Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...
Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of uncertainty. Researchers have developed a lightweight machine learning framework that ...
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Physical function metrics improve mortality prediction in elderly heart failure patients
Current models of mortality risk after heart failure (HF) rely primarily on cardiac-specific clinical variables and may ...
RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...
The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...
New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...
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