Objectives Chest X-rays (CXRs) convey much illegible physiological information that deep
learning model (DLM) has been reported interpreting successfully. Since the …

Background: The performance of chest radiography-based age and sex prediction has not
been well validated. We used a deep learning model to predict the age and sex of healthy …

Chest X-ray (CXR) is one of the most commonly performed medical imaging tests. Although
aging, sex and disease status have been known to cause changes in CXR findings, the …

Background In recent years, there has been considerable research on the use of artificial
intelligence to estimate age and disease status from medical images. However, age …

Objectives The goal of this study was to assess whether a deep learning estimate of age
from a chest radiograph image (CXR-Age) can predict longevity beyond chronological age …

In this paper we present a framework for automatically predicting the gender and age of a
patient using chest x-rays (CXRs). The work of this paper derives from common situations in …

Purpose To assess the prognostic value of a deep learning–based chest radiographic age
(hereafter, CXR-Age) model in a large external test cohort of Asian individuals. Materials …

Objective The biological age progression of the heart varies from person to person. We
developed a deep learning model (DLM) to predict the biological age via ECG to explore its …

Age prediction based on appearances of different anatomies in medical images has been
clinically explored for many decades. In this paper, we used deep learning to predict a …

Purpose To develop and test the performance of deep convolutional neural networks
(DCNNs) for automated classification of age and sex on chest radiographs (CXR). Methods …