2003
No-reflow is an independent predictor of death and myocardial infarction after percutaneous coronary intervention
Resnic F, Wainstein M, Lee M, Behrendt D, Wainstein R, Ohno-Machado L, Kirshenbaum J, Rogers C, Popma J, Piana R. No-reflow is an independent predictor of death and myocardial infarction after percutaneous coronary intervention. American Heart Journal 2003, 145: 42-46. PMID: 12514653, DOI: 10.1067/mhj.2003.36.Peer-Reviewed Original ResearchConceptsPercutaneous coronary interventionPostprocedural myocardial infarctionStrong independent predictorMyocardial infarctionIndependent predictorsSodium nitroprussideInhospital outcomesCoronary interventionClinical outcomesSaphenous vein graft interventionIntracoronary vasodilator therapyVein graft interventionAdministration of verapamilAcute myocardial infarctionRate of deathInhospital mortalityVasodilator therapyCardiogenic shockBaseline demographicsGraft interventionUnstable anginaAdverse eventsConsecutive patientsIntracoronary verapamilInfarction
1997
Sequential versus standard neural networks for pattern recognition: An example using the domain of coronary heart disease
Ohno-Machado L, Musen M. Sequential versus standard neural networks for pattern recognition: An example using the domain of coronary heart disease. Computers In Biology And Medicine 1997, 27: 267-281. PMID: 9303265, DOI: 10.1016/s0010-4825(97)00008-5.Peer-Reviewed Original ResearchMeSH KeywordsAdultAge FactorsAlgorithmsArea Under CurveBlood PressureBody WeightCause of DeathCholesterolCoronary DiseaseDatabases as TopicDemographyDisease ProgressionDisease-Free SurvivalEvaluation Studies as TopicFollow-Up StudiesForecastingHumansMaleMiddle AgedModels, CardiovascularNeural Networks, ComputerOutcome Assessment, Health CarePattern Recognition, AutomatedPrognosisROC CurveSmokingSurvival AnalysisTime FactorsConceptsNeural network modelNeural networkSequential neural network modelsTime-oriented dataNetwork modelNeural network architectureStandard neural networkSequential neural networkNeural network systemRecognition of patternsNetwork architecturePattern recognitionUnseen casesNetwork systemTest setSingle pointResearch data basesData basesNetworkMedical researchersSuch modelsRecognitionBackpropagationSetArchitecture
1993
Prognostic classification for aids patients in Brazil
Ohno-Machado L. Prognostic classification for aids patients in Brazil. Journal Of Medical Systems 1993, 17: 163-172. PMID: 8254260, DOI: 10.1007/bf00996941.Peer-Reviewed Original ResearchMeSH KeywordsAcquired Immunodeficiency SyndromeAdolescentAdultAgedAIDS-Related Opportunistic InfectionsBrazilCause of DeathChildChild, PreschoolCross-Sectional StudiesDeveloping CountriesDiscriminant AnalysisFemaleHospitalizationHumansIncidenceInfantInfant, NewbornMaleMiddle AgedNeoplasmsSurvival RateConceptsHospitalized AIDS patientsPrognosis of deathHistory of transfusionGroup IV patientsNumber of infectionsEsophageal candidiasisIV patientsAIDS patientsFirst manifestationAID patientsRisk groupsPrognostic classificationPrognostic variablesSurvival ratePatientsFinal discriminant functionInfectionDiseaseDeathAnalysis groupHospitalizationTransfusionPrognosisGroupCandidiasis