The deep learning market in drug discovery and diagnostics offers promising opportunities, driven by rising technology adoption, significant investments, and innovative solutions in healthcare. Key ...

The field of kidney transplantation is increasingly incorporating machine learning (ML) strategies to enhance the accuracy of ...

Combining newer neural networks with older AI systems could be the secret to building an AI to match or surpass human ...

SignalHire, a leading provider in the contact intelligence space, has achieved a 96% accuracy rate through advanced machine learning algorithms and real-time verification systems. The platform ...

As Artificial Intelligence (AI) continues to reshape healthcare, one of the most compelling frontiers is emotion detection ...

The University of Twente’s BRAINS Center for Brain-Inspired Computing has developed a groundbreaking hardware-based learning method that enables electronic materials to adapt without using ...

Abstract: Parkinson’s disease (PD) is the second most common neurodegenerative disorder and is characterized by dopaminergic neuron loss and the accumulation of abnormal synuclein. PD presents both ...

An integrated intent-driven verification and distributed monitoring framework strengthens network infrastructure security by uniting real-time traffic analysis, machine learning-based threat detection ...

An intelligent AFM processing framework integrates optimized scanning trajectories, distortion correction, and deep learning segmentation to improve imaging stability, accuracy, and automation. By ...

It’s useful to think of our engagement with algorithms as a social contract. Political theorists have long used the social contract as a device to explain why individuals submit to the authority of a ...

Sasha S. Rao and Todd M. Hopfinger of Sterne, Kessler, Goldsten & Fox PLLC discuss guidance and decisions on securing patents ...

AI-assisted signal debugging has broad impact across many domains.