Adnan and colleagues evaluated machine learning models’ ability to screen for Parkinson’s disease using self-recorded smile videos. 2. The models achieved high sensitivity and specificity among ...

Abstract: Credit card fraud detection presents a significant challenge due to the extreme class imbalance in transaction datasets. Traditional machine learning models struggle to achieve high recall ...

For years, the artificial intelligence industry has followed a simple, brutal rule: bigger is better. We trained models on ...

Quantum computing has moved from physics labs into boardroom slide decks, promising to crack problems that leave even the ...

Pharmaceutical Separation Science Session Day two of HPLC 2025 concluded with a session on pharmaceutical separations chaired ...

The progression of glaucoma was accurately predicted by machine learning models based on structural, functional and vascular biomarkers, including those from OCT angiography, according to data ...

A newly developed artificial intelligence (AI) model is highly accurate in predicting blood loss in patients undergoing high-volume liposuction, reports a study in the January issue of Plastic and ...

Manufacturing technologies have been the first domain to experience this transformation. The review documents how artificial ...

The strong role of socioeconomic factors underscores the limits of purely spatial or technical solutions. While predictive models can identify where risk concentrates, addressing why it does so ...

Reverse Logistics, Artificial Intelligence, Circular Economy, Supply Chain Management, Sustainability, Machine Learning Share and Cite: Waditwar, P. (2026) De-Risking Returns: How AI Can Reinvent Big ...

A newly developed artificial intelligence (AI) model is highly accurate in predicting blood loss in patients undergoing ...

How AI-driven admission and discharge prediction can help emergency departments improve throughput, reduce delays, and ...