Brain-Computer Interfaces (BCIs) are emerging as transformative tools that enable direct communication between the human brain and external devices. With recent advancements in Electroencephalography ...

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 ...

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

Researchers analyzed data from middle-aged workers who had received Specific Health Guidance -- a revolutionary system implemented by the Japanese Ministry of Health, Labor, and Welfare to improve ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

Reservoir computing is a promising machine learning-based approach for the analysis of data that changes over time, such as ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

Effect of KROS 101, a small molecule GITR ligand agonist, on T effector cells, T reg cells and intratumoral CD8 T cell cytotoxicity. Phase 1 study of DK210 (EGFR), a tumor-targeted IL2 x IL10 dual ...

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 ...

Below is a curated list of machine learning development providers that stand out in 2026 for their ability to build enterprise-grade ML solutions tailored to complex business environments.