AI makes quantum field theories computable

How can quantum field theories be best formulated on a lattice to optimally simulate them on a computer? The answer comes ...

Mapping cell development with mathematics-informed machine learning

The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions ...
Psychiatry Advisor

Accuracy of Machine Learning in Predicting CVD Risk in Bipolar Disease

Models using established cardiovascular disease risk factors had satisfactory predictive performance for 5-year CVD risk in ...
The Robot Report

4 physical AI predictions for 2026 — and beyond, from UR

Trends such as industry-specific AI and a new data economy will affect physical AI in 2026, says a Universal Robots executive ...
Heart

Anaemia and blood transfusion in cardiac surgery with infective endocarditis

Background Up to half of patients with infective endocarditis (IE) require cardiac surgery. Although anaemia is common, its ...
Scientific Research Publishing

Alamdari, S., Basiri, M., Mousavi, A. and Soofastaei, A. (2022) Application of Machine Learning Techniques to Predict Haul Truck Fuel Consumption in Open-Pit Mines. Journal of ...

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...
Frontiers

Evaluating machine learning models for stroke prediction based on clinical variables

Introduction: Stroke remains one of the leading causes of global mortality and long-term disability, driving the urgent need for accurate and early risk prediction tools. Traditional models such as ...
Frontiers

Postpartum depression risk prediction using explainable machine learning algorithms

1 Department of Science and Education, Shenyang Maternity and Child Health Hospital, Shenyang, China 2 Department of Maternal, Child and Adolescent Health, School of Public Health, Shenyang Medical ...
IEEE

Machine Learning-Enhanced Model-Based Optical Proximity Correction Framework With Convolutional Neural Network-Based Variable Threshold Method Near the Diffraction Limit

Abstract: As semiconductor manufacturing approaches the diffraction limit of lithography, traditional model-based optical proximity correction (MBOPC) techniques face accuracy bottlenecks due to ...