Efficiently Assemble Normalization Layers and Regularization for Federated Domain Generalization

no code implementations • 22 Mar 2024 • Khiem Le, Long Ho, Cuong Do, Danh Le-Phuoc, Kok-Seng Wong

Domain shift is a formidable issue in Machine Learning that causes a model to suffer from performance degradation when tested on unseen domains.

Domain Generalization Federated Learning +1

Detecting COVID-19 from digitized ECG printouts using 1D convolutional neural networks

no code implementations • 10 Aug 2022 • Thao Nguyen, Hieu H. Pham, Huy Khiem Le, Anh Tu Nguyen, Ngoc Tien Thanh, Cuong Do

Experiments on the COVID-19 ECG images dataset demonstrate that the proposed digitization method is able to capture correctly the original signals, with a mean absolute error of 28. 11 ms. Our proposed 1D-CNN model, which is trained on the digitized ECG signals, allows identifying individuals with COVID-19 and other subjects accurately, with classification accuracies of 98. 42%, 95. 63%, and 98. 50% for classifying COVID-19 vs. Normal, COVID-19 vs. Abnormal Heartbeats, and COVID-19 vs. other classes, respectively.

A novel deep learning-based approach for sleep apnea detection using single-lead ECG signals

no code implementations • 5 Aug 2022 • Anh-Tu Nguyen, Thao Nguyen, Huy-Khiem Le, Huy-Hieu Pham, Cuong Do

In this study, a novel method of feature extraction based on the detection of S peaks is proposed to enhance the detection of adjacent SA segments using a single-lead ECG.

Feature Engineering Sleep apnea detection +1