Unsupervised deep learning of electrocardiograms enables scalable human disease profiling

Unsupervised deep learning of electrocardiograms enables scalable human disease profiling

Abstract The 12-lead electrocardiogram (ECG) is inexpensive and widely available. Whether conditions across the human disease landscape can be detected using the ECG is unclear. We developed a deep learning denoising autoencoder and systematically evaluated associations between ECG encodings and ~1,...

Full description

Saved in:
Bibliographic Details
Main Authors: Sam F. Friedman, Shaan Khurshid, Rachael A. Venn, Xin Wang, Nate Diamant, Paolo Di Achille, Lu-Chen Weng, Seung Hoan Choi, Christopher Reeder, James P. Pirruccello, Pulkit Singh, Emily S. Lau, Anthony Philippakis, Christopher D. Anderson, Mahnaz Maddah, Puneet Batra, Patrick T. Ellinor, Jennifer E. Ho, Steven A. Lubitz
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:npj Digital Medicine
Online Access:https://doi.org/10.1038/s41746-024-01418-9
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items