Anomaly detection (AD) plays a crucial role in various domains, including cybersecurity,
finance, and healthcare, by identifying patterns or events that deviate from normal …

The use of machine learning in biomedical research has surged in recent years thanks to
advances in devices and artificial intelligence. Our aim is to expand this body of knowledge …

Background and objectives Detection and classification of heart murmur using mobile-
phone-collected sound is an emerging approach to the scale-up screening of valvular heart …

Arrhythmia is a major cardiac abnormality in fetuses. Therefore, early diagnosis of
arrhythmia is clinically crucial. Pulsed-wave Doppler ultrasound is a commonly used …

One among the major causes of death in the country is Heart disease (HD). 17.3 million
deaths per year are caused by cardiac diseases, which is the primary reason for death in the …

Diagnostic methods for cardiovascular disease diagnosis based on heart sound
classification have been widely investigated for their noninvasiveness, low-cost, and high …

Objective To develop a deep learning algorithm to perform multi-class classification of
normal pediatric heart sounds, innocent murmurs, and pathologic murmurs. Methods We …

This study focuses on an artificial neural network (ANN) model for classifying pavement
types using acoustic and image data. While conventional studies often use road-surface …

Heart sound segmentation has been shown to improve the performance of artificial
intelligence (AI)-based auscultation decision support systems increasingly viewed as a …

This work investigates whether inclusion of the low-frequency components of heart sounds
can increase the accuracy, sensitivity and specificity of diagnosis of cardiovascular …