Due to the rapid spread of the new coronavirus variant during the most recent pandemic, it
became difficult to distinguish common cold symptoms from those of other respiratory …

Strict privacy regulations pose challenges to the development of machine learning (ML) in
the field of health technology where data is particularly sensitive. Gathering and using …

Atrial fibrillation (AF) is one of the frequent and potentially dangerous arrhythmias that can
participate in cardioembolic stroke and heart failure. Early AF identification is possible by the …

This study introduces two models, ConvLSTM2D-liquid time-constant network (CLTC) and
ConvLSTM2D-closed-form continuous-time neural network (CCfC), designed for …

Ankle injuries caused by the Anterior Talofibular Ligament (ATFL) are the most common type
of injury. Thus, finding new ways to analyze these injuries through novel technologies is …

Edge computing is becoming increasingly popular in artificial intelligence (AI) application
development due to the benefits of local execution. One widely used approach to overcome …

Background Atrial fibrillation (AF) is one of the common types of cardiac arrhythmias, and its
medical burden is continuously increasing. Wearable ECG signal analysis based on deep …

Deep learning (DL) models have shown promise for the accurate detection of atrial
fibrillation (AF) from electrocardiogram/photoplethysmography (ECG/PPG) data, yet …

In this paper, we proposed the implementation of a simple and lightweight Atrial Fibrillation
detection based on an improved Variable Step Dynamic Threshold Local Binary Pattern …

Accuracy and effectiveness towards multiscale and dense remote sensing multivariate 2D
information with object detection of bi-directional learning method remains challenging. Most …