Hosted on MSN

AI meets plasma turbulence modeling for fusion

Scientists are blending physics-informed AI with supercomputing to model plasma turbulence more accurately and efficiently. These breakthroughs could improve predictions for fusion reactors, ...
News-Medical.Net

T1GRS model enhances prediction of genetic risk for Type 1 diabetes

In people with Type 1 diabetes (T1D), the immune system shuts down the body's ability to make the hormone insulin, ...
IEEE

Comparing Text-Based Clinical Risk Prediction in Critical Care: A Note-Specific Hierarchical Network and Large Language Models

Abstract: Clinical predictive analysis is a crucial task with numerous applications and has been extensively studied using machine learning approaches. Clinical notes, a vital data source, have been ...
IEEE

Remaining Useful Life Prediction for Hybrid Systems Under Intermittent Fault Using Doubly Stochastic Process Model

Abstract: This paper proposes a stochastic process based remaining useful life (RUL) prediction method for hybrid systems in the presence of intermittent fault. The failure of an intermittently faulty ...
Hosted on MSN

Turning math into Python-powered solutions

Python isn’t just for coding—it’s a powerful ally for solving complex mathematical problems. From symbolic algebra to simulations and optimization, its libraries turn abstract concepts into practical ...
Radio World

A Class on Predicting FM Radio Signals

In my latest Signal Spot, I had my Villanova students explore machine learning techniques to see if we could accurately ...
Nature

Dozens of AI disease-prediction models were trained on dubious data

Dubious data sets are being used to train artificial-intelligence models that are designed to predict people’s risk of stroke and diabetes, researchers report in a preprint 1 on medRxiv. Some of the ...