Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

The dodo's closest living relative, the Samoan manumea, was spotted alive in the wild, after being missing for years.

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

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

The history of AI shows how setting evaluation standards fueled progress. But today's LLMs are asked to do tasks without clear benchmarks.

Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

Imagine a town with two widget merchants. Customers prefer cheaper widgets, so the merchants must compete to set the lowest price. Unhappy with their meager profits, they meet one night in a ...

Abstract: Various machine learning algorithms exist, each maintaining different assumptions about the underlying data or the function they aim to approximate. One such class of algorithms include tree ...