Retinal detachments can be diagnosed using a deep learning-powered fundus imaging system, offering expertise to screening sites.

Researchers at the Department of Energy's Oak Ridge National Laboratory have developed a deep learning algorithm that ...

Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning ...

Deep learning uses multi-layered neural networks that learn from data through predictions, error correction and parameter adjustments. It started with the ...

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...

Abstract: The success of deep learning (DL) is often achieved at the expense of large model sizes and high computational complexity during both training and post-training inferences, making it ...

ABSTRACT: Magnetic Resonance Imaging (MRI) is commonly applied to clinical diagnostics owing to its high soft-tissue contrast and lack of invasiveness. However, its sensitivity to noise, attributable ...

Economists have developed different types of models describing the interaction of agents in markets. Early models in general equilibrium theory describe agents taking prices as given and do not ...

Physiologically Based Pharmacokinetic Model to Assess the Drug-Drug-Gene Interaction Potential of Belzutifan in Combination With Cyclin-Dependent Kinase 4/6 Inhibitors A total of 14,177 patients were ...

Abstract: Recent advancements in deep neural networks heavily rely on large-scale labeled datasets. However, acquiring annotations for large datasets can be challenging due to annotation constraints.

These data were aggregated from a number of sources including the American Community Survey (https://www.census.gov), https://www.clinicaltrials.gov, and https://www.cancer.gov. Significant ...