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

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

The innovative “fragmentomics” approach could one day allow doctors to identify cancer in patients sooner than possible today using smaller blood draws LOS ANGELES--(BUSINESS WIRE)--Researchers at ...

In a recent study published in Scientific Reports, researchers established a benchmark classification of major depressive disorder (MDD) using machine learning (ML) on cortical and subcortical ...

Objective To (1) develop and evaluate a machine learning model incorporating gait and physical activity to predict medial tibiofemoral cartilage worsening over 2 years in individuals without advanced ...

A study published in peer-reviewed American Journal of Health-System Pharmacy last month found that machine learning and advanced analytics technology can successfully identify instances of drug ...

The software tool uses self-supervised learning to detect long-term defects in solar assets weeks or years before ...

Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have developed a pioneering computational ...

Through a novel combination of machine learning and atomic force microscopy, researchers in China have unveiled the molecular ...

“With the improvement of VLSI technology, on-chip power grid design is becoming more challenging than before. In this design phase of VLSI CAD, power grids are generated in order to make power and ...