{"title":"妊娠期糖尿病早期风险评估的数据挖掘方法","authors":"Saeed Rouhani, Maryam MirSharif","doi":"10.4018/IJKDB.2018010101","DOIUrl":null,"url":null,"abstract":"Inthisarticle,theauthorsproposedthemethodofmedicaldiagnosisingestationaldiabetesmellitus (GDM)intheinitialstagesofpregnancytofacilitatediagnosesandpreventtheaffection.Nowadays, inindustrialmodernworldwithchanginglifestylealimentalmannertheincidenceofcomplexdisease hasbeenincreasinglygrown.GDMisachronicdiseaseandoneofthemajorhealthproblemsthat isoftendiagnosedinmiddleorlateperiodofpregnancy,whenitistoolateforprediction.Ifitis nottreated,itwillmakeseriouscomplicationsandvarioussideeffectsformotherandchild.This articleisdesignedforansweringtothequestionof:“Whatisthebestapproachintimelyandaccurate predictionofGDM?”Thus,theartificialneuralnetworkanddecisiontreeareproposedtoreducethe amountoferrorandthelevelofaccuracyinanticipatingandimprovingtheprecisionofprediction. Theresultsillustratethatintelligentdiagnosissystemscanimprovethequalityofhealthcare,timely prediction,prevention,andknowledgediscoveryinbioinformatics. KEywoRDS Artificial Neural Network, Data Mining, Decision Tree, GDM, Risk Assessment","PeriodicalId":160270,"journal":{"name":"Int. J. Knowl. Discov. Bioinform.","volume":"182 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Data Mining Approach for the Early Risk Assessment of Gestational Diabetes Mellitus\",\"authors\":\"Saeed Rouhani, Maryam MirSharif\",\"doi\":\"10.4018/IJKDB.2018010101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Inthisarticle,theauthorsproposedthemethodofmedicaldiagnosisingestationaldiabetesmellitus (GDM)intheinitialstagesofpregnancytofacilitatediagnosesandpreventtheaffection.Nowadays, inindustrialmodernworldwithchanginglifestylealimentalmannertheincidenceofcomplexdisease hasbeenincreasinglygrown.GDMisachronicdiseaseandoneofthemajorhealthproblemsthat isoftendiagnosedinmiddleorlateperiodofpregnancy,whenitistoolateforprediction.Ifitis nottreated,itwillmakeseriouscomplicationsandvarioussideeffectsformotherandchild.This articleisdesignedforansweringtothequestionof:“Whatisthebestapproachintimelyandaccurate predictionofGDM?”Thus,theartificialneuralnetworkanddecisiontreeareproposedtoreducethe amountoferrorandthelevelofaccuracyinanticipatingandimprovingtheprecisionofprediction. Theresultsillustratethatintelligentdiagnosissystemscanimprovethequalityofhealthcare,timely prediction,prevention,andknowledgediscoveryinbioinformatics. KEywoRDS Artificial Neural Network, Data Mining, Decision Tree, GDM, Risk Assessment\",\"PeriodicalId\":160270,\"journal\":{\"name\":\"Int. J. Knowl. Discov. Bioinform.\",\"volume\":\"182 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Int. J. Knowl. Discov. Bioinform.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/IJKDB.2018010101\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Int. J. Knowl. Discov. Bioinform.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/IJKDB.2018010101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Data Mining Approach for the Early Risk Assessment of Gestational Diabetes Mellitus
Inthisarticle,theauthorsproposedthemethodofmedicaldiagnosisingestationaldiabetesmellitus (GDM)intheinitialstagesofpregnancytofacilitatediagnosesandpreventtheaffection.Nowadays, inindustrialmodernworldwithchanginglifestylealimentalmannertheincidenceofcomplexdisease hasbeenincreasinglygrown.GDMisachronicdiseaseandoneofthemajorhealthproblemsthat isoftendiagnosedinmiddleorlateperiodofpregnancy,whenitistoolateforprediction.Ifitis nottreated,itwillmakeseriouscomplicationsandvarioussideeffectsformotherandchild.This articleisdesignedforansweringtothequestionof:“Whatisthebestapproachintimelyandaccurate predictionofGDM?”Thus,theartificialneuralnetworkanddecisiontreeareproposedtoreducethe amountoferrorandthelevelofaccuracyinanticipatingandimprovingtheprecisionofprediction. Theresultsillustratethatintelligentdiagnosissystemscanimprovethequalityofhealthcare,timely prediction,prevention,andknowledgediscoveryinbioinformatics. KEywoRDS Artificial Neural Network, Data Mining, Decision Tree, GDM, Risk Assessment
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