Artificial intelligence (AI) in medicine is an increasingly studied and widespread
phenomenon, applied in multiple clinical settings. Alongside its many potential advantages …

Electrocardiography (ECG), improved by artificial intelligence (AI), has become a potential
technique for the precise diagnosis and treatment of cardiovascular disorders. The …

Cardiovascular diseases (CVDs) remain a leading cause of morbidity and mortality
worldwide. Effective prevention and management strategies are essential to reduce the …

Study Objectives: Machine learning (ML) models have been employed in the setting of sleep
disorders. This review aims to summarize the existing data about the role of ML techniques …

Routinely collected electronic health records (EHRs) data contain a vast amount of valuable
information for conducting epidemiological studies. With the right tools, we can gain insights …

Objective Artificial intelligence (AI) detects heart disease from images of electrocardiograms
(ECGs). However, traditional supervised learning is limited by the need for large amounts of …

Artificial intelligence (AI) has come to play a pivotal role in revolutionizing medical practices,
particularly in the field of pancreatic cancer detection and management. As a leading cause …

This paper proposes a denoising method based on an adversarial deep learning approach
for the post-processing of multi-channel fetal electrocardiogram (ECG) signals. As it's well …

Aims The diagnostic application of artificial intelligence (AI)-based models to detect
cardiovascular diseases from electrocardiograms (ECGs) evolves, and promising results …

Contemporary methods used to interpret the electrocardiogram (ECG) signal for diagnosis
or monitoring are based on expert knowledge and rule-centered algorithms. In recent years …