Peter Noseworthy, MD

Associate Professor, Rochester, MN, Cardiovascular Medicine

Emailnoseworthy.peter@mayo.edu

Source: Scopus
Calculated based on no. of publications stored in Pure and citations from Scopus

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Pairing Observational and Patient-level Clinical Trial Data to Assess Cardiovascular Risk Reduction with Catheter Ablation for Atrial Fibrillation
Noseworthy, P. & Yao, X.
Project: Research project
Optimizing stroke prevention for older adults with atrial fibrillation: Towards rigorous evaluation and judicious application of a new device
Noseworthy, P. & Yao, X.
Project: Research project

5080 Citations
36 Scopus h-Index
157 Article
22 Review article
14 Letter
9 Editorial
5 More
- 3 Comment/debate
- 2 Short survey

85-Year-Old Man With Chest Pain
Kashou, A. H., May, A. M. & Noseworthy, P. A., Jan 2020, In : Mayo Clinic proceedings. 95, 1, p. e1-e6
Research output: Contribution to journal › Short survey › peer-review

Open Access
Aggregating multiple real-world data sources using a patient-centered health-data-sharing platform
Dhruva, S. S., Ross, J. S., Akar, J. G., Caldwell, B., Childers, K., Chow, W., Ciaccio, L., Coplan, P., Dong, J., Dykhoff, H. J., Johnston, S., Kellogg, T., Long, C., Noseworthy, P. A., Roberts, K., Saha, A., Yoo, A. & Shah, N. D., Dec 1 2020, In : npj Digital Medicine. 3, 1, 60.
Research output: Contribution to journal › Article › peer-review

Open Access
A lateral lead variant of the de Winter pattern due to left main stenosis and left anterior descending artery occlusion
Kashou, A. H., LoCoco, S., Asirvatham, S. J., May, A. M. & Noseworthy, P. A., Jul 1 2020, In : Journal of Electrocardiology. 61, p. 77-80 4 p.
Research output: Contribution to journal › Article › peer-review
1 Scopus citations
An AI-ECG algorithm for atrial fibrillation risk: steps towards clinical implementation – Authors' reply
Noseworthy, P. A., Attia, Z. I., Carter, R. E., Yao, X. & Friedman, P. A., Jul 25 2020, In : The Lancet. 396, 10246, p. 236-237 2 p.
Research output: Contribution to journal › Letter › peer-review

Open Access
Artificial Intelligence and Machine Learning in Arrhythmias and Cardiac Electrophysiology
Feeny, A. K., Chung, M. K., Madabhushi, A., Attia, Z. I., Cikes, M., Firouznia, M., Friedman, P. A., Kalscheur, M. M., Kapa, S., Narayan, S. M., Noseworthy, P. A., Passman, R. S., Perez, M. V., Peters, N. S., Piccini, J. P., Tarakji, K. G., Thomas, S. A., Trayanova, N. A., Turakhia, M. P. & Wang, P. J., Aug 1 2020, In : Circulation: Arrhythmia and Electrophysiology. p. 873-890 18 p.
Research output: Contribution to journal › Review article › peer-review

Pairing Observational and Patient-level Clinical Trial Data to Assess Cardiovascular Risk Reduction with Catheter Ablation for Atrial Fibrillation

Optimizing stroke prevention for older adults with atrial fibrillation: Towards rigorous evaluation and judicious application of a new device

85-Year-Old Man With Chest Pain

Aggregating multiple real-world data sources using a patient-centered health-data-sharing platform

A lateral lead variant of the de Winter pattern due to left main stenosis and left anterior descending artery occlusion

An AI-ECG algorithm for atrial fibrillation risk: steps towards clinical implementation – Authors' reply

Artificial Intelligence and Machine Learning in Arrhythmias and Cardiac Electrophysiology