2024
Artificial Intelligence in Cardiovascular Clinical Trials
Cunningham J, Abraham W, Bhatt A, Dunn J, Felker G, Jain S, Lindsell C, Mace M, Martyn T, Shah R, Tison G, Fakhouri T, Psotka M, Krumholz H, Fiuzat M, O’Connor C, Solomon S, Collaboratory H. Artificial Intelligence in Cardiovascular Clinical Trials. Journal Of The American College Of Cardiology 2024, 84: 2051-2062. PMID: 39505413, DOI: 10.1016/j.jacc.2024.08.069.Peer-Reviewed Original ResearchMeSH KeywordsArtificial IntelligenceCardiovascular DiseasesClinical Trials as TopicHumansRandomized Controlled Trials as TopicConceptsArtificial intelligenceIntegrate AIPatient privacyClinical trialsRandomized clinical trialsClinical event outcomesCardiovascular clinical trialsIntelligenceInaccurate resultsRandomized trialsInterpreting imagesCardiovascular therapyMedical decision makingDecision makingGold standardValidity of trial resultsClinical trial operationsPrivacy
2023
Foundation models for generalist medical artificial intelligence
Moor M, Banerjee O, Abad Z, Krumholz H, Leskovec J, Topol E, Rajpurkar P. Foundation models for generalist medical artificial intelligence. Nature 2023, 616: 259-265. PMID: 37045921, DOI: 10.1038/s41586-023-05881-4.Peer-Reviewed Original ResearchMeSH KeywordsArtificial IntelligenceDatasets as TopicDiagnostic ImagingElectronic Health RecordsGenomicsHumansMedicineUnsupervised Machine LearningConceptsMedical AILarge medical datasetsMedical artificial intelligenceArtificial intelligence modelsImage annotationMedical datasetsArtificial intelligenceElectronic health recordsAI devicesIntelligence modelsTraining datasetDiverse datasetsExpressive outputHealth recordsRapid developmentDatasetFree-text explanationsMedical modalitiesNew paradigmMedical textsAITechnical capabilitiesDiverse setNewfound capabilitiesCapabilityChatGPT: Temptations of Progress
Doshi R, Bajaj S, Krumholz H. ChatGPT: Temptations of Progress. The American Journal Of Bioethics 2023, 23: 6-8. PMID: 36853242, DOI: 10.1080/15265161.2023.2180110.Peer-Reviewed Original ResearchArtificial IntelligenceHumans
2022
Perspectives of Patients About Artificial Intelligence in Health Care
Khullar D, Casalino LP, Qian Y, Lu Y, Krumholz HM, Aneja S. Perspectives of Patients About Artificial Intelligence in Health Care. JAMA Network Open 2022, 5: e2210309. PMID: 35507346, PMCID: PMC9069257, DOI: 10.1001/jamanetworkopen.2022.10309.Peer-Reviewed Original ResearchAutomated multilabel diagnosis on electrocardiographic images and signals
Sangha V, Mortazavi BJ, Haimovich AD, Ribeiro AH, Brandt CA, Jacoby DL, Schulz WL, Krumholz HM, Ribeiro ALP, Khera R. Automated multilabel diagnosis on electrocardiographic images and signals. Nature Communications 2022, 13: 1583. PMID: 35332137, PMCID: PMC8948243, DOI: 10.1038/s41467-022-29153-3.Peer-Reviewed Original ResearchConceptsConvolutional neural networkArtificial intelligenceApplication of AISignal-based dataSignal-based modelElectrocardiographic imagesECG imagesGrad-CAMImage-based modelsNeural networkDiagnosis modelECG signalsImagesClinical labelsValidation setLabelsExternal validation setMultilabelIntelligenceNetworkApplicationsModelBroad useSetBroader setting
2019
Validation and Regulation of Clinical Artificial Intelligence
Schulz WL, Durant T, Krumholz HM. Validation and Regulation of Clinical Artificial Intelligence. Clinical Chemistry 2019, 65: 1336-1337. PMID: 32100825, DOI: 10.1373/clinchem.2019.308304.Commentaries, Editorials and Letters
2016
Data Acquisition, Curation, and Use for a Continuously Learning Health System
Krumholz HM, Terry SF, Waldstreicher J. Data Acquisition, Curation, and Use for a Continuously Learning Health System. JAMA 2016, 316: 1669-1670. PMID: 27668668, DOI: 10.1001/jama.2016.12537.Peer-Reviewed Original Research