An AI-powered model developed at University of Michigan can read a brain MRI and diagnose a person in seconds, a study suggests.
Severe bleeding is one of the most common and preventable causes of death after traumatic injury, yet currently available tools have poor ability to determine which patients urgently need blood ...
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 ...
Abstract: Chronic Kidney Disease (CKD) is a serious health condition that progresses silently, often going undiagnosed until it reaches critical stages. Early detection is vital, but traditional ...
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 ...
Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global population. It is characterized by a persistent low mood, disruptions in typical ...
bCentre for Translational Bioinformatics, William Harvey Research Institute, London, UK cExperimental Medicine and Rheumatology, William Harvey Research Institute, London, UK dSchool of Infection, ...
The final, formatted version of the article will be published soon. Accurate and timely heart disease diagnosis through intelligent ECG signal processing is essential to reducing death rates and ...
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 ...
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