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

Read more about how machine learning and deep learning differ, where each is used, and how businesses choose between them in ...

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 ...

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 ...

After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, researchers organized them into a 'periodic table of machine learning' that can help scientists ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

Zero knowledge proofs enhance transparency while maintaining confidentiality in decision-making processes. Lagrange is ...

Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has ...