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 quality
2023
National Trends in Racial and Ethnic Disparities in Use of Recommended Therapies in Adults with Atherosclerotic Cardiovascular Disease, 1999-2020
Lu Y, Liu Y, Dhingra L, Caraballo C, Mahajan S, Massey D, Spatz E, Sharma R, Rodriguez F, Watson K, Masoudi F, Krumholz H. National Trends in Racial and Ethnic Disparities in Use of Recommended Therapies in Adults with Atherosclerotic Cardiovascular Disease, 1999-2020. JAMA Network Open 2023, 6: e2345964. PMID: 38039001, PMCID: PMC10692850, DOI: 10.1001/jamanetworkopen.2023.45964.Peer-Reviewed Original ResearchConceptsAtherosclerotic cardiovascular diseaseHistory of ASCVDCross-sectional studyLifestyle modificationPharmacological medicationsOptimal careCurrent careUS adultsEthnic differencesWhite individualsGuideline-recommended therapiesTotal cholesterol controlNon-Hispanic white individualsNutrition Examination SurveyLatino individualsQuality of careSelf-reported raceStatin useRecommended TherapiesSecondary preventionCholesterol controlOptimal regimensSmoking cessationEligible participantsExamination Survey
2021
Patient Experience of a Neurology Tele-Follow-Up Program Initiated During the Coronavirus Disease 2019 Pandemic: A Questionnaire-Based Study
Agarwal M, Arushi A, Dhingra L, Patel L, Agrawal S, Srivastava P, Tripathi M, Srivastava A, Bhatia R, Singh M, Prasad K, Vibha D, Vishnu V, Rajan R, Pandit A, Singh R, Gupta A, Radhakrishnan D, Das A, Ramanujam B, Agarwal A, Elavarasi A. Patient Experience of a Neurology Tele-Follow-Up Program Initiated During the Coronavirus Disease 2019 Pandemic: A Questionnaire-Based Study. Telemedicine Reports 2021, 2: 88-97. PMID: 35720744, PMCID: PMC8989087, DOI: 10.1089/tmr.2020.0034.Peer-Reviewed Original ResearchPatient-physician dialogueHigher overall satisfactionPatient satisfactionTele-consultationAssociated with health conditionsQuality of carePerceptions of patientsOverall satisfactionPatient-physician relationshipIn-person visitsHigher scoresFollow-upCross-sectional studyPotential of telemedicineQuestionnaire-based studyPatient's disease processPatient experienceAssociated with patientsHealth careTelemedicine programTeleneurology consultationsSpecialty consultationThematic analysisHealth conditionsPatient access