Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Recent advances in machine learning have opened transformative avenues for investigating complex problems in string theory and geometry. By integrating sophisticated algorithms with theoretical ...

Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries? Theoretical ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...

To create their contactless approach, the researchers created a machine learning algorithm capable of analyzing aspects of ...

Catalog description: Presents the underlying theory behind machine learning in proofs-based format. Answers fundamental questions about what learning means and what can be learned via formal models of ...

Scientific knowledge advances through the interplay of empiricism and theory. Empirical observations of environmental ...

Overview Machine learning offers efficiency at scale, but trust depends on understanding how decisions are madeAs machine ...