公开(公告)号：US20220415524A1

公开(公告)日：2022-12-29

申请号：US17361717

申请日：2021-06-29

申请人： International Business Machines Corporation

发明人： Sarah Kefayati ,  PRITHWISH CHAKRABORTY ,  Ajay Ashok Deshpande ,  Vishrawas Gopalakrishnan ,  Jianying Hu ,  Hu Trombley Huang ,  Gretchen Jackson ,  Xuan Liu ,  SAYALI NAVALEKAR ,  Raman Srinivasan

IPC分类号： G16H50/80 ,  G06N20/00 ,  G16H50/70 ,  G16H50/20 ,  G16H40/20

摘要： In an approach for building a machine learning model with a flexible prediction horizon, a processor gathers statistical data related to a disease from one or more regional sources. A processor clusters the statistical data according to a plurality of localized regional source similarity criteria and a plurality of region criteria. A processor builds a plurality of training models based on the clustered statistical data. A processor builds a plurality of feature vectors based on the plurality of localized regional source similarity criteria and the plurality of region criteria. A processor trains the plurality of training models separately against the plurality of feature vectors. A processor selects a best performing training model for each of the plurality of localized regional source similarity criteria and the plurality of region criteria based on a performance criterion. A processor tests the best performing training model to predict one or more future outcomes.