Integrative Multi‐Omics and Routine Blood Analysis Using Deep Learning: Cost‐Effective Early Prediction of Chronic Disease Risks (Adv. Sci. 22/2025)

Early Prediction of Chronic Disease Risks In article number 2412775, Zhibin Dong, Pei Li, Zhihan Wang, Kai Guo, Kunlun He, and co-workers developed a deep learning model called Omicsformer for detailed analysis and classification of routine blood samples. Omicsformer adeptly identified potential risks for nine diseases including cancer, cardiovascular conditions, and psychiatric conditions. Analysis of risk trajectories from 20 years of large clinical patients confirmed the validity of the group in preclinical risk assessment, revealing trends in increased disease risk at the time of onset.