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 ...

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 ...

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 factors contributing to driving under the influence, according to a new analysis ...

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 ...

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

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 ...

AI-powered polarized retinal imaging detects protein deposits linked to neurodegenerative diseases, distinguishing Alzheimer’s from ALS and related disorders with high accuracy, enabling earlier ...

An environmental reporter joins a research team trying to attach recording devices to sperm whales, in hopes of decoding their calls.

AI is rapidly reshaping the landscape of surgical oncology. However, its true potential lies not in isolated tools, but rather ...

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 ...