Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Editorial
. 2022 Mar 22;1(1):100017.
doi: 10.1016/j.jacadv.2022.100017. eCollection 2022 Mar.

Deep Learning in Medicine

Augustin Toma  1   2 , Gerhard-Paul Diller  3 , Patrick R Lawler  4   5   6
Affiliations
Editorial

Deep Learning in Medicine

Augustin Toma et al. JACC Adv. .
No abstract available

Keywords: artificial intelligence; deep learning; electrocardiography; machine learning.

PubMed Disclaimer

Conflict of interest statement

Dr Lawler is supported by a Heart and Stroke Foundation of Canada National New Investigator award; and has received unrelated research funding from the Canadian Institutes of Health Research, the National Institutes of Health (National Heart, Lung, and Blood Institute), the Peter Munk Cardiac Centre, the LifeArc Foundation, the Thistledown Foundation, the Ted Rogers Centre for Heart Research, the Medicine by Design Fund, the University of Toronto, and the Government of Ontario. Dr Lawler has received unrelated consulting honoraria from Novartis, CorEvitas, and Brigham and Women's Hospital; and unrelated royalties from McGraw-Hill Publishing. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Figures

None
Graphical abstract
Figure 1
Figure 1
Feedforward Networks are the Simplest Form of Artificial Neural Networks, Although No Longer Typically Used for Computer Vision Tasks They Illustrate Core Concepts in Neural Network Architecture
See this image and copyright information in PMC

Comment on

  • doi: 10.1016/j.jacadv.2022.100003

References

    1. Schlesinger D.E., Diamant N., Raghu A., et al. A deep learning model for inferring elevated pulmonary capillary wedge pressures from the 12-lead electrocardiogram. JACC Adv. 2022;1(1):100003.
    1. Raghunath S., Pfeifer J.M., Ulloa-Cerna A.E., et al. Deep neural networks can predict new-onset atrial fibrillation from the 12-lead ECG and help identify those at risk of atrial fibrillation-related stroke. Circulation. 2021;143:1287–1298. doi: 10.1161/CIRCULATIONAHA.120.047829. - DOI - PMC - PubMed
    1. Attia Z.I., Friedman P.A., Noseworthy P.A., et al. Age and sex estimation using artificial intelligence from standard 12-lead ECGs. Circ Arrhythmia Electrophysiol. 2019;12(9):1–11. doi: 10.1161/CIRCEP.119.007284. - DOI - PMC - PubMed

Publication types

LinkOut - more resources