Big data and variceal rebleeding prediction in cirrhosis patients  

作　　者：Quan Yuan Wen-Long Zhao Bo Qin 

机构地区：[1]Department of Gastroenterology,The First Affiliated Hospital of Chongqing Medical University,Chongqing 400042,China [2]College of Medical Informatics,Chongqing Medical University,Chongqing 400016,China [3]Medical Data Science Academy,Chongqing 400016,China [4]Chongqing Engineering Research Centre for Clinical Big-data and Drug Evaluation,Chongqing 400016,China [5]Department of Infectious Diseases,The First Affiliated Hospital of Chongqing Medical University,Chongqing 400042,China

出　　处：《Artificial Intelligence in Gastroenterology》2023年第1期1-9,共9页胃肠病学中的人工智能（英文）

摘　　要：Big data has convincing merits in developing risk stratification strategies for diseases.The 6“V”s of big data,namely,volume,velocity,variety,veracity,value,and variability,have shown promise for real-world scenarios.Big data can be applied to analyze health data and advance research in preclinical biology,medicine,and especially disease initiation,development,and control.A study design comprises data selection,inclusion and exclusion criteria,standard confirmation and cohort establishment,follow-up strategy,and events of interest.The development and efficiency verification of a prognosis model consists of deciding the data source,taking previous models as references while selecting candidate predictors,assessing model performance,choosing appropriate statistical methods,and model optimization.The model should be able to inform disease development and outcomes,such as predicting variceal rebleeding in patients with cirrhosis.Our work has merits beyond those of other colleagues with respect to cirrhosis patient screening and data source regarding variceal bleeding.

关 键 词：Big data Disease onset PROGNOSIS Modeling CIRRHOSIS Gastrointestinal rebleeding 

分 类 号：R73[医药卫生—肿瘤]