This paper presents an automated machine learning framework designed to assist
hydrologists in detecting anomalies in time series data generated by sensors in a research …

Introduction: Atrial fibrillation (AF) is the most common cardiac arrhythmia, which is clinically
identified with irregular and rapid heartbeat rhythm. AF puts a patient at risk of forming blood …

Wearable systems measuring human physiological indicators with integrated sensors and
supervised learning-based medical image analysis (eg ECG, X-ray, CT or ultrasound …

Myocardial scar (MS) and left ventricular ejection fraction (LVEF) are vital cardiovascular
parameters, conventionally determined using cardiac magnetic resonance (CMR). However …

Abstract Machine learning contributes in improving the accuracy of melanoma detection.
There are extensive studies in classic and deep learning-based approaches for melanoma …

Deep learning technology has been widely adopted in the research of automatic arrhythmia
detection. However, there are several limitations in existing diagnostic models, eg …

Bangla Handwritten Character Recognition (HCR) remains a persistent challenge within the
domain of Optical Character Recognition (OCR) systems. Despite extensive research efforts …

The utilization of deep learning on electrocardiogram (ECG) analysis has brought the
advanced accuracy and efficiency of cardiac healthcare diagnostics. By leveraging the …

Tele-rehabilitation has garnered significant interest among clinicians and researchers with
its potential to transform cardiac rehabilitation, affecting millions of patients annually. A …

One of the main sources of the Sudden Cardiac Death (SCD) is termed as Fatal arrhythmia.
The electric shock treatment retrieves the regular electrical and mechanical functions of the …