Researchers have developed a hybrid CFD-neural network model for predicting TAIs in hydrogen-fueled turbines, improving ...

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...

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 ...

Combining microscopy and machine-learning techniques leads to faster, more precise analyses of critical coating materials ...

A research team has developed a new hybrid artificial intelligence framework that can accurately estimate leaf nitrogen ...

Background Although chest X-rays (CXRs) are widely used, diagnosing mitral stenosis (MS) based solely on CXR findings remains ...

This study reviews recent advances in ultrasonic cement bond quality evaluation and proposes a unified framework for enhanced signal processing in ...

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 ...

BullFrog AI Holdings, Inc. (NASDAQ: BFRG; BFRGW) ("BullFrog AI" or the "Company"), a technology-enabled drug development company using artificial ...

Applied Digital stock is up big because of demand for its AI data centers. Lease agreements with CoreWeave and another hyperscaler are worth approximately $16 billion over the next 15 years. Data ...

Today, the plastics industry stands at the threshold of a technological revolution, with artificial intelligence and machine learning poised to transform everything from material development to ...