Carter, Rickey E.

An artificial intelligence-enabled ECG algorithm for the identification of patients with atrial fibrillation during sinus rhythm: a retrospective analysis of outcome prediction

Attia, Z. I., Noseworthy, P. A., Lopez-Jimenez, F., Asirvatham, S. J., Deshmukh, A. J., Gersh, B. J., Carter, R. E., Yao, X., Rabinstein, A. A., Erickson, B. J., et al. (2019) · The Lancet

ECG Monitoring and AnalysisAtrial Fibrillation Management and Outcomes

Cited by 1,613

Screening for cardiac contractile dysfunction using an artificial intelligence–enabled electrocardiogram

Attia, Z. I., Kapa, S., Lopez-Jimenez, F., McKie, P. M., Ladewig, D. J., Satam, G., Pellikka, P. A., Enriquez-Sarano, M., Noseworthy, P. A., Munger, T. M., et al. (2019) · Nature Medicine

ECG Monitoring and AnalysisArtificial Intelligence in Healthcare

Cited by 1,389

Recommendations for Planning Pilot Studies in Clinical and Translational Research

Moore, C. G., Carter, R. E., Nietert, P. J., & Stewart, P. W. (2011) · Clinical and Translational Science

Statistical Methods in Clinical TrialsStatistical Methods in Epidemiology

Cited by 661

Enhanced Protein Translation Underlies Improved Metabolic and Physical Adaptations to Different Exercise Training Modes in Young and Old Humans

Robinson, M. M., Dasari, S., Konopka, A. R., Johnson, M. L., Manjunatha, S., Esponda, R. R., Carter, R. E., Lanza, I. R., & Nair, K. S. (2017) · Cell Metabolism

Muscle metabolism and nutritionCardiovascular and exercise physiology

Cited by 539

Detection of hypertrophic cardiomyopathy using a convolutional neural network-enabled electrocardiogram

Ko, W.-Y., Siontis, K. C., Attia, Z. I., Carter, R. E., Kapa, S., Ommen, S. R., Demuth, S. J., Ackerman, M. J., Gersh, B. J., Arruda-Olson, A. M., et al. (2020) · Journal of the American College of Cardiology

ECG Monitoring and AnalysisCardiac electrophysiology and arrhythmias

Cited by 404

Development and Validation of a Deep-Learning Model to Screen for Hyperkalemia From the Electrocardiogram

Galloway, C. D., Valys, A. V., Shreibati, J. B., Treiman, D. L., Petterson, F. L., Gundotra, V. P., Albert, D. E., Attia, Z. I., Carter, R. E., Asirvatham, S. J., et al. (2019) · JAMA Cardiology

ECG Monitoring and AnalysisPotassium and Related Disorders

Cited by 318

VO2max Trainability and High Intensity Interval Training in Humans: A Meta-Analysis

Bacon, A. P., Carter, R. E., Ogle, E. A., & Joyner, M. J. (2013) · PLoS ONE

Cardiovascular and exercise physiologySports Performance and Training

Cited by 311

Diurnal pattern to insulin secretion and insulin action in healthy individuals

Saad, A., Dalla Man, C., Nandy, D. K., Levine, J. A., Bharucha, A. E., Rizza, R. A., Basu, R., Carter, R. E., Cobelli, C., Kudva, Y. C., et al. (2012) · Diabetes

Diabetes Management and ResearchPancreatic function and diabetes

Cited by 297

Electrocardiogram screening for aortic valve stenosis using artificial intelligence

Cohen-Shelly, M., Attia, Z. I., Friedman, P. A., Ito, S., Essayagh, B. A., Ko, W.-Y., Murphree, D. H., Michelena, H. I., Enriquez-Sarano, M., Carter, R. E., et al. (2021) · European Heart Journal

Cardiac Valve Diseases and TreatmentsECG Monitoring and Analysis

Cited by 252

Effects of Experimental Sleep Restriction on Caloric Intake and Activity Energy Expenditure

Calvin, A. D., Carter, R. E., Adachi, T., Macedo, P. G., Albuquerque, F. N., van der Walt, C., Bukartyk, J., Davison, D. E., Levine, J. A., & Somers, V. K. (2013) · Chest

Regulation of Appetite and ObesitySleep and related disorders

Cited by 196

Artificial Intelligence-Enabled ECG Algorithm to Identify Patients With Left Ventricular Systolic Dysfunction Presenting to the Emergency Department with Dyspnea

Adedinsewo, D., Carter, R. E., Attia, Z., Johnson, P., Kashou, A. H., Dugan, J. L., Albus, M., Sheele, J. M., Bellolio, F., Friedman, P. A., et al. (2020) · Circulation: Arrhythmia and Electrophysiology

ECG Monitoring and AnalysisArtificial Intelligence in Healthcare

Cited by 169

Prospective evaluation of smartwatch-enabled detection of left ventricular dysfunction

Attia, Z. I., Harmon, D. M., Dugan, J., Manka, L., Lopez-Jimenez, F., Lerman, A., Siontis, K. C., Noseworthy, P. A., Yao, X., Klavetter, E. W., et al. (2022) · Nature Medicine

ECG Monitoring and AnalysisNon-Invasive Vital Sign Monitoring

Cited by 154

Sex and age interact to determine clinicopathologic differences in Alzheimer’s disease

Liesinger, A. M., Graff-Radford, N. R., Duara, R., Carter, R. E., Hanna Al-Shaikh, F. S., Koga, S., Hinkle, K. M., DiLello, S. K., Johnson, M. F., Aziz, A., et al. (2018) · Acta Neuropathologica

Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatments

Cited by 126

Diurnal Pattern of Insulin Action in Type 1 Diabetes

Hinshaw, L., Dalla Man, C., Nandy, D. K., Saad, A., Bharucha, A. E., Levine, J. A., Rizza, R. A., Basu, R., Carter, R. E., Cobelli, C., et al. (2013) · Diabetes

Diabetes Management and ResearchPancreatic function and diabetes

Cited by 125

Pathogenesis of Prediabetes: Role of the Liver in Isolated Fasting Hyperglycemia and Combined Fasting and Postprandial Hyperglycemia

Basu, R., Barosa, C., Jones, J., Dube, S., Carter, R., Basu, A., & Rizza, R. A. (2013) · The Journal of Clinical Endocrinology & Metabolism

Pancreatic function and diabetesDiabetes, Cardiovascular Risks, and Lipoproteins

Cited by 121

Artificial Intelligence-Enabled ECG for Left Ventricular Diastolic Function and Filling Pressure

Lee, E., Ito, S., Miranda, W. R., Lopez-Jimenez, F., Kane, G. C., Asirvatham, S. J., Noseworthy, P. A., Friedman, P. A., Carter, R. E., Borlaug, B. A., et al. (2024) · npj Digital Medicine

ECG Monitoring and AnalysisCardiovascular Function and Risk Factors

Cited by 106

Exercise effects on postprandial glucose metabolism in type 1 diabetes: a triple-tracer approach

Mallad, A., Hinshaw, L., Schiavon, M., Dalla Man, C., Dadlani, V., Basu, R., Lingineni, R., Cobelli, C., Johnson, M. L., Carter, R., et al. (2015) · American Journal of Physiology-Endocrinology and Metabolism

Diabetes Management and ResearchDiabetes, Cardiovascular Risks, and Lipoproteins

Cited by 94

The Effect of Walking on Postprandial Glycemic Excursion in Patients With Type 1 Diabetes and Healthy People

Manohar, C., Levine, J. A., Nandy, D. K., Saad, A., Dalla Man, C., McCrady-Spitzer, S. K., Basu, R., Cobelli, C., Carter, R. E., Basu, A., et al. (2012) · Diabetes Care

Diabetes Management and ResearchPhysical Activity and Health

Cited by 89

Continuous Glucose Monitor Interference With Commonly Prescribed Medications: A Pilot Study

Basu, A., Slama, M. Q., Nicholson, W. T., Langman, L., Peyser, T., Carter, R., & Basu, R. (2017) · Journal of Diabetes Science and Technology

Diabetes Management and ResearchElectrochemical sensors and biosensors

Cited by 77

Artificial intelligence guided screening for cardiomyopathies in an obstetric population: a pragmatic randomized clinical trial

Adedinsewo, D. A., Morales-Lara, A. C., Afolabi, B. B., Kushimo, O. A., Mbakwem, A. C., Ibiyemi, K. F., Ogunmodede, J. A., Raji, H. O., Ringim, S. H., Habib, A. A., et al. (2024) · Nature Medicine

Cardiovascular Issues in PregnancyArtificial Intelligence in Healthcare and Education

Cited by 63

Postprandial glucose fluxes and insulin sensitivity during exercise: A study in healthy individuals

Schiavon, M., Hinshaw, L., Mallad, A., Man, C. D., Sparacino, G., Johnson, M., Carter, R., Basu, R., Kudva, Y., Cobelli, C., et al. (2013) · American Journal of Physiology-Endocrinology and Metabolism

Diabetes, Cardiovascular Risks, and LipoproteinsMuscle metabolism and nutrition

Cited by 45

Real-World Performance, Long-Term Efficacy, and Absence of Bias in the Artificial Intelligence Enhanced Electrocardiogram to Detect Left Ventricular Systolic Dysfunction

Harmon, D. M., Carter, R. E., Cohen-Shelly, M., Svatikova, A., Adedinsewo, D. A., Noseworthy, P. A., Kapa, S., Lopez-Jimenez, F., Friedman, P. A., & Attia, Z. I. (2022) · European Heart Journal - Digital Health

ECG Monitoring and AnalysisArtificial Intelligence in Healthcare and Education

Cited by 35

Mitigating bias in clinical machine learning models

Perez-Downes, J. C., Tseng, A. S., McConn, K. A., Elattar, S. M., Sokumbi, O., Sebro, R. A., Allyse, M. A., Dangott, B. J., Carter, R. E., & Adedinsewo, D. (2024) · Current Treatment Options in Cardiovascular Medicine

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 23