Рақамли технологияларнинг назарий ва амалий масалалари 9-том 3-нөмір (2026) · 147-154-беттер
Analysis of ECG signals based on machine learning models
Облокулов, С.З.
Аңдатпа
The article investigates the effectiveness of electrocardiogram (ECG) signal analysis for arrhythmia detection using classical machine learning and deep learning models based on the MIT-BIH Arrhythmia Database, created by the Massachusetts Institute of Technology and Beth Israel Hospital, which contains expert-annotated heartbeat points and their types. The study was structured as a binary classification task to distinguish between normal and arrhythmia states. The performance of LinearSVC, SVC RBF, Random Forest, 1D-CNN, and CNN-BiLSTM models was evaluated and compared in terms of metrics (accuracy, precision, sensitivity/recall, F1-score), confusion matrix, and training time.
ЭКГаритмиямодельMIT-BIHRandom ForestSVM1D-CNNCNN-BiLSTMDeep LearningMachine Learning
Метадеректер дереккөзі: журналдың OAI-PMH архиві · Sindex толық мәтінді сақтамайды, дереккөзге сілтеме береді.