Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Researchers have developed a new machine-learning-assisted approach to optimize micro-electro-discharge machining (µ-EDM) of a next-generation biocompatible titanium alloy, potentially improving the ...

This study presents a bio-inspired control framework for soft robots, enhancing tracking accuracy by over 44% under disturbances while maintaining stability.

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

Explore how machine learning in insurance enhances risk assessment, fraud detection, and personalization. ✓ Subscribe for ...

Researchers at the University of Bayreuth have developed a method using artificial intelligence that can significantly speed up the calculation of liquid properties. The AI approach predicts the ...

Spirent Luma uses a multi-agent architecture and deterministic rule sets to automate root cause analysis in multi-technology network environments.

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...

Identifying vulnerabilities is good for public safety, industry, and the scientists making these models.

Background Motor and cognitive dysfunctions are common and disabling features in multiple sclerosis (MS) that remain challenging to treat. Here, we aimed to explore the effect of exergames as a ...

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...