Magnetocardiography-Based Ischemic Heart Disease Detection and Localization Using Machine Learning Methods

Conclusion: we have developed an automatic IHD detection and localization system. We find that 1. T wave repolarization synchronicity is an important factor to distinguish IHD from normal subjects 2. Magnetic field pattern is associated with stenosis location. Significance: The proposed machine learning method provides the clinicians a fast and accurate diagnosis tool to - nterpret MCG data, boosting its acceptance into clinics. Furthermore, the magnetic pole characteristics revealed by the method shows to be related to ischemia location, presenting the opportunity to noninvasively locate ischemia.
Source: IEEE Transactions on Biomedical Engineering - Category: Biomedical Engineering Source Type: research