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First Name Last Name E-mailsort descending Telephone Institution Area of Expertise Address 1 Address 2 City State ZIP
Wesley DeHaven wmd12@pitt.edu University of Pittsburgh air pollution health effects Pennsylvania
Michael Wolz wolzm@nhlbi.nih.gov 301-435-1295 NHLBI Alzheimer's dementia, biostatistics, cardiovascular risk score, diastolic blood pressure, Framingham risk scale, hypertension, hypertension treatment, Latent Class Analysis, latent variable models, linear regression, lipid levels, marital status, markers, markov, Markov process, Measurement, Measurement error, mini-mental score, Mini-Mental State Exam (MMSE), misclassification, mismeasured variables, missing covariates, missing data, Public Health, public health impact, pulmonary function, pulmonary function test, Risk, risk assessment, risk factor, risk factors, Risk model, risk prediction, risk predictors, risk score, risk score analysis, risk stratification, RR interval, software development, Statistical disclosure limitation, Statistical methods, statistical modeling, statistics, systolic blood pressure 6701 Rockledge Drive #10018 Bethesda Maryland 20892
Wendy Post wpost@jhmi.edu Johns Hopkins University Division of Cardiology Blalock 910 Baltimore Maryland 21212
Lisa Wruck wruck@unc.edu University of North Carolina N/A
chenkai wu wuche@onid.orst.edu Oregon State University age-related changes, Aging, all-cause mortality, methods 206 Bates Hall corvallis Oregon 97333
Xiaojuan Liu xjliu@stanford.edu Stanford University School of Medicine Activities of Daily Living (ADL), Aging, antihypertensive medication, biomarkers, biostatistics, blood pressure control, cardiovascular disease epidemiology, Cohort study, epidemiology, proteomics Alway Building 300 Pasteur Drive Stanford California 94305
xurui Jin xurui.jin@dukekunshan.edu.cn Duke University 1000 genomes, 25(OH)D, 3MSE, AD, age-related changes, Aged, Aged--80 and over, albumin, Albumin to creatinine ratio, albuminuria, Alzheimer Disease, Alzheimer's dementia, Alzheimer's disease, alzheimers disease; risk factors; transition probabilities; progression, Alzheimer’s disease, Alzheimer’s disease risk factors, Alzhiemer's disease, APOE ε4, biomarkers, biostatistics, Machine learning, Vitamin D, vitamin D metabolism N/A
Yvonne Plantinga y.plantinga@umcutrecht.nl Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Heidelberglaan 100 The Netherlands
Yanning Xu y.xu@erasmusmc.nl Erasmus Medical Center thryoid, thyroid, thyroid auto-immunity, Thyroid disease, Thyroid function, Thyroid hormones, thyroid medication, thyroid status, thyroid-stimulating hormone N/A
Yabing Li yabingli@wfubmc.edu N/A
Yacob Tedla yacob.tedla@vumc.org Northwestern University abdominal aorta, anti-hypertensive medication, Anti-Hypertensive Therapy, anticoagulants, aortic distensibility, aortic stenosis, aortosclerosis, arterial disease, arterial plaque, arterial stiffness, arteriosclerosis, blood pressure, blood pressure control, cardiac mortality, Cardiac troponin T, cardiometabolic disease, cardiovascular and thrombotic risk factors, cardiovascular damage, cardiovascular death, cardiovascular disease, cardiovascular disease (CVD), cardiovascular disease epidemiology, cardiovascular disease prediction, cardiovascular disease risk factors, cardiovascular events, carotid artery disease, carotid atherosclerosis, CAROTID WALL THICKENING, Epidemiologic methods, epidemiological studies, epidemiology, hypertension, hypertension medications, hypertension treatment N/A
Yakubu Bene-Alhasan yakubu.bene-alhasan@medstar.net 6173097277 Beth Israel Deaconess Medical Center biostatistics, cardiovascular, epidemiology
Yan Sun yan.v.sun@emory.edu 404-727-9090 Emory University body mass index, epigenetic clock, epigenetics, epigenomics, Gene by Environment Interaction Framework, gene-environment interaction, genetic epidemiology, Genetics, genome wide association study, Genome-wide Methylation Association Study, genomic methodologies, HFPEF, HFREF, infectious diseases, Machine learning, obesity, omics Georgia 30322
David Yanez yanezn@ohsu.edu University of Washington (CHSCC) biostatistics, CHD 840 SW Gaines Street Gaines Hall, Room 155 Portland Oregon 97239
Yanxi Lui yanxi@cs.cmu.edu 412-268-6234 Carnegie Mellon University School of Computer Science, The Robotics Institute 4109 Newell-Simon Hall Pittsburgh Pennsylvania 15213
Yuni Choi yc4429@cumc.columbia.edu Columbia University ASCVD, cardiometabolic disease, cardiometabolic risk factors, cardiovascular, chronic lower respiratory disease, DASH diet, epidemiology N/A
Yvette Conley yconley@pitt.edu University of Pittsburgh 440 Victoria Bldg 3500 Victoria St Pittsburgh Pennsylvania 15261
Ye Yan ye.yan@nih.gov NHLBI age-related changes, Aging, Alzheimer’s disease, Atherosclerotic Cardiovascular Disease N/A
Sachin Yende yendes@upmc.edu University of Pittsburgh Department of Critical Care Medicine 641 Scaife Hall Pittsburgh Pennsylvania 15261
Yohannes Endeshaw yendesh@emory.edu 404-728-6698 Emory Universit N/A
Younghoon Kwon yhkwon@uw.edu 6514979411 University of Washington cardiovascular disease (CVD), cardiovascular health, cardiovascular outcomes, Cardiovascular Prevention, echocardiogram, hypertension, Sleep Disordered Breathing, Sleep disorders, systolic function, systolic heart failure 325 9th Ave. | 2CT-69.1 Seattle Washington 98104
Jenny Yi-Chen Hsieh yhsieh3@uw.edu 2062902370 University of Washington adults, age -related, age at menopause, Aging, Atherosclerotic Cardiovascular Disease, cardioembolic stroke, cardiometabolic disease, cardiometabolic risk, cardiometabolic risk factors, cardiovascular, cardiovascular medication, cardiovascular and thrombotic risk factors, cardiovascular damage, cardiovascular death, cardiovascular disease, cardiovascular disease (CVD), cardiovascular disease epidemiology, cardiovascular disease prediction, cardiovascular disease risk factors, cardiovascular events, cardiovascular exposure, cardiovascular health, cardiovascular health study, Cardiovascular Health Study (CHS), cardiovascular medications, cardiovascular morbitidy, cardiovascular mortality, cardiovascular outcomes, Cardiovascular Prevention, cardiovascular risk, cardiovascular risk factors, cardiovascular risk prediction, caregiver, caregiving, clinical epidemiology; nutrition; heart failure, CLINICAL HEART DISEASE, congestive heart failure, congestive heart failure (CHF), coronary heart disease, coronary heart disease (CHD), coronary heart disease and stroke, disability; cognitive; Medicare; stroke, functional assessment, functional decline, functional dependence, Geriatric Cardiology, Geriatric conditions, Geriatric Heart Failure, geriatric impairment, Geriatric medicine, geriatric medicine and assessment, geriatric syndrome, Geriatrics, Heart, heart failure, heart failure outcomes, Heart failure phenotype. HFpeF, heart failure with preserved ejection fraction, heart failure with reduced ejection fraction, hemorrhagic stroke, incident CHD, incident CHF, incident CVD, incident heart failure, incident stroke, independent activities of daily living (IADL), ischemic heart disease, ischemic stroke, morbidity, mortality, mortality rate, mortality risk, neurobiomarkers, neurofilament light chain, neurofilament llight chain, NT-proBNP, older adult, older adults, postmenopausal estrogen, postmenopausal estrogen, postmenopausal hormone therapy, Postmenopausal hormones, Prevalent CHD, prevalent disease, prevention, preventive, Public Health, public health impact, SEX DIFFERENCES, SOCIOECONOMIC INDICATORS, stroke, stroke in middle age, Stroke incidence, stroke prediction, stroke risk model, stroke severity, survival analysis, vascular disease 3980 15th Ave NE Seattle Washington 98105
Yao Hu yhu23@fredhutch.org Fred Hutch Cancer Research Center cardiometabolic disease, Genome-wide association studies Seattle Washington 98109
Yvonne Michael ylm23@drexel.edu Drexel University School of Public Health epidemiology, Epidemiology of Aging, mobility, spatial epidemiology 3215 Market Street, Nesbitt Hall Philadelphia Pennsylvania 19104
Yuichi Shimada ys3053@cumc.columbia.edu Columbia University cardiomyopathy, ECHO, echocardiogram, echocardiogram abnormalities, echocardiographic correlates, echocardiographic findings, echocardiography, echocardiography (ECHO), HEART DISEASE, heart failure outcomes, heart failure; genetics, Hypertrophy, proteome, proteomics, ventricular hypertrophy, ventricular size, ventricular volume, ventricular wall thickness N/A

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