Reports: Multicenter Quantitative Study

This retrospective compliance study was approved by the Ethics Review Committee of Guizhou Provincial People’s Hospital (2024004), the Third Affiliated Hospital of Sun Yat-sen University (B2023074), the Third Xiangya Hospital, Central South University (2024011), and Jiangxi Cancer Hospital (JC2024006). Written informed consent was obtained from individual or guardian participants. To ensure patient confidentiality, all reports were anonymized to remove any personal identifiers before analysis.

Xiongwen Yang, Yi Xiao, Di Liu, Huiyou Shi, Huiyin Deng, Jian Huang, Yun Zhang, Dan Liu, Maoli Liang, Xing Jin, Yongpan Sun, Jing Yao, XiaoJiang Zhou, Wankai Guo, Yang He, Weijuan Tang, Chuan Xu

J Med Internet Res 2025;27:e63786

Leveraging Datathons to Teach AI in Undergraduate Medical Education: Case Study

Leveraging Datathons to Teach AI in Undergraduate Medical Education: Case Study

Each track was associated with its own dataset: (1) Clinical Documentation track participants used the MTS-Dialog dataset of patient-physician conversation transcripts from Abacha et al [26]; (2) Medical Education track participants used the Med QA dataset of practice medical board examination questions from Jin et al [27]; and (3) Mental Health track participants used the Suicide Watch and Mental Health Collection dataset of tagged social media posts from Ji et al [28].

Michael Steven Yao, Lawrence Huang, Emily Leventhal, Clara Sun, Steve J Stephen, Lathan Liou

JMIR Med Educ 2025;11:e63602