Machine learning holds great promise for classifying and identifying fossils, and has recently been marshaled to identify trackmakers of dinosaur ...

A signal-processing–based framework converts DNA sequences into numerical signals to identify protein-coding regions. By integrating spectral ...

Models using established cardiovascular disease risk factors had satisfactory predictive performance for 5-year CVD risk in ...

Schizophrenia is a severe and often highly debilitating psychiatric disorder characterized by distorted emotions, thinking patterns and altered perceptions of reality, as well as mental impairments.

There is often no straightforward explanation for the various types of violence that occur around the world. In fact, even when using clear definitions (such as “Civil War,” “Invasion,” or “Local ...

In a study titled Recent Applications of Machine Learning Algorithms for Pesticide Analysis in Food Samples, published in the ...

SCAN project aims to build European GNSS-based and AI-driven technologies to detect and assess roadway pavement problems.

Market growth is driven by industrial automation, predictive maintenance demand, AI/ML analytics adoption, IoT integration, and the need to reduce downtime and operational costs.Austin, Jan. 27, 2026 ...

Overview: Master deep learning with these 10 essential books blending math, code, and real-world AI applications for lasting expertise.From neural networks to N ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

The tax agency accounts for nearly half of Treasury’s AI use cases, with a heavy focus on IT and some fraud-fighting tech, ...