Cardiovascular disease continues to be the leading cause of death worldwide. To save lives, constantly improving diagnostic ...
Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...
A deep learning model using retinal images obtained during retinopathy of prematurity (ROP) screening may be used to predict diagnosis of bronchopulmonary dysplasia (BPD) and pulmonary hypertension ...
Abstract: Artificial intelligence (AI) predictions are widely used to address challenges in the heart health sector, such as providing clinical decision support. Early detection of valvular heart ...
bCentre for Translational Bioinformatics, William Harvey Research Institute, London, UK cExperimental Medicine and Rheumatology, William Harvey Research Institute, London, UK dSchool of Infection, ...
Background: Liver disease remains a major global health burden, often progressing undetected until advanced stages. Traditional diagnostic approaches, while accurate, are invasive, costly, and limited ...
Abstract: Heart disease remains the leading cause of mortality worldwide, emphasizing the importance of early prediction, which is often challenging. This study proposes an optimized machine learning ...
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