Ebinger, Joseph

Video-based AI for beat-to-beat assessment of cardiac function

Ouyang, D., He, B., Ghorbani, A., Yuan, N., Ebinger, J., Langlotz, C. P., Heidenreich, P. A., Harrington, R. A., Liang, D. H., Ashley, E. A., et al. (2020) · Nature

Cardiovascular Function and Risk FactorsArtificial Intelligence in Healthcare and Education

Cited by 1,153

Sex Differences in Blood Pressure Trajectories Over the Life Course

Ji, H., Kim, A., Ebinger, J. E., Niiranen, T. J., Claggett, B. L., Bairey Merz, C. N., & Cheng, S. (2020) · JAMA Cardiology

Blood Pressure and Hypertension StudiesCardiovascular Health and Disease Prevention

Cited by 556

Blinded, randomized trial of sonographer versus AI cardiac function assessment

He, B., Kwan, A. C., Cho, J. H., Yuan, N., Pollick, C., Shiota, T., Ebinger, J., Bello, N. A., Wei, J., Josan, K., et al. (2023) · Nature

Artificial Intelligence in Healthcare and EducationCardiovascular Function and Risk Factors

Cited by 256

Deep learning evaluation of biomarkers from echocardiogram videos

Hughes, J. W., Yuan, N., He, B., Ouyang, J., Ebinger, J., Botting, P., Lee, J., Theurer, J., Tooley, J. E., Nieman, K., et al. (2021) · EBioMedicine

Artificial Intelligence in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 71

Electrocardiographic deep learning for predicting post-procedural mortality: a model development and validation study

Ouyang, D., Theurer, J., Stein, N. R., Hughes, J. W., Elias, P., He, B., Yuan, N., Duffy, G., Sandhu, R. K., Ebinger, J., et al. (2024) · The Lancet Digital Health

ECG Monitoring and AnalysisCardiac, Anesthesia and Surgical Outcomes

Cited by 64