A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications ...

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and data preprocessing. If you''ve ever built a predictive model, worked on a ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Research authored by partners from the Bottle Consortium and published in Nature Communications this month aims to challenge ...

Predicting hospitalization risk among patients on hemodialysis is vital, given their high rate of unplanned hospitalizations related to fluid overload and infections.

Phishing websites remain a persistent cybersecurity threat, exploiting users by imitating trusted online services. New ...

Microelectromechanical systems (MEMS) electrothermal actuators are widely used in applications ranging from micro-optics and microfluidics to nanomaterial testing, thanks to their compact size and ...

Insulin resistance - when the body doesn't properly respond to insulin, a hormone that helps control blood glucose levels - ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...