Deep Learning to Assess Long-term Mortality From Chest Radiographs

2019149 citationsJournal Articlegold Open Access

Authors

Michael T. Lu · Massachusetts General Hospital

Alexander Ivanov · Harvard University

Thomas Mayrhofer · University of Applied Sciences Stralsund

Ahmed Hosny · Dana-Farber Cancer Institute

Hugo J.W.L. Aerts · Brigham and Women's Hospital

Udo Hoffmann · Massachusetts General Hospital

Abstract

In this study, the deep learning CXR-risk score stratified the risk of long-term mortality based on a single chest radiograph. Individuals at high risk of mortality may benefit from prevention, screening, and lifestyle interventions.

Topics & Keywords

Radiomics and Machine Learning in Medical Imaging Lung Cancer Diagnosis and Treatment Colorectal Cancer Screening and Detection

UN Sustainable Development Goals

Good health and well-being

Publication Details

Published in: JAMA Network Open

Volume 2, Issue 7, pp. e197416-e197416

DOI: 10.1001/jamanetworkopen.2019.7416

Field-Weighted Citation Impact: 15.54