Atherosclerosis is a chronic inflammatory disease of the arterial wall, characterized by the
formation of plaques containing lipid, connective tissue and immune cells in the intima of …

Causal machine learning (ML) offers flexible, data-driven methods for predicting treatment
outcomes including efficacy and toxicity, thereby supporting the assessment and safety of …

Electrocardiogram (ECG) signal is a measure of the heart's electrical activity. Recently, ECG
detection and classification have benefited from the use of computer-aided systems by …

Cardiovascular disease (CVD) is the principal cause of mortality and morbidity globally. With
the pressures for improved care and translation of the latest medical advances and …

Wearable devices, such as smartwatches and activity trackers, are commonly used by
patients in their everyday lives to manage their health and well-being. These devices collect …

Cardiovascular disease is difficult to detect due to several risk factors, including high blood
pressure, cholesterol, and an abnormal pulse rate. Accurate decision‐making and optimal …

Heart disease is one the leading causes of death globally, making the early detection of it
crucial. Emerging technologies such as machine learning and deep learning are now being …

Abstract Background Coronavirus disease 2019 (COVID-19) is still ongoing spreading
globally, machine learning techniques were used in disease diagnosis and to predict …

Unfair behaviors of Machine Learning (ML) software have garnered increasing attention and
concern among software engineers. To tackle this issue, extensive research has been …

Developments in technology facilitate the use of machine learning methods in medical
fields. In cancer research, the combination of machine learning tools and gene expression …