Meta wants us to believe there’s a difference between addiction and ‘problematic use.’ The harm to kids suggests otherwise ...
Neuromorphic computers modeled after the human brain can now solve the complex equations behind physics simulations — something once thought possible only with energy-hungry supercomputers. The ...
Optokinetic Nystagmus (OKN) is a natural reflexive eye movement in oculomotor studies, reflecting the health status of the ...
Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...
By transforming movement into data, Timothy Dunn is reshaping how scientists can study behavior and the brain.
Researchers at the University of Bayreuth have developed a method using artificial intelligence that can significantly speed up the calculation of liquid properties. The AI approach predicts the ...
Non-terrestrial networks have their own challenges that cellular networks didn't have. Will AI help solve them dynamically?
The small and complicated features of TSVs give rise to different defect types. Defects can form during any of the TSV ...
A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
In 1930, a young physicist named Carl D. Anderson was tasked by his mentor with measuring the energies of cosmic ...
Machine learning requires humans to manually label features while deep learning automatically learns features directly from raw data. ML uses traditional algorithms like decision tress, SVM, etc., ...
Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
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