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

Affiliations

¹ Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55905, USA.
² Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL, USA.
³ Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA.
⁴ Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55905, USA. Electronic address: friedman.paul@mayo.edu.

Comment

Peter A Noseworthy et al. Lancet. 2020.

. 2020 Jul 25;396(10246):236-237.

doi: 10.1016/S0140-6736(20)31064-3.

¹ Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55905, USA.
² Department of Health Sciences Research, Mayo Clinic, Jacksonville, FL, USA.
³ Department of Health Sciences Research, Mayo Clinic, Rochester, MN 55905, USA.
⁴ Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN 55905, USA. Electronic address: friedman.paul@mayo.edu.

No abstract available

Comment on

An AI-ECG algorithm for atrial fibrillation risk: steps towards clinical implementation.
Wolters FJ. Wolters FJ. Lancet. 2020 Jul 25;396(10246):235-236. doi: 10.1016/S0140-6736(20)31062-X. Lancet. 2020. PMID: 32711792 No abstract available.
An AI-ECG algorithm for atrial fibrillation risk: steps towards clinical implementation.
Freedman B. Freedman B. Lancet. 2020 Jul 25;396(10246):236. doi: 10.1016/S0140-6736(20)31063-1. Lancet. 2020. PMID: 32711794 No abstract available.