Zhibin Dong, Pei Li, Yi Jiang, Zhihan Wang, Shihui Fu, Hebin Che, Meng Liu, Xiaojing Zhao, Chunlei Liu, Chenghui Zhao, Qin Zhong, Chongyou Rao, Siwei Wang, Suyuan Liu, Dayu Hu, Dongjin Wang, Juntao Gao, Kai Guo, Xinwang Liu, En Zhu, Kunlun He
{"title":"Integrative Multi-Omics and Routine Blood Analysis Using Deep Learning: Cost-Effective Early Prediction of Chronic Disease Risks (Adv. Sci. 22/2025)","authors":"Zhibin Dong, Pei Li, Yi Jiang, Zhihan Wang, Shihui Fu, Hebin Che, Meng Liu, Xiaojing Zhao, Chunlei Liu, Chenghui Zhao, Qin Zhong, Chongyou Rao, Siwei Wang, Suyuan Liu, Dayu Hu, Dongjin Wang, Juntao Gao, Kai Guo, Xinwang Liu, En Zhu, Kunlun He","doi":"10.1002/advs.202570175","DOIUrl":null,"url":null,"abstract":"<p><b>Early Prediction of Chronic Disease Risks</b></p><p>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.\n\n <figure>\n <div><picture>\n <source></source></picture><p></p>\n </div>\n </figure></p>","PeriodicalId":117,"journal":{"name":"Advanced Science","volume":"12 22","pages":""},"PeriodicalIF":14.3000,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/advs.202570175","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advanced Science","FirstCategoryId":"88","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/advs.202570175","RegionNum":1,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍:
Advanced Science is a prestigious open access journal that focuses on interdisciplinary research in materials science, physics, chemistry, medical and life sciences, and engineering. The journal aims to promote cutting-edge research by employing a rigorous and impartial review process. It is committed to presenting research articles with the highest quality production standards, ensuring maximum accessibility of top scientific findings. With its vibrant and innovative publication platform, Advanced Science seeks to revolutionize the dissemination and organization of scientific knowledge.