In a recent paper, SFI Complexity Postdoctoral Fellow Yuanzhao Zhang and co-author William Gilpin show that a deceptively ...

In data analysis, time series forecasting relies on various machine learning algorithms, each with its own strengths. However, we will talk about two of the most used ones. Long Short-Term Memory ...

Researchers at The University of Manchester have created a physics‑informed machine‑learning model that can run molecular ...

A new study published in Genome Research presents an interpretable artificial intelligence framework that improves both the accuracy and transparency of genomic prediction, a key challenge in fields ...

A mathematics professor at The University of Manchester has developed a novel machine-learning method to detect sudden changes in fluid behaviour, improving speed and cost of identifying these ...

By bringing the training of ML models to users, organizations can advance their AI ambitions while maintaining data security.

The landscape of artificial intelligence and machine learning is undergoing a seismic shift in early 2026. As we move beyond the era of simple text prediction and generative chatbots, a new paradigm ...

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

Head and neck cancers represent a biologically heterogeneous group of malignancies requiring accurate diagnosis, staging, and risk stratification for ...

AI-driven interventions reduce the odds of hospitalization within 7 days by 8% in patients with end-stage kidney disease receiving hemodialysis, according to a recent study.