Artificial Intelligence-enabled Large-scale Electrocardiogram Feature Extraction and Exploring Association Between the Extracted Features and Mortality, Stroke or Various Health Outcome of Interest

* In this study, large-scale ECG data (Electrocardiogram data of all patients stored in the MUSE system by measuring standard 12-guided ECG at Severance Health Checkup at Severance Hospital from November 1, 2005 to October 31, 2022) are combined with electronic medical records, National Health Insurance Corporation data, and National Statistical Office death cause data, and the artificial intelligence algorithm is used to extract ECG features to analyze the association between death, stroke, and various health conditions, and to conduct external verification or transfer learning using public databases (e.g., UK Biobank data). * Intended to use a web-based artificial intelligence platform to distribute computational loads generated during large-scale data processing and improve analysis accuracy and efficiency.