Responsible AI involves designing machine learning systems that are transparent, fair, and accountable. In the context of healthcare, responsible AI also includes protecting patient privacy, ensuring ...

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.

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

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

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 ...

Objective To estimate the prevalence of potential overtreatment of type 2 diabetes mellitus (T2DM) among older adults and to develop and compare predictive models to identify patient and physician ...

This article digs into how machine learning (ML) and artificial intelligence (AI) contribute to the optimization of green ...

A Lightweight Self-Supervised Representation Learning Framework for Depression Risk Profiling from Synthetic Daily ...

Reported accuracies were 86% (Random Forest) and 96% (convolutional neural networks), positioning retinal imaging as a ...

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

A retinal image could help doctors quickly distinguish between similar neurodegenerative diseases, such as ALS and Alzheimer's disease, and with remarkable accuracy, according to new research ...