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 ...

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 ...

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

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 ...

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.

Relating brain activity to behavior is an ongoing aim of neuroimaging research as it would help scientists understand how the brain begets behavior — and perhaps open new opportunities for ...

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

As agent hype fades, machine learning quietly proves it’s still essential.

Mount Sinai researchers have created an analytic tool using machine learning that can predict cardiovascular disease risk in ...