New book explains how AI and machine learning are transforming banking through fraud detection, credit risk modeling, ...

Recent advancements in machine learning have ushered in a transformative era for seismic data analysis. By integrating sophisticated algorithms such as convolutional neural networks (CNNs), generative ...

Machine learning is rapidly emerging as a pivotal tool in plant tissue culture research, offering innovative approaches to optimise protocols, predict morphogenic responses, and streamline ...

This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...

A new self-supervised machine learning model, TweetyBERT, automatically segments and classifies canary vocalizations with expert-level accuracy, offering a scalable platform for neuroscience, ...

Artificial Intelligence (AI) and Machine Learning (ML) are increasingly integral to database management, driving new levels of automation and intelligence in how data systems are administered. Modern ...

Based on these challenges, a comprehensive reassessment of how AI should be deployed in electrocatalysis has become urgently needed. Addressing this need, a review published (DOI: 10.1016/j.esci.2025.

A new machine learning model, TweetyBERT, automatically segments and classifies canary vocalizations with expert-level accuracy, offering a scalable ...

The rapid expansion of artificial intelligence initiatives across enterprise environments has given rise to a new class of ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average diagnosis time?