Last Updated July 2025
Validation of a Deep Learning-Based Automated Workflow for the Interpretation of the Echocardiogram
- Tromp, J., Bauer, D., Claggett, B. L., Frost, M., Iversen, M. B., Prasad, N., Petrie, M. C., Larson, M. G.,Ezekowitz, J. A., & Solomon, S. D. (2022). A formal validation of a deep learning-based automated workflow for the interpretation of the echocardiogram. Nature Communications, 13(1). https://doi.org/10.1038/s41467-022-34245-1
Automated Interpretation of Systolic and Diastolic Dysfunction on the Echocardiogram: A multicohort study
- Tromp, J., Seekings, P. J., Hung, C.-L., Iversen, M. B., Frost, M. J., Ouwerkerk, W., Jiang, Z., Eisenhaber, F., Goh, R. S. M., Zhao, H., Huang, W., Ling, L.-H., Sim, D., Cozzone, P., Richards, A. M., Lee, H. K., Solomon, S. D., Lam, C. S. P., & Ezekowitz, J. A. (2021). Automated interpretation of systolic and diastolic function on the echocardiogram: a multicohort study. The Lancet Digital Health, 4(1). https://doi.org/10.1016/S2589-7500(21)00235-1
Strain
- Balinisteanu, A., Duchenne, J., Puvrez, A., Wouters, L., Bézy, S., Youssef, A., Minten, L., Bekhuis, Y., van Langenhoven, L., Papangelopoulou, K., Cieplucha, A., Cattapan, I., Tostes, P., Bogaert, J., Vinereanu, D., Thomas, J. D., Badano, L., & Voigt, J.-U. (2025). Vendor Differences in 2D-Speckle Tracking Global Longitudinal Strain: An Update on a Ten-Year Standardization Effort. European Heart Journal - Cardiovascular Imaging. https://doi.org/10.1093/ehjci/jeaf155
- Myhre, P. L., Hung, C., Frost, M., Jiang, Z., Ouwerkerk, W., Teramoto, K., Svedlund, S., Saraste, A., Hage, C., Tan, R., Beussink‐Nelson, L., Fermér, M. L., Gan, L., Hummel, Y. M., Lund, L. H., Shah, S. J., Lam, C. S.P. & Tromp, J. (2023). External validation of a deep learning algorithm for automated echocardiographic strain measurements. European Heart Journal. https://doi.org/10.1093/ehjdh/ztad072
Valvular Disease – Aortic Stenosis
- Dohse, C. A., Kansal, M. M., Twing, A., Frost, M., Equilbec, C., Hill, M. C., Carolina, M., Slostad B., Carter, A., Smith, D., Tiu, D., Lam, C. S. P., Ezekowitz, J. A., Pellikka, P. A., Behan, S., & Krishna, H. (2024). Application of Machine Learning Technology to Automate Proximal Aorta Dimension by Echocardiography. Journal of the American College of Cardiology, 83(13), 1550–1550. https://doi.org/10.1016/s0735-1097(24)03540-x
- Arnold, J. H., Desai, K. V., Slostad, B., Bhayani, S., Ouwerkerk, W., Hummel, Y. M., Lam C. S.P., Ezekowitz, J. A., Frost, M., Jiang, Z., Equilbec, C., Twing, A., Pellikka, P. A., Frazin, L. J., Kansal, M. M., & Krishna, H. (2024). Artificial Intelligence-Assisted Classification of Aortic Stenosis Severity. Journal of the American College of Cardiology, 83(13), 2450–2450. https://doi.org/10.1016/s0735-1097(24)04440-1
- Tsourdinis, G. E., Xia, E., Hussain, K., Sanagala, T., & Karagodin, I. (2024). Machine Learning Based Assessment of Aortic Valve Parameters on Transthoracic Echocardiography and Comparison to Previous Literature. Journal of the American College of Cardiology, 83(13), 1570–1570. https://doi.org/10.1016/s0735-1097(24)03560-5
- Venema, C. S., Bergeijk, V., Plekkenpol, L. H., Tromp, J., W Ouwerkerk, Hummel, Y. M., Krikken, J. A., Der, V., Den, V., Douglas, Y. L., E Lipsic, Voors, A. A., & Wykrzykowska, J. J. (2024). Discordance between symptomatic response and changes in cardiac structure and function one year after transcatheter aortic valve implantation. European Heart Journal, 45(Supplement_1). https://doi.org/10.1093/eurheartj/ehae666.2464
- Krishna, H., Desai, K., Slostad, B., Bhayani, S., Arnold, J. H., Ouwerkerk, W., Hummel, Y., Lam, C. S. P., Ezekowitz, J., Frost, M., Jiang, Z., Equilbec, C., Twing, A., Pellikka, P. A., Frazin, L., & Kansal, M. (2023). Fully Automated Artificial Intelligence Assessment of Aortic Stenosis by Echocardiography. Journal of the American Society of Echocardiography: Official Publication of the American Society of Echocardiography, 36(7), 769–777. https://doi.org/10.1016/j.echo.2023.03.008
Valvular Disease – Mitral Regurgitation