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Heart rate (HR) estimation from photoplethysmography (PPG) signals is a key feature of modern wearable devices for health and wellness monitoring. While deep learning models show promise, their performance relies on the availability of…

The use of Convolutional Neural Networks (CNN) in natural image classification systems has produced very impressive results. Combined with the inherent nature of medical images that make them ideal for deep-learning, further application of…

The electrocardiogram (ECG) is one of the most commonly-used tools to diagnose cardiovascular disease in clinical practice. Although deep learning models have achieved very impressive success in the field of automatic ECG analysis, they…

Cardiac diseases are among the leading causes of morbidity and mortality worldwide, which requires accurate and timely diagnostic strategies. In this study, we introduce an innovative approach that combines deep learning image registration…

The electrocardiogram (ECG) is a vital tool for diagnosing heart diseases. However, many disease patterns are derived from outdated datasets and traditional stepwise algorithms with limited accuracy. This study presents a method for direct…

The state-of-the-art cardiovascular disease diagnosis techniques use machine-learning algorithms based on feature extraction and classification. In this work, in contrast to a conventional single Electrocardiogram (ECG) lead, two leads are…

Segmentation of the heart in cardiac cine MR is clinically used to quantify cardiac function. We propose a fully automatic method for segmentation and disease classification using cardiac cine MR images. A convolutional neural network (CNN)…

Pulmonary pathologies are a significant global health concern, often leading to fatal outcomes if not diagnosed and treated promptly. Chest radiography serves as a primary diagnostic tool, but the availability of experienced radiologists…

The primary aim of this paper is to comprehend, assess, and analyze the role, relevance, and efficiency of machine learning models in predicting heart disease risks using clinical data. While the importance of heart disease risk prediction…

In the cutting-edge domain of medical artificial intelligence (AI), remarkable advances have been achieved in areas such as diagnosis, prediction, and therapeutic interventions. Despite these advances, the technology for image segmentation…

Coronary Artery Disease (CAD) is one of the leading causes of death worldwide, and so it is very important to correctly diagnose patients with the disease. For medical diagnosis, machine learning is a useful tool, however features and…

An electrocardiogram (ECG) monitors the electrical activity generated by the heart and is used to detect fatal cardiovascular diseases (CVDs). Conventionally, to capture the precise electrical activity, clinical experts use multiple-lead…

In this work, a data-driven, modal decomposition method, the higher order dynamic mode decomposition (HODMD), is combined with a convolutional neural network (CNN) in order to improve the classification accuracy of several cardiac diseases…

Cardiovascular diseases are widespread among patients with chronic noncommunicable diseases and are one of the leading causes of death, including in the working age. The article presents the relevance of the development and application of…

Currently, many researchers and analysts are working toward medical diagnosis enhancement for various diseases. Heart disease is one of the common diseases that can be considered a significant cause of mortality worldwide. Early detection…

Classifying the behavior of humans or animals from videos is important in biomedical fields for understanding brain function and response to stimuli. Action recognition, classifying activities performed by one or more subjects in a trimmed…

Sudden cardiac death and arrhythmia account for a large percentage of all deaths worldwide. Electrocardiography (ECG) is the most widely used screening tool for cardiovascular diseases. Traditionally, ECG signals are classified manually,…

Studying animal locomotion improves our understanding of motor control and aids in the treatment of motor impairment. Mice are a premier model of human disease and are the model system of choice for much of basic neuroscience. High frame…

Coronary Heart Disease affects millions of people worldwide and is a well-studied area of healthcare. There are many viable and accurate methods for the diagnosis and prediction of heart disease, but they have limiting points such as…

Arrhythmia is just one of the many cardiovascular illnesses that have been extensively studied throughout the years. Using multi-lead ECG data, this research describes a deep learning (DL) pipeline technique based on convolutional neural…