Researchers report that the integration of machine learning and Internet of Things (IoT) technologies is enabling a new generation of intelligent industrial environments capable of real-time ...

Machine learning algorithms may accurately predict inborn errors of immunity (IEI) in children with persistently low serum IgE.

A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine ...

The frequency of substance use, early age of initiation, and cannabis-related memory impairments are among the primary ...

The battlefield is no longer just a physical space of troops and artillery; it is a vast, invisible network of data, sensors, and machine learning models. In the current Iran-Israel conflict, AI is ...

The use of machine learning (ML) and artificial intelligence (AI) in power converters represents the latest development in ...

Dr. Melanie Campbell and graduate student Lyndsy Acheson study an image of a retina. They are looking for protein deposits found in association with brain diseases, such as Alzheimer's, FTLD-TDP and ...

Traditional lending relies on collateral and a financial history that productive smallholder farmers may find difficult to ...

Reported accuracies were 86% (Random Forest) and 96% (convolutional neural networks), positioning retinal imaging as a candidate scalable tool for underserved populations. AI-powered polarized-light ...

A retinal image could help doctors quickly distinguish between similar neurodegenerative diseases such as ALS and Alzheimer's disease, and with ...

Researchers develop a 96% accurate AI-powered retinal scan to distinguish between Alzheimer’s and ALS by detecting specific ...

AI-powered polarized retinal imaging detects protein deposits linked to neurodegenerative diseases, distinguishing ...