Frontiers

Physics-Grounded Machine Learning Force Fields for Biomolecular Modelling: Variational, Renormalization and Effective Field Theory Approaches

Machine learning is rapidly reshaping how we model molecules, and a growing body of work suggests that neural networks are not merely statistical ...
EurekAlert!

IOP Publishing launches series of open access journals dedicated to machine learning and artificial intelligence for the sciences

IOP Publishing (IOPP) is launching the world’s first series of open access journals dedicated to the application and development of machine learning (ML) and artificial intelligence (AI) for the ...
BMJ

Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis

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 ...
Nature

Machine Learning Approaches for Construction Cost Estimation

Machine learning techniques are transforming the practice of estimating construction costs by automating pattern recognition in historical project data, improving accuracy, and quantifying uncertainty ...
Phys.org

Machine learning helps solve a central problem of quantum chemistry

Within the STRUCTURES Cluster of Excellence, two research teams at the Interdisciplinary Center for Scientific Computing (IWR) have refined a computing process, long held to be unreliable, such that ...
ascopubs.org

Predicting therapeutic clinical trial enrollment for underrepresented patients in neuro-oncology using supervised machine learning.

The impacts of area-level social deprivation on overall survival in patients receiving immune-checkpoint inhibitors (ICI) treatments: A retrospective cohort study.