Integration of radiomics, deep learning, transcriptomics, and metabolomics reveals prognostic risk stratification and underlying biological mechanisms in colorectal cancer.

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Title: Integration of radiomics, deep learning, transcriptomics, and metabolomics reveals prognostic risk stratification and underlying biological mechanisms in colorectal cancer.
Authors: Li Z; Department of Radiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China., Cai R; Department of Radiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.; Department of Radiology, Cancer hospital of Shantou University Medical College, Shantou, Guangdong, China., Qin Y; Department of Radiology, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, China., Liao X; Department of Radiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China., Wang E; Department of Radiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China., Wu X; Department of Radiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China., Zhao Y; Department of Radiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.; Central Laboratory, Clinical Research Center, Shantou Central Hospital, Shantou, Guangdong, China., Lu Z; Department of Radiology, The Shaoxing People's Hospital, Shaoxing, Zhejiang, China., Lin Y; Department of Radiology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China. ylin1@stu.edu.cn.
Source: NPJ precision oncology [NPJ Precis Oncol] 2026 Mar 06; Vol. 10 (1). Date of Electronic Publication: 2026 Mar 06.
Publication Type: Journal Article
Journal Info: Publisher: Springer Nature Country of Publication: England NLM ID: 101708166 Publication Model: Electronic Cited Medium: Print ISSN: 2397-768X (Print) Linking ISSN: 2397768X NLM ISO Abbreviation: NPJ Precis Oncol Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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Description
ISSN:2397-768X
DOI:10.1038/s41698-026-01331-2