{"title":"远程医疗中患者数据处理的模糊遗传算法","authors":"Richa Gupta, Parmod Kumar","doi":"10.1109/GHTC.2012.45","DOIUrl":null,"url":null,"abstract":"Uncertainties and vagueness are always present in the patient data received from far distance. It is, therefore, not possible to extract the information about the patient condition properly, and the patient data need processing before presenting to the physician. In this paper, it has been demonstrated that processing the patient data with a fuzzy-genetic algorithm at physician/expert doctor end will reduce the uncertainties and vagueness in the patient data. The physician is able to diagnose the patient disease with better reliability and prescribe the medicine accordingly.. Initial population for the genetic algorithm is randomly generated with assumed fuzzy functions. These functions are optimized using the theory of reproduction, crossover, and mutation. The result shows that the fuzzy-genetic algorithm gives satisfactory result for processing the patient data for the purpose.","PeriodicalId":265555,"journal":{"name":"2012 IEEE Global Humanitarian Technology Conference","volume":"104 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Fuzzy-Genetic Algorithm for Patient Data Processing in Telemedicine\",\"authors\":\"Richa Gupta, Parmod Kumar\",\"doi\":\"10.1109/GHTC.2012.45\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Uncertainties and vagueness are always present in the patient data received from far distance. It is, therefore, not possible to extract the information about the patient condition properly, and the patient data need processing before presenting to the physician. In this paper, it has been demonstrated that processing the patient data with a fuzzy-genetic algorithm at physician/expert doctor end will reduce the uncertainties and vagueness in the patient data. The physician is able to diagnose the patient disease with better reliability and prescribe the medicine accordingly.. Initial population for the genetic algorithm is randomly generated with assumed fuzzy functions. These functions are optimized using the theory of reproduction, crossover, and mutation. The result shows that the fuzzy-genetic algorithm gives satisfactory result for processing the patient data for the purpose.\",\"PeriodicalId\":265555,\"journal\":{\"name\":\"2012 IEEE Global Humanitarian Technology Conference\",\"volume\":\"104 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE Global Humanitarian Technology Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/GHTC.2012.45\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Global Humanitarian Technology Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GHTC.2012.45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fuzzy-Genetic Algorithm for Patient Data Processing in Telemedicine
Uncertainties and vagueness are always present in the patient data received from far distance. It is, therefore, not possible to extract the information about the patient condition properly, and the patient data need processing before presenting to the physician. In this paper, it has been demonstrated that processing the patient data with a fuzzy-genetic algorithm at physician/expert doctor end will reduce the uncertainties and vagueness in the patient data. The physician is able to diagnose the patient disease with better reliability and prescribe the medicine accordingly.. Initial population for the genetic algorithm is randomly generated with assumed fuzzy functions. These functions are optimized using the theory of reproduction, crossover, and mutation. The result shows that the fuzzy-genetic algorithm gives satisfactory result for processing the patient data for the purpose.