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 ...

Mr. Jeremy Sameulson, EVP of AI and Innovation at IQT, publishes VEIL™ Privacy-Preserving Machine Learning Framework on arXiv: Introduces an architecture designed to enable use of sensitive data ...

A machine learning model using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD ...

Finding high-performing catalysts, which are used to accelerate processes from chemical manufacturing to energy production, ...

Researchers from several Parisian institutions have worked together to develop a non-destructive approach to study how ...

The increasing global demand for sustainable energy and carbon materials, alongside pressing environmental concerns, ...

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 ...

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

A research team at Tohoku University and Future University Hakodate has demonstrated that living biological neurons can be trained to perform a supervised temporal pattern learning task previously ...

In this digitally dominated economy, where instantaneous transactions are the order of the day for all businesses, the landscape of accounting technology has li ...

Personality tests are widely used in workplaces to shape recruitment, leadership training and team building. But what if ...