Philip Adejumo
About
Research
Publications
2024
Natural Language Processing of Clinical Documentation to Assess Functional Status in Patients With Heart Failure
Adejumo P, Thangaraj P, Dhingra L, Aminorroaya A, Zhou X, Brandt C, Xu H, Krumholz H, Khera R. Natural Language Processing of Clinical Documentation to Assess Functional Status in Patients With Heart Failure. JAMA Network Open 2024, 7: e2443925. PMID: 39509128, PMCID: PMC11544492, DOI: 10.1001/jamanetworkopen.2024.43925.Peer-Reviewed Original ResearchConceptsFunctional status assessmentArea under the receiver operating characteristic curveClinical documentationElectronic health record dataHF symptomsOptimal care deliveryHealth record dataAssess functional statusStatus assessmentClinical trial participationProcessing of clinical documentsFunctional status groupCare deliveryOutpatient careMain OutcomesMedical notesTrial participantsNew York Heart AssociationFunctional statusQuality improvementRecord dataHeart failureClinical notesDiagnostic studiesStatus groupsAutomated 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 quality
2022
Characteristics of patients referred to a cardiovascular disease clinic for post-acute sequelae of SARS-CoV-2 infection
Wang SY, Adejumo P, See C, Onuma OK, Miller EJ, Spatz ES. Characteristics of patients referred to a cardiovascular disease clinic for post-acute sequelae of SARS-CoV-2 infection. American Heart Journal Plus Cardiology Research And Practice 2022, 18: 100176. PMID: 35856065, PMCID: PMC9277988, DOI: 10.1016/j.ahjo.2022.100176.Peer-Reviewed Original ResearchSARS-CoV-2 infectionCardiovascular disease clinicPost-acute sequelaeDisease clinicCommon symptomsExercise intoleranceChest pain/pressureNew cardiac diagnosesNew cardiovascular diseaseCharacteristics of patientsPain/pressurePattern of symptomsCOVID-19 diagnosisCardiovascular manifestationsCardiovascular symptomsCardiovascular diseaseDiagnostic evaluationObservational studyAverage agePatientsCardiac diagnosisCardiac pathologyCardiovascular diagnosisSymptomsDiagnosis
News
News
- November 05, 2024
Yale Researchers at American Heart Association Scientific Session 2024
- April 01, 2024
Yale Faculty Present Groundbreaking Clinical Research at the 2024 American College of Cardiology Scientific Sessions
- November 01, 2022Source: American Heart Association News
Perceived discrimination increased the risk of worse health outcomes after a heart attack
- May 11, 2022
Insights from the AHA QCOR Scientific Sessions