Artificial intelligence (AI) electrocardiogram technology that predicts the risk of heart failure even in asymptomatic patients is attracting attention. Kim Kyung-hee, director of the Incheon Sejong Hospital Heart Transplant Center, presented on the clinical application of AI-based electrocardiograms at an international conference held in Taiwan.
On Wednesday, Kim spoke on “Perioperative Heart Failure Management Using AI-Based Electrocardiography” at the Taiwan Society of Cardiovascular and Thoracic Surgery (TSA 2026) conference held at the Taipei International Convention Center recently, the hospital said.
AI-ECG uses deep learning algorithms to analyze electrocardiogram waveforms. Test results that may seem normal to your doctor can detect signs of heart failure, atrial fibrillation, or left ventricular dysfunction. An electrocardiogram obtained during a regular health checkup may provide a clue to preventing serious heart disease.
This technique is also useful for patients scheduled for surgery. By calculating the likelihood of cardiac complications in advance, the anesthesiology and surgical teams can prepare preventative measures. Its usefulness is particularly high for patients at high cardiovascular risk, such as elderly patients with diabetes and hypertension.
In his lecture, Mr. Kim introduced the AI-ECG risk prediction model and early diagnosis strategy. Related research in perioperative risk assessment and management of serious cardiovascular disease is rapidly expanding worldwide.
“AI is filling the blind spots of traditional electrocardiogram analysis and expanding the range of clinical applications,” Kim said. “It was a meaningful opportunity to share the latest research results with overseas medical professionals.”
