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Publication Name Artificial Intelligence in Cancer
Manuscript ID 106356
Country China
Category Computer Science, Artificial Intelligence
Manuscript Type Retrospective Study
Article Title Can ChatGPT and DeepSeek help cancer patients: A comparative study of artificial intelligence models in clinical decision support
Manuscript Source Invited Manuscript
All Author List Meng Sun, Jun Yu, Jing-Wen Zhou, Ming Ye, Fang Ye and Mei Ding
Funding Agency and Grant Number
Funding Agency Grant Number
Jiangsu Provincial Key R&D Program No. BE2019723
China Academy of Chinese Medical Sciences No. CI2022E028XB
Corresponding Author Fang Ye, . 1596837403@qq.com
Key Words Artificial intelligence; Clinical decision support; Oncology; ChatGPT; DeepSeek; Precision medicine
Core Tip This study compares the efficacy of ChatGPT [a general-purpose artificial intelligence (AI)] and DeepSeek (a domain-specific clinical AI) in oncology decision support. DeepSeek demonstrated superior diagnostic accuracy (F1-score: 89.2% vs 76.5%) and guideline adherence (Cohen’s κ: 0.82 vs 0.67), while ChatGPT excelled in patient communication (readability score: 8.2/10 vs 6.5/10). Both models underperformed in rare cancer subtypes (F1 < 60%), highlighting the need for hybrid systems integrating technical precision and patient-centered communication. This work advocates for AI models tailored to oncology’s heterogeneous demands, with dynamic updates to address evolving clinical guidelines and rare malignancies.
Citation Sun M, Yu J, Zhou JW, Ye M, Ye F, Ding M. Can ChatGPT and DeepSeek help cancer patients: A comparative study of artificial intelligence models in clinical decision support. Artif Intell Cancer 2025; In press
Received
2025-02-24 10:59
Peer-Review Started
2025-02-24 10:59
To Make the First Decision
Return for Revision
2025-04-02 11:22
Revised
2025-04-02 13:27
Second Decision
2025-04-27 02:43
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief
2025-04-27 08:41
Articles in Press
2025-04-27 08:41
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript
ISSN 2644-3228 (online)
Open Access This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: Https://creativecommons.org/Licenses/by-nc/4.0/
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