{"title":"心脏旁路手术后出血的朴素贝叶斯预测","authors":"I. Smith, R. Lister, M. Ray, G. Hawson","doi":"10.1109/ANZIIS.2001.974097","DOIUrl":null,"url":null,"abstract":"Excessive post-operative bleeding occurs in approximately one out of eight patients who undergo heart bypass surgery. Earlier workers have identified laboratory parameters that are correlated with post-operative blood loss but these correlations are not strong enough to be clinically useful. This paper describes a predictor that combines several of these parameters using Naive Bayesian Reasoning, to produce a clinically useful predictor of blood loss.","PeriodicalId":383878,"journal":{"name":"The Seventh Australian and New Zealand Intelligent Information Systems Conference, 2001","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Naive Bayesian prediction of bleeding after heart by-pass surgery\",\"authors\":\"I. Smith, R. Lister, M. Ray, G. Hawson\",\"doi\":\"10.1109/ANZIIS.2001.974097\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Excessive post-operative bleeding occurs in approximately one out of eight patients who undergo heart bypass surgery. Earlier workers have identified laboratory parameters that are correlated with post-operative blood loss but these correlations are not strong enough to be clinically useful. This paper describes a predictor that combines several of these parameters using Naive Bayesian Reasoning, to produce a clinically useful predictor of blood loss.\",\"PeriodicalId\":383878,\"journal\":{\"name\":\"The Seventh Australian and New Zealand Intelligent Information Systems Conference, 2001\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Seventh Australian and New Zealand Intelligent Information Systems Conference, 2001\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ANZIIS.2001.974097\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Seventh Australian and New Zealand Intelligent Information Systems Conference, 2001","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ANZIIS.2001.974097","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Naive Bayesian prediction of bleeding after heart by-pass surgery
Excessive post-operative bleeding occurs in approximately one out of eight patients who undergo heart bypass surgery. Earlier workers have identified laboratory parameters that are correlated with post-operative blood loss but these correlations are not strong enough to be clinically useful. This paper describes a predictor that combines several of these parameters using Naive Bayesian Reasoning, to produce a clinically useful predictor of blood loss.