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

In a significant move aimed at strengthening regulatory clarity for cancer related medical technologies, the Central Drugs ...

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 ...

For decades, Uranus and Neptune have been filed neatly into the “ice giant” drawer, shorthand for worlds built mostly from ...

A machine with a tree growing through it is tested for operation. Opinion: James Talarico might be the antidote to MAGA Christianity Ford CEO Jim Farley said Trump would halve the EV market by ending ...

Karthik Ramgopal and Daniel Hewlett discuss the evolution of AI at LinkedIn, from simple prompt chains to a sophisticated ...

Recent developments in machine learning techniques have been supported by the continuous increase in availability of high-performance computational resources and data. While large volumes of data are ...

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

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

Forests and plantations play a vital role in carbon sequestration, yet accurately monitoring their growth remains costly and labor-intensive.

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 ...