Classification of electrocardiogram and auscultatory blood pressure signals using machine learning models. Issue 7 (1st May 2015) - Seera, Manjeevan; Lim, Chee Peng; Liew, Wei Shiung; Lim, Einly; Loo, Chu Kiong
Highlights Medical data classification problems with two real data sets are investigated. A literature review on biomedical signal processing techniques is provided. The data sets are corrupted with noise to assess the robustness of different models. The logistic regression model produces the best results in noise-free environments. Ensemble-based learning model yields the best results in noisy environments.