By transforming movement into data, Timothy Dunn is reshaping how scientists can study behavior and the brain.

Abstract: Employee attrition poses considerable challenges for organizations by affecting productivity and increasing recruitment costs. This study employs tree-based machine learning classifiers to ...

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

AI agents help businesses stop guessing — linking predictions to actions so teams can move from “what might happen” to ...

RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

Healthtech and edtech are two of the fastest growing sectors, with the healthtech market size to reach $3.1 billion by 2033, while the global education technology market size is projected to reach ...

Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

IMF researchers show that satellite data, especially nighttime lights combined with machine learning can reliably estimate ...

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions ...