This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...

LCGC International’s interview series on the evolving role of artificial intelligence (AI)/machine learning (ML) in separation science continues with Boudewijn Hollebrands from Unilever Foods R&D, ...

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 ...

Recent advances in machine learning have significantly enhanced the diagnosis and prediction of thyroid diseases. By integrating diverse algorithms including ensemble methods, neural networks, and ...

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 ...

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 ...

A new review highlights how machine learning is transforming the way scientists detect and measure organic pollutants in the ...

Statistical insights into machine learning analysis can help researchers evaluate model performance and may even provide new physical understanding.

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

A new technical paper titled “Estimating Voltage Drop: Models, Features and Data Representation Towards a Neural Surrogate” was published by researchers at KTH Royal Institute of Technology and ...

Reservoir computing is a promising machine learning-based approach for the analysis of data that changes over time, such as weather patterns, recorded speech or stock market trends. Classical ...