Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.

Craif Inc. in Nagoya, Japan, working with Nagoya University's Institute of Innovation for Future Society, has developed a ...

A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...

Info-Tech Research Group has released its 2025 Machine Learning Emotional Footprint Report, which identifies the ...

From SOCs to smart cameras, AI-driven systems are transforming security from a reactive to a predictive approach. This ...

According to a new study, machine learning can reliably identify patients at high risk of early dysphagia following acute ...

A generative advertising framework integrates diffusion models, multimodal learning, and brand style embeddings to automate creative ...

This study shows that a blood-based metabolomic signature linked to maternal BMI predicts gestational diabetes and ...

Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...

The review reports that blockchain-enhanced federated learning systems typically achieve slightly lower raw accuracy than ...

Doctors treating ICU patients on ventilators face a constant challenge regarding nutrition. Now, an AI system can help.

Phase III is intended to generate meaningful biological data on potential drug compounds prioritized by YuvaBio’s classifier, ...