Clinical Sudden Cardiac Death Risk Prediction: A Grid Search Support Vector Machine Multimodel Base on Ventricular Fibrillation Visualization Features

• Main Authors: Xie, Chao Xin, Wang, Liang Hung, Yu, Yan Ting, Ding, Lin Juan, Yang, Tao, Kuo, I. Chun, Wang, Xin Kang, Gao, Jie, Abu, Patricia Angela R
• Format: text
• Published: Archīum Ateneo 2025
• Subjects: ECG; Sudden cardiac death prediction; SVM; Visualizing feature; Analytical, Diagnostic and Therapeutic Techniques and Equipment; Biomedical; Computer Engineering; Computer Sciences; Electrical and Computer Engineering; Medicine and Health Sciences; Physical Sciences and Mathematics
• Online Access: https://archium.ateneo.edu/discs-faculty-pubs/420; https://doi.org/10.1016/j.compeleceng.2024.110022
• Institution: Ateneo De Manila University

Sudden cardiac death (SCD) occurs when an individual experiences ventricular fibrillation (VF) and does not receive intervention within several minutes. Predicting SCD or VF can provide medical professionals with additional time to perform rescues, thereby reducing mortality. This study proposes a n...