DESIGN AUTOMATIONOFDECISIONSUPPORT SYSTEMS FORCARDIOVASCULARDISEASE PREDICTION

Abstract

Cardiovasculardisease(CVD)topsthelistamongallmajorcausesofdeathworldwide. Only cardiovasculardiseasesaccountfor 17 million deathsworldwide.CVDisamong such diseases,withamortalityrateofapproximately 7 million perannum. CVD isa general termpopularlyusedfordiseaseoftheheartorbloodvessels,includingatheroscle- rosis, cardiomyopathy,coronaryarterydisease,peripheralvasculardisease,andothers. Though, otherthanabalancedlifestyle,earlydetection,prognostication,andin-timedi- agnosis canreducethemortalityrateandincreasepatients’survivalrate.Conventional computer-aideddesign(CAD)detectionsystemsarecumbersomeandexpensive.The massivevariationinthecountries’economicgrowthanddevelopment,accompaniedby the unavailabilityorscarcityofmedicalexpertsandradiologistsduetoseveralreasons, is aprominentfactorforhindranceinearlydiagnosis.Researchersandacademiciansare developingthedecisionsupportsystemstoprovidediagnosticstothehumanracewithout anydifferencesconsideringgeographical,economic,andfinancialcomparisons,which will assistdoctorsandradiologistsinprognosticationandassessment.Amongvarious effortstodevelopdecisionsupportsystems,computationalintelligenceisanemerging trend inmedicalimagingtodetect,prognosticate,anddiagnosethedisease.Therefore, this iswhenresearchersanddoctorsarecollaborativelylookingforwardtodevelopinga computational intelligencesysteminmedicalimagingsystemsforprognostication,iden- tification, treatment,anddiseasediagnosis.Ithelpsradiologistsanddoctorstogetrelief from beingover-burdenedandminimizestheinduceddelaysforin-timediagnosisofpa- tients.