2024
Automated Identification of Heart Failure With Reduced Ejection Fraction Using Deep Learning-Based Natural Language Processing
Nargesi A, Adejumo P, Dhingra L, Rosand B, Hengartner A, Coppi A, Benigeri S, Sen S, Ahmad T, Nadkarni G, Lin Z, Ahmad F, Krumholz H, Khera R. Automated Identification of Heart Failure With Reduced Ejection Fraction Using Deep Learning-Based Natural Language Processing. JACC Heart Failure 2024 PMID: 39453355, DOI: 10.1016/j.jchf.2024.08.012.Peer-Reviewed Original ResearchReduced ejection fractionEjection fractionHeart failureLeft ventricular ejection fractionVentricular ejection fractionYale-New Haven HospitalIdentification of patientsCommunity hospitalIdentification of heart failureLanguage modelNorthwestern MedicineMeasure care qualityQuality of careNew Haven HospitalDeep learning-based natural language processingHFrEFGuideline-directed careDeep learning language modelsMIMIC-IIIDetect HFrEFNatural language processingReclassification improvementHospital dischargePatientsCare qualityArtificial Intelligence for Cardiovascular Care—Part 1: Advances JACC Review Topic of the Week
Elias P, Jain S, Poterucha T, Randazzo M, Lopez Jimenez F, Khera R, Perez M, Ouyang D, Pirruccello J, Salerno M, Einstein A, Avram R, Tison G, Nadkarni G, Natarajan V, Pierson E, Beecy A, Kumaraiah D, Haggerty C, Avari Silva J, Maddox T. Artificial Intelligence for Cardiovascular Care—Part 1: Advances JACC Review Topic of the Week. Journal Of The American College Of Cardiology 2024, 83: 2472-2486. PMID: 38593946, DOI: 10.1016/j.jacc.2024.03.400.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsEnhanced image qualityHuman expertsLeverage AIEvaluation benchmarkArtificial intelligenceAI modelsAI advancementsDetect diseaseTraining methodsImage qualityReduced ejection fractionEvolving technologyValvular heart diseaseReal-world efficacyEjection fractionProvider experienceHeart diseaseTechnologyCardiovascular carePatient careUnique characteristicsIntelligenceBenchmarks
2021
Nonalcoholic Fatty Liver Disease and Risk of Heart Failure Among Medicare Beneficiaries
Fudim M, Zhong L, Patel KV, Khera R, Abdelmalek MF, Diehl AM, McGarrah RW, Molinger J, Moylan CA, Rao VN, Wegermann K, Neeland IJ, Halm EA, Das SR, Pandey A. Nonalcoholic Fatty Liver Disease and Risk of Heart Failure Among Medicare Beneficiaries. Journal Of The American Heart Association 2021, 10: e021654. PMID: 34755544, PMCID: PMC8751938, DOI: 10.1161/jaha.121.021654.Peer-Reviewed Original ResearchConceptsNonalcoholic fatty liver diseaseIncident heart failureReduced ejection fractionFatty liver diseaseHeart failureEjection fractionMedicare beneficiariesHF subtypesLiver diseaseHigh riskBackground Nonalcoholic fatty liver diseaseBaseline NAFLDAssociation of NAFLDNew-onset heart failureConclusions PatientsCohort studyPrior diagnosisBlack patientsNinth RevisionKidney diseaseOutpatient claimsRisk factorsIndependent associationHigh burdenMedicare patients
2019
Machine Learning Prediction of Mortality and Hospitalization in Heart Failure With Preserved Ejection Fraction
Angraal S, Mortazavi BJ, Gupta A, Khera R, Ahmad T, Desai NR, Jacoby DL, Masoudi FA, Spertus JA, Krumholz HM. Machine Learning Prediction of Mortality and Hospitalization in Heart Failure With Preserved Ejection Fraction. JACC Heart Failure 2019, 8: 12-21. PMID: 31606361, DOI: 10.1016/j.jchf.2019.06.013.Peer-Reviewed Original ResearchConceptsHF hospitalizationRisk of mortalityEjection fractionBlood urea nitrogen levelsLogistic regressionPrevious HF hospitalizationHeart failure hospitalizationReduced ejection fractionReceiver-operating characteristic curveRisk of deathBody mass indexBlood urea nitrogenUrea nitrogen levelsHealth status dataMean c-statisticKCCQ scoresTOPCAT trialFailure hospitalizationHeart failureHemoglobin levelsMass indexC-statisticHospitalizationUrea nitrogenMortality