2020
Engaging heart failure patients from a clinical data research network: A survey on willingness to participate in different types of research.
Choi Y, López J, Meeker D, Ohno-Machado L, Kim K. Engaging heart failure patients from a clinical data research network: A survey on willingness to participate in different types of research. AMIA Annual Symposium Proceedings 2020, 2019: 305-312. PMID: 32308823, PMCID: PMC7153117.Peer-Reviewed Original ResearchConceptsClinical Data Research NetworkHeart failure patientsLarge cohort studyResearch participationResearch NetworkCohort studyFailure patientsOne-time surveyPatient cohortObservational studyPatient motivationWeight controlSignificant associationClinical researchPatientsPrecision medicineHealth dataRecruitment effortsNational effortsActivity interestsSurgeryCohort
2018
A Novel Stakeholder Engagement Approach for Patient-centered Outcomes Research
Kim K, Khodyakov D, Marie K, Taras H, Meeker D, Campos H, Ohno-Machado L. A Novel Stakeholder Engagement Approach for Patient-centered Outcomes Research. Medical Care 2018, 56: s41-s47. PMID: 30074950, PMCID: PMC6143220, DOI: 10.1097/mlr.0000000000000790.Peer-Reviewed Original ResearchConceptsClinical Data Research NetworkPatient-centered outcomes researchEngagement of patientsOutcomes research studiesConditions of focusStakeholder advisory boardPatient-centered outcomes research studiesKawasaki diseaseHeart failurePatient advocatesPatientsClinical sitesOutcomes researchSignificant differencesHealth researchCliniciansResearch NetworkResearch prioritiesSetting of prioritiesEngagement strategiesAdvisory BoardFavorable opinionObesityEngagement principlesDisease
2000
Risk stratification in heart failure using artificial neural networks.
Atienza F, Martinez-Alzamora N, De Velasco J, Dreiseitl S, Ohno-Machado L. Risk stratification in heart failure using artificial neural networks. AMIA Annual Symposium Proceedings 2000, 32-6. PMID: 11079839, PMCID: PMC2243942.Peer-Reviewed Original ResearchConceptsNeural network modelNeural networkNetwork modelMedical classification problemsArtificial neural networkSimple neural networkHeart failureAutomatic relevance determination (ARD) methodClassification problemRisk stratificationOne-year event-free survivalOne-year prognosisEvent-free survivalAccurate risk stratificationHeart failure patientsComplex multisystem diseaseNetworkFailure patientsMultisystem diseaseResampling methodPatientsPrognosisOutcomesPredictorsFailureMajor complications after angioplasty in patients with chronic renal failure: a comparison of predictive models.
Lacson R, Ohno-Machado L. Major complications after angioplasty in patients with chronic renal failure: a comparison of predictive models. AMIA Annual Symposium Proceedings 2000, 457-61. PMID: 11079925, PMCID: PMC2243840.Peer-Reviewed Original ResearchConceptsPercutaneous transluminal coronary angioplastyEnd-stage renal diseaseChronic renal failureMajor complicationsRenal failureCongestive heart failurePatient risk factorsTransluminal coronary angioplastyLogistic regression modelsCoronary angioplastyHeart failureRenal diseasePoor outcomeMyocardial infarctionRisk factorsPrior historyPresence of shockComplicationsLogistic regressionPatientsDiscriminatory abilityDemographic characteristicsAngioplastyRegression modelsStandard logistic regression model