{"title":"自适应进化决策支持模型","authors":"V. Podgorelec, P. Kokol","doi":"10.1109/ISIE.1999.797015","DOIUrl":null,"url":null,"abstract":"Decision support systems that help physicians are becoming a very important part of medical decision making. They are based on different models and the best of them are providing an explanation together with an accurate and reliable response. One of the most viable among models are decision trees, already used for many medical decision making purposes. Although effective and reliable, the traditional decision tree construction approach contains several deficiencies. Therefore, we decided to develop a self-adapting evolutionary decision support model, that uses evolutionary principles for the induction of decision trees. Our approach can be considered as a good choice for all kinds of real-world decision making, with respect to the advantages of our model, especially in various medical applications.","PeriodicalId":227402,"journal":{"name":"ISIE '99. Proceedings of the IEEE International Symposium on Industrial Electronics (Cat. No.99TH8465)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1999-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Self-adapting evolutionary decision support model\",\"authors\":\"V. Podgorelec, P. Kokol\",\"doi\":\"10.1109/ISIE.1999.797015\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Decision support systems that help physicians are becoming a very important part of medical decision making. They are based on different models and the best of them are providing an explanation together with an accurate and reliable response. One of the most viable among models are decision trees, already used for many medical decision making purposes. Although effective and reliable, the traditional decision tree construction approach contains several deficiencies. Therefore, we decided to develop a self-adapting evolutionary decision support model, that uses evolutionary principles for the induction of decision trees. Our approach can be considered as a good choice for all kinds of real-world decision making, with respect to the advantages of our model, especially in various medical applications.\",\"PeriodicalId\":227402,\"journal\":{\"name\":\"ISIE '99. Proceedings of the IEEE International Symposium on Industrial Electronics (Cat. No.99TH8465)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1999-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ISIE '99. Proceedings of the IEEE International Symposium on Industrial Electronics (Cat. No.99TH8465)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIE.1999.797015\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISIE '99. Proceedings of the IEEE International Symposium on Industrial Electronics (Cat. No.99TH8465)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIE.1999.797015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Decision support systems that help physicians are becoming a very important part of medical decision making. They are based on different models and the best of them are providing an explanation together with an accurate and reliable response. One of the most viable among models are decision trees, already used for many medical decision making purposes. Although effective and reliable, the traditional decision tree construction approach contains several deficiencies. Therefore, we decided to develop a self-adapting evolutionary decision support model, that uses evolutionary principles for the induction of decision trees. Our approach can be considered as a good choice for all kinds of real-world decision making, with respect to the advantages of our model, especially in various medical applications.