Behnken, Emma M.

Artificial intelligence–enabled electrocardiograms for identification of patients with low ejection fraction: a pragmatic, randomized clinical trial

Yao, X., Rushlow, D. R., Inselman, J. W., McCoy, R. G., Thacher, T. D., Behnken, E. M., Bernard, M. E., Rosas, S. L., Akfaly, A., Misra, A., et al. (2021) · Nature Medicine

Artificial Intelligence in Healthcare and EducationECG Monitoring and Analysis

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Artificial intelligence-guided screening for atrial fibrillation using electrocardiogram during sinus rhythm: a prospective non-randomised interventional trial

Noseworthy, P. A., Attia, Z. I., Behnken, E. M., Giblon, R. E., Bews, K. A., Liu, S., Gosse, T. A., Linn, Z. D., Deng, Y., Yin, J., et al. (2022) · The Lancet

Atrial Fibrillation Management and OutcomesECG Monitoring and Analysis

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ECG AI-Guided Screening for Low Ejection Fraction (EAGLE): Rationale and design of a pragmatic cluster randomized trial

Yao, X., McCoy, R. G., Friedman, P. A., Shah, N. D., Barry, B. A., Behnken, E. M., Inselman, J. W., Attia, Z. I., & Noseworthy, P. A. (2020) · American Heart Journal

Artificial Intelligence in Healthcare and EducationECG Monitoring and Analysis

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Determinants of self-reported health outcomes in adrenal insufficiency: a multisite survey study

Li, D., Genere, N., Behnken, E., Xhikola, M., Abbondanza, T., Vaidya, A., & Bancos, I. (2021) · The Journal of Clinical Endocrinology & Metabolism

Adrenal Hormones and DisordersStress Responses and Cortisol

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Normalization of a conversation tool to promote shared decision making about anticoagulation in patients with atrial fibrillation within a practical randomized trial of its effectiveness: a cross-sectional study

Shared Decision Making for Atrial Fibrillation (SDM4AFib) Trial Investigators, Spencer-Bonilla, G., Thota, A., Organick, P., Ponce, O. J., Kunneman, M., Giblon, R., Branda, M. E., Sivly, A. L., Behnken, E., et al. (2020) · Trials

Health Policy Implementation SciencePatient-Provider Communication in Healthcare

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