{"title":"基于冗余训练矩阵的病理过程智能诊断系统","authors":"A. Dovbysh, A. A. Stadnyk","doi":"10.1109/CRMICO.2014.6959417","DOIUrl":null,"url":null,"abstract":"The method of infection diseases diagnosing is considered within the bounds of information-extreme intelligence technology, which is based on maximization of informational capability of a decision support system in the study process by means of sequential optimization of the redundant binary training matrix. Implementation of the proposed algorithm was done for GRID-center of acute enteric infection diagnosing.","PeriodicalId":6662,"journal":{"name":"2014 24th International Crimean Conference Microwave & Telecommunication Technology","volume":"21 1","pages":"330-331"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Intelligence diagnosis system of pathological process with redundant training matrix\",\"authors\":\"A. Dovbysh, A. A. Stadnyk\",\"doi\":\"10.1109/CRMICO.2014.6959417\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The method of infection diseases diagnosing is considered within the bounds of information-extreme intelligence technology, which is based on maximization of informational capability of a decision support system in the study process by means of sequential optimization of the redundant binary training matrix. Implementation of the proposed algorithm was done for GRID-center of acute enteric infection diagnosing.\",\"PeriodicalId\":6662,\"journal\":{\"name\":\"2014 24th International Crimean Conference Microwave & Telecommunication Technology\",\"volume\":\"21 1\",\"pages\":\"330-331\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 24th International Crimean Conference Microwave & Telecommunication Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CRMICO.2014.6959417\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 24th International Crimean Conference Microwave & Telecommunication Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CRMICO.2014.6959417","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Intelligence diagnosis system of pathological process with redundant training matrix
The method of infection diseases diagnosing is considered within the bounds of information-extreme intelligence technology, which is based on maximization of informational capability of a decision support system in the study process by means of sequential optimization of the redundant binary training matrix. Implementation of the proposed algorithm was done for GRID-center of acute enteric infection diagnosing.