Identifying patient subgroups with simple Bayes'
暂无分享,去创建一个
Medical records can form the basis of retrospective studies, be used to evaluate hospital practices and guidelines, and provide examples for teaching medicine. Each of these tasks presumes the ability to accurately identify patient subgroups. We describe a method for selecting patient subgroups based on the text of their medical records and demonstrate its effectiveness. We also describe a modification of the basic system that does not assume the existence of a preclassified training set, and illustrate its effectiveness in one retrieval task.
[1] John K. Vries,et al. The medical archival system: An information retrieval system based on distributed parallel processing , 1991, Inf. Process. Manag..
[2] Thomas G. Dietterich. What is machine learning? , 2020, Archives of Disease in Childhood.
[3] Bruce G. Buchanan,et al. Using computer modeling to help identify patient subgroups in clinical data repositories , 1998, AMIA.
[4] Tom Fawcett,et al. Analysis and Visualization of Classifier Performance: Comparison under Imprecise Class and Cost Distributions , 1997, KDD.