Russian Scientists Use Neural Network to Improve Heart Disease Diagnosis
AI analyzes ECG data alongside heart position to detect early signs of cardiovascular disorders.
Researchers from Penza State University and Penza State Technological University have developed a neural network–based method for electrocardiogram (ECG) analysis that significantly improves the accuracy of diagnosing cardiovascular diseases.
The novelty of the approach lies in its simultaneous consideration of standard ECG data and the geometric axis of the heart — a factor that helps reveal structural changes invisible to traditional ECG interpretation. The AI system is already trained to detect markers of sudden cardiac death, chronic heart failure, pulmonary embolism, and myocardial infarction.
Faster and More Accurate Diagnostics
The technology was tested on data from more than 250 patients, and the AI-assisted analysis takes less than 15 minutes. Physicians can then use these results to refine and confirm their final diagnoses.
This innovation could help save countless lives. Cardiovascular diseases remain the leading cause of death worldwide, and technologies like this one bring medicine closer to preventing fatal cardiac events before they occur.
