Unsupervised machine learning improves risk stratification of patients with visual normal SPECT myocardial perfusion imaging assessments
Bednarski B, Williams M, Pieszko K, Miller R, Huang C, Kwiecinski J, Sharir T, Di Carli M, Fish M, Ruddy T, Hasuer T, Miller E, Acampa W, Berman D, Slomka P. Unsupervised machine learning improves risk stratification of patients with visual normal SPECT myocardial perfusion imaging assessments. European Heart Journal 2022, 43: ehac544.300. DOI: 10.1093/eurheartj/ehac544.300.Peer-Reviewed Original ResearchMajor adverse cardiac eventsPeak systolic blood pressureSystolic blood pressureHigh-risk clustersRisk stratificationMyocardial perfusion imagingNormal perfusionHazard ratioBlood pressureCox proportional hazards analysisHigher left ventricular massHigher body mass indexTomography myocardial perfusion imagingNormal clinical assessmentRisk-stratified subgroupsAdverse cardiac eventsPrevalence of diabetesProportional hazards analysisBetter risk stratificationCoronary artery diseaseImproved risk stratificationManagement of patientsKaplan-Meier curvesBody mass indexLeft ventricular mass