Early Prediction of Liver Cirrhosis Up to Two Years in Advance: A Machine Learning Study Benchmarking Against the FIB-4 and APRI Scores
提前两年预测肝硬化:一项机器学习研究,与FIB-4和APRI评分的基准比较
机构 * Center for Health Systems Innovation, Oklahoma State University(俄克拉荷马州立大学健康系统创新中心) ; Department of Management Science and Information Systems, Oklahoma State University(俄克拉荷马州立大学管理科学与信息系统系) ; Department of Health Services Administration, University of Alabama at Birmingham(阿拉巴马大学伯明翰分校健康服务管理系) ; Division of Gastroenterology and Hepatology, Department of Medicine, University of Alabama at Birmingham(阿拉巴马大学伯明翰分校消化内科与肝病科) ; College of Medicine, The University of Oklahoma Health Campus(俄克拉荷马大学健康校园医学院) ; Department of Family and Community Medicine, University of Alabama at Birmingham(阿拉巴马大学伯明翰分校家庭与社区医学系)
专题命中 临床大模型 :diagnosis(abstract);分类 cs.LG
AI总结 本研究利用常规电子健康记录数据开发XGBoost模型,在诊断前1年和2年预测肝硬化,性能优于FIB-4和APRI评分。