Deep learning-based age estimation from chest X-rays indicates cardiovascular prognosis
H Ieki, K Ito, M Saji, R Kawakami, Y Nagatomo… - Communications …, 2022 - nature.com
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 …
intelligence to estimate age and disease status from medical images. However, age …
Deep learning to estimate biological age from chest radiographs
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 …
from a chest radiograph image (CXR-Age) can predict longevity beyond chronological age …
Deep learning-based age estimation from chest CT scans
Purpose Medical imaging can be used to estimate a patient's biological age, which may
provide complementary information to clinicians compared to chronological age. In this …
provide complementary information to clinicians compared to chronological age. In this …
Age prediction using a large chest x-ray dataset
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 …
clinically explored for many decades. In this paper, we used deep learning to predict a …
External testing of a deep learning model to estimate biologic age using chest radiographs
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 …
(hereafter, CXR-Age) model in a large external test cohort of Asian individuals. Materials …
Estimation of age in unidentified patients via chest radiography using convolutional neural network regression
CF Sabottke, MA Breaux, BM Spieler - Emergency radiology, 2020 - Springer
Purpose Patient age has important clinical utility for refining a differential diagnosis in
radiology. Here, we evaluate the potential for convolutional neural network models to predict …
radiology. Here, we evaluate the potential for convolutional neural network models to predict …
Electrocardiogram-based heart age estimation by a deep learning model provides more information on the incidence of cardiovascular disorders
CH Chang, CS Lin, YS Luo, YT Lee… - Frontiers in Cardiovascular …, 2022 - frontiersin.org
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 …
developed a deep learning model (DLM) to predict the biological age via ECG to explore its …
Using deep neural networks for predicting age and sex in healthy adult chest radiographs
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 …
been well validated. We used a deep learning model to predict the age and sex of healthy …
Heart age gap estimated by explainable advanced electrocardiography is associated with cardiovascular risk factors and survival
Aims Deep neural network artificial intelligence (DNN-AI)–based Heart Age estimations
have been presented and used to show that the difference between an electrocardiogram …
have been presented and used to show that the difference between an electrocardiogram …
Deep neural network-estimated electrocardiographic age as a mortality predictor
EM Lima, AH Ribeiro, GMM Paixão, MH Ribeiro… - Nature …, 2021 - nature.com
The electrocardiogram (ECG) is the most commonly used exam for the evaluation of
cardiovascular diseases. Here we propose that the age predicted by artificial intelligence …
cardiovascular diseases. Here we propose that the age predicted by artificial intelligence …