Machine learning to predict abnormal myocardial perfusion from pre-test features
Miller RJH, Hauser MT, Sharir T, Einstein AJ, Fish MB, Ruddy TD, Kaufmann PA, Sinusas AJ, Miller EJ, Bateman TM, Dorbala S, Di Carli M, Huang C, Liang JX, Han D, Dey D, Berman DS, Slomka PJ. Machine learning to predict abnormal myocardial perfusion from pre-test features. Journal Of Nuclear Cardiology 2022, 29: 2393-2403. PMID: 35672567, PMCID: PMC9588501, DOI: 10.1007/s12350-022-03012-6.Peer-Reviewed Original ResearchConceptsAbnormal myocardial perfusionAbnormal perfusionMyocardial perfusionDiamond-Forrester modelCAD consortiumConsecutive patientsInternational registryPre-test informationSPECT-MPIClinical informationPhysician's decisionPatientsPerfusionTesting populationExpert visual interpretationRegistryPopulationMethodsWePhysicians