Deep learning predicts all-cause mortality from longitudinal total-body DXA imaging

Autor: Yannik Glaser, John Shepherd, Lambert Leong, Thomas Wolfgruber, Li-Yung Lui, Peter Sadowski, Steven R. Cummings
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Communications Medicine, Vol 2, Iss 1, Pp 1-12 (2022)
Druh dokumentu: article
ISSN: 2730-664X
DOI: 10.1038/s43856-022-00166-9
Popis: Glaser et al. develop a deep learning system to predict all-cause mortality from total-body DXA scans. Their best predictive model integrates longitudinal body composition data with traditional mortality risk factors.
Databáze: Directory of Open Access Journals