biostudies-literatureUnknown44Hirota N<h4>Background</h4>There is increasing evidence that 12-lead electrocardiograms (ECG) can be used to predict biological age, which is associated with cardiovascular events. However, the utility of artificial intelligence (AI)-predicted age using ECGs remains unclear.<h4>Methods</h4>Using a single-center database, we developed an AI-enabled ECG using 17 042 sinus rhythm ECGs (SR-ECG) to predict chronological age (CA) with a convolutional neural network that yields AI-predicted age. Using the 5-fold cross validation method, AI-predicted age deriving from the test dataset was yielded for all ECGs. The incidence by AgeDiff and the areas under the curve by receiver operating characteristic curve with AI-predicted age for cardiovascular events were analyzed.<h4>Results</h4>During the mean followInternational journal of cardiology. Heart & vasculature101172https://www.ebi.ac.uk/biostudies/studies/S-EPMC9841236biostudies-literatureCardiovascular events and artificial intelligence-predicted age using 12-lead electrocardiograms.PMC9841236Suzuki SArita THirota NMotogi JSatoh KHyodo ATakayanagi TYamashita TNakai HMatsuzawa WYagi NOtsuka TUmemoto TfalseCardiovascular events and artificial intelligence-predicted age using 12-lead electrocardiograms.<h4>Background</h4>There is increasing evidence that 12-lead electrocardiograms (ECG) can be used to predict biological age, which is associated with cardiovascular events. However, the utility of artificial intelligence (AI)-predicted age using ECGs remains unclear.<h4>Methods</h4>Using a single-center database, we developed an AI-enabled ECG using 17 042 sinus rhythm ECGs (SR-ECG) to predict chronological age (CA) with a convolutional neural network that yields AI-predicted age. Using the 5-fold cross validation method, AI-predicted age deriving from the test dataset was yielded for all ECGs. The incidence by AgeDiff and the areas under the curve by receiver operating characteristic curve with AI-predicted age for cardiovascular events were analyzed.<h4>Results</h4>During the mean follow2023-01-01T00:00:00Z2023 Feb2025-04-04T14:28:22.029Z2025-04-04T14:28:22.029ZS-EPMC98412363665488510.1016/j.ijcha.2023.101172