Abstract: Alzheimer's disease (AD) is a disease of the central nervous system that manifests as dementia and other mental disorders. It's critical to correctly diagnose Alzheimer's disease as well as ...

A research team funded by the National Institutes of Health (NIH) has developed a versatile machine learning model that could one day greatly expand what medical scans can tell us about disease.

This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...

For some years now, groups, universities, organizations and authorities have developed and implemented AI for data analysis, tattoo identification, facial recognition and to give a voice to the ...

Could you briefly share your background and how you came to focus on AFM technologies within the cosmetics industry? My name is Alexander Dulebo, and I’m a Bio Sales Application Engineer at Bruker, ...

Physical AI connects algorithms to the real world. Learn how embodied systems sense, adapt, and operate beyond pure computation.

Artificial intelligence tools are helping hackers find and exploit vulnerable systems more quickly, and accelerate everything ...

Machine learning models are usually complimented for their intelligence. However, their success mostly hinges on one fundamental aspect: data labeling for machine learning. A model has to get familiar ...

A multi-institutional team of researchers led by Virginia Tech's Fralin Biomedical Research Institute at VTC has for the first time identified specific patterns of brain chemical activity that predict ...

Amazon One Medical is launching an agentic health AI assistant for use in the One Medical app. The assistant seems to be drawing on the appeal of using a consumer chatbot for round-the-clock access to ...

A research team led by the University of Sharjah in the United Arab Emirates has developed a novel machine learning approach for fault detection in bifacial PV systems. The method combines a ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...