Nature

Achieving interpretable machine learning by functional decomposition of black-box models into explainable predictor effects

Machine learning (ML) has increased greatly in both popularity and significance, driven by an increase in methods, computing power and data availability 1, making it an useful tool in the development ...
Medical Xpress

Integrating machine learning with statistical methods enhances disease risk prediction models

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...
Nature

Predictive optimization of curcumin nanocomposites using hybrid machine learning and physics informed modeling

The aim of the current research was to develop a hybrid computational model that involves the integration of Machine Learning (ML) with Physics-Informed Neural Networks (PINNs) to predict and maximize ...
InsuranceNewsNet

New Machine Learning Study Findings Reported from Youngstown State University (Machine Learning and Frequency-Severity Decomposition for Insurance Pricing): Machine Learning

By a News Reporter-Staff News Editor at Insurance Daily News-- Current study results on artificial intelligence have been published. According to news reporting out of Youngstown, Ohio, by NewsRx ...
EurekAlert!

Machine learning-assisted metal additive manufacturing forming: a review

Machine learning-assisted metal additive manufacturing has been widely applied in performance optimization and control, such as process parameter optimization, structural optimization of formed parts, ...