Machine learning has emerged as a transformative approach in the design and evaluation of steel alloys, offering data-driven models that complement traditional physics-based methods. By training ...

Globally, mental disorders are a significant burden, particularly in low- and middle-income countries, with high prevalence in Rwanda, especially among survivors of the 1994 genocide against Tutsi.

Explore predictive modeling for compound prioritization, including in silico screening, toxicology models, and lead selection ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

Dynamic prediction of cancer-associated thrombosis to guide prophylactic anticoagulation. Age distribution of metastatic cancer patients and chemotherapy discontinuation rates.

Development and Validation of an 18F-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography–Based Imaging Score to Predict 12-Week Life Expectancy in Advanced Chemorefractory Colorectal ...

As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...

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 ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...