Geske, Jeffrey B.

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

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Natural language processing for identification of hypertrophic cardiomyopathy patients from cardiac magnetic resonance reports

Dewaswala, N., Chen, D., Bhopalwala, H., Kaggal, V. C., Murphy, S. P., Bos, J. M., Geske, J. B., Gersh, B. J., Ommen, S. R., Araoz, P. A., et al. (2022) · BMC Medical Informatics and Decision Making

Biomedical Text Mining and OntologiesCardiomyopathy and Myosin Studies

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Association of GLP-1 receptor agonists versus bariatric surgery with outcomes in obese patients with hypertrophic cardiomyopathy: a multicenter propensity-matched analysis

Mahmoud, A. K., Awad, K., Sheashaa, H., Kandil, O., Farina, J. M., Ibrahim, R., Abdelnabi, M., Allam, M., Mital, R., Shipman, J., et al. (2026) · European Heart Journal - Quality of Care and Clinical Outcomes

Bariatric Surgery and OutcomesCardiomyopathy and Myosin Studies

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