The transformative aspect of merging quantum computing with classical neural networks has been phenomenal in this fast-paced ...

The purpose of this study was to develop a method of classifying cancers to specific diagnostic categories based on their gene expression signatures using artificial neural networks (ANNs).

Radiologists who evaluate CT scans have diagnostic challenges due to the complexity of underlying anatomy and the potential ...

Concerns about AI's energy use have a lot of people looking into ways to cut down on its power requirements. Many of these focus on hardware and software approaches that are pretty straightforward ...

One notable missing feature in most ANN models is top-down feedback, i.e. projections from higher-order layers to lower-order layers in the network. Top-down feedback is ubiquitous in the brain, and ...

A research paper by scientists at Shanghai Jiao Tong University presented a novel channel-wise cumulative spike train image-driven model (cwCST-CNN ...

In a rapidly evolving digital landscape, machine learning is at the forefront of computational advancements, revolutionizing industries from healthcare to finan ...

In a small lab at Sokoine University of Agriculture in Morogoro, Tanzania, artificial intelligence is doing something unexpected—it’s not just solving problems, it’s changing lives.

A Convergence of Two Powerful Technologies, Shashank Chaudhary, a researcher at the forefront of computational science, explores the dynamic fusion of quantum computing and artificial intelligence in ...

The "Multimodal AI Market Opportunity, Growth Drivers, Industry Trend Analysis, and Forecast 2025-2034" report has been added ...

For decades, AI has run on silicon–a given that few have questioned or tried to challenge. However, one startup believes the ...

One of the most striking claims in the review is that AI-based classification models can meet or exceed the performance of ...