• Comparative analysis of artifi...

*Result*: Comparative analysis of artificial intelligence tools for the dissemination of colorectal cancer screening guidelines: a novel perspective on early screening education.

Title:
Comparative analysis of artificial intelligence tools for the dissemination of colorectal cancer screening guidelines: a novel perspective on early screening education.
Authors:
Zhang Z; Cancer Center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China., Zhang ZC; Cancer Center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China., Zhang SP; Cancer Center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China., Luan WY; Cancer Center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China., Han S; Cancer Center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China., Xu ZX; Cancer Center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China., Li SS; Cancer Center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China., Wang SJ; Cancer Center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China., Zhao Q; Cancer Center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China., Chen YM; Cancer Center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China., Yuan XY; Cancer Center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China., Zhang SY; Cancer Center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China., Tang XL; The Second Department of Gastrointestinal Surgery, Affiliated Hospital of North Sichuan Medical College, Nanchong, China., Lin SX; Cancer Center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China.; Department of Oncology, Xinhui District People's Hospital, Jiangmen, China., Miao YD; Cancer Center, Yantai Affiliated Hospital of Binzhou Medical University, The 2nd Medical College of Binzhou Medical University, Yantai, China.; Department of Oncology, Xinhui District People's Hospital, Jiangmen, China.; Guangdong Provincial Key Laboratory of Medical Biomechanics, National Key Discipline of Human Anatomy, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China.; Research and Translational Center for Immunological Disorders of Binzhou Medical University, Yantai, China.
Source:
International journal of surgery (London, England) [Int J Surg] 2025 Nov 01; Vol. 111 (11), pp. 8616-8620. Date of Electronic Publication: 2025 Jul 02.
Publication Type:
Journal Article; Comparative Study
Language:
English
Journal Info:
Publisher: Wolters Kluwer Health, Inc Country of Publication: United States NLM ID: 101228232 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1743-9159 (Electronic) Linking ISSN: 17439159 NLM ISO Abbreviation: Int J Surg Subsets: MEDLINE
Imprint Name(s):
Publication: 2023- : [Philadelphia] : Wolters Kluwer Health, Inc.
Original Publication: London : Surgical Associates Ltd., c2004-
MeSH Terms:
Colorectal Neoplasms*/diagnosis , Early Detection of Cancer*/methods , Early Detection of Cancer*/standards , Information Dissemination*/methods , Health Education*/methods , Artificial Intelligence* , Practice Guidelines as Topic*, Humans
References:
Zhou S, Luo X, Chen C, et al. The performance of large language model-powered chatbots compared to oncology physicians on colorectal cancer queries. Int J Surg 2024;110:6509–17.
Conroy G, Mallapaty S. How China created AI model DeepSeek and shocked the world. Nature 2025;638:300–01.
Normile D. Chinese firm’s large language model makes a splash. Science (New York, NY) 2025;387:238.
Kanth P, Inadomi JM. Screening and prevention of colorectal cancer. BMJ (Clinical Research Ed) 2021;374:n1855.
Agha RA, Mathew G, Rashid R, et al. Transparency in the reporting of Artificial INtelligence – the TITAN guideline. Prem J Sci 2025;10:100082.
Wang F, Chen G, Zhang Z, et al. The Chinese Society of Clinical Oncology (CSCO): clinical guidelines for the diagnosis and treatment of colorectal cancer, 2024 update. Cancer Commun (London, England) 2024;45:332–79.
Buhr RG, Romero R, Wisk LE. Promotion of knowledge and trust surrounding scarce resource allocation policies: a randomized clinical trial. JAMA Health Forum 2024;5:e243509.
Sandmann S, Hegselmann S, Fujarski M, et al. Benchmark evaluation of DeepSeek large language models in clinical decision-making. Nat Med 2025.
Boscardin CK, Gin B, Golde PB, Hauer KE. ChatGPT and generative artificial intelligence for medical education: potential impact and opportunity. Acad Med 2024;99:22–27.
Tan S, Xin X, Wu D. ChatGPT in medicine: prospects and challenges: a review article. Int J Surg 2024;110:3701–06.
Contributed Indexing:
Keywords: ChatGPT-4o; Claude 3.5; DeepSeek; artificial intelligence; colorectal cancer; large language models
Entry Date(s):
Date Created: 20250703 Date Completed: 20251208 Latest Revision: 20260224
Update Code:
20260224
PubMed Central ID:
PMC12626496
DOI:
10.1097/JS9.0000000000002951
PMID:
40607944
Database:
MEDLINE

*Further Information*

*This study systematically evaluated the effectiveness of three artificial intelligence (AI) tools - ChatGPT-4o, Claude 3.5, and DeepSeek - in disseminating colorectal cancer screening guidelines to nonmedical populations. Using uniform instructions aligned with the Chinese Society of Clinical Oncology 2024 standards, the AI-generated content was analyzed for accuracy, clarity, and rigor, supplemented by a cross-evaluation mechanism to quantify performance. Key findings revealed that DeepSeek demonstrated superior regional adaptability and logical rigor, while requiring improvements in threshold accuracy; ChatGPT-4o exhibited outdated starting age criteria and oversimplified high-risk population screening protocols; and Claude 3.5 provided a comprehensive framework but lacked critical implementation details. All tools effectively translated complex medical guidelines into accessible language, underscoring AI's potential in public health education. However, outputs necessitated clinical validation and ethical oversight to mitigate data biases. The study emphasizes AI's role as an auxiliary tool for medical knowledge dissemination, advocating for continuous algorithmic optimization, multidisciplinary collaboration, and dynamic regulatory mechanisms to ensure alignment with evolving medical standards while balancing scientific precision and public accessibility.
(Copyright © 2025 The Author(s). Published by Wolters Kluwer Health, Inc.)*