Current models of mortality risk after heart failure (HF) rely primarily on cardiac-specific clinical variables and may ...
Juntendo University researchers have trained a machine learning algorithm to use clinical information and physical function ...
Abstract: The major contributor to global mortality is cardiovascular disease, posing a formidable challenge to the global healthcare system. Heart disease often develops and progresses without ...
Background Machine Learning (ML) has been transformative in healthcare, enabling more precise diagnostics, personalised treatment regimens and enhanced patient care. In cardiology, ML plays a crucial ...
When infectious diseases surge, response often comes down to timing: whether communities can position the right people and supplies before case counts spike. A new tool developed by UC San Diego with ...
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 ...
Changes to land use can directly heighten the risk of diseases spreading from animals to humans, new University of Stirling–led research has shown. The study, led by Dr. Adam Fell of the University's ...
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 ...
Ms. Scanlon is the author of “In This Economy? How Money & Markets Really Work” and Kyla’s Newsletter. Prediction markets have exploded into mainstream American life. Platforms like Polymarket and ...
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