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Article

Artificial intelligence-driven integration of multi-biofluid omics and clinical phenotype enables stratification of endometrial cancer.

Cell reports. Medicine - 16 Jun 2026

Li Dandan, Wu Pengfei, Zheng Jianxujie, Yang Yunhan, Shan Weiwei, Yi Jia, Zhao Dan, Yang Shijun, Hu Yiwei, Zhu Xinying, Fan Ruibin, Fu Pengxiao, Bai Chenqi, Chen Xiaojun, Qiao Liang

Abstract excerpt

Endometrial cancer (EC) incidence is rising, yet current diagnostics lack precision and scalability. We develop an artificial intelligence (AI)-based platform integrating multi-biofluid omics and clinical data for EC stratification. Using two independent cohorts from different clinical centers (531 participants for model development, 204 for external validation), we collect 1,179 samples (plasma, cervical/uterine...

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Identifiers

PMID: 42140194
DOI: 10.1016/j.xcrm.2026.102805
PMCID: PMC13293950

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

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