Artificial intelligence-based models for colorectal cancer diagnosis using laboratory tests: an exploratory retrospective case-control study.

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Bibliographic Details
Title: Artificial intelligence-based models for colorectal cancer diagnosis using laboratory tests: an exploratory retrospective case-control study.
Authors: Lin JM; Department of Clinical Laboratory, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.; Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.; Guangdong Provincial Clinical Research Center for Laboratory Medicine, Guangzhou, China., Huang HY; Department of Clinical Laboratory, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.; Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.; Guangdong Provincial Clinical Research Center for Laboratory Medicine, Guangzhou, China., Tan HL; Department of Clinical Laboratory, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.; Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.; Guangdong Provincial Clinical Research Center for Laboratory Medicine, Guangzhou, China., Ren SW; Department of Clinical Laboratory, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.; Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.; Guangdong Provincial Clinical Research Center for Laboratory Medicine, Guangzhou, China., Lu XM; Department of Clinical Laboratory, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.; Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.; Guangdong Provincial Clinical Research Center for Laboratory Medicine, Guangzhou, China., Liu J; Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.; Guangdong Provincial Clinical Research Center for Laboratory Medicine, Guangzhou, China.; Department of Health Information Management, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China., Li H; Department of Clinical Laboratory, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.; Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.; Guangdong Provincial Clinical Research Center for Laboratory Medicine, Guangzhou, China., Jia HZ; Department of Clinical Laboratory, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.; Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.; Guangdong Provincial Clinical Research Center for Laboratory Medicine, Guangzhou, China., Xiao YH; Department of Clinical Laboratory, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.; Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.; Guangdong Provincial Clinical Research Center for Laboratory Medicine, Guangzhou, China.
Source: Translational cancer research [Transl Cancer Res] 2026 Jun 30; Vol. 15 (6), pp. 461. Date of Electronic Publication: 2026 Jun 25.
Publication Type: Journal Article
Journal Info: Publisher: Pioneer Bioscience Publishing Company Country of Publication: China NLM ID: 101585958 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2219-6803 (Electronic) Linking ISSN: 2218676X NLM ISO Abbreviation: Transl Cancer Res Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2219-6803
DOI:10.21037/tcr-2026-0535