Metabolic-associated steatotic liver disease (MASLD) is a clinically heterogeneous condition with highly variable outcomes affecting more than 30% ...

Deep learning has been successfully applied in the field of medical diagnosis, and improving the accurate classification of ...

Although artificial intelligence (AI) has demonstrated potential in automating glaucoma screening, there is still a ...

This study presents a deep learning model for breast cancer detection, achieving 99.24% accuracy and improving clinical ...

Deep learning is a subset of machine learning that uses multi-layer neural networks to find patterns in complex, unstructured data like images, text, and audio. What sets deep learning apart is its ...

Abstract: Deep learning-based approaches to hyperspectral image analysis have attracted large attention and exhibited high performance in image classification tasks. However, deployment of deep ...

Deepfakes of Venezuela’s ousted president, Nicolás Maduro, flooded the internet after his capture, in a new collision of breaking news and artificial intelligence. By Stuart A. Thompson and Tiffany ...

This repository contains Python notebooks demonstrating image classification using Azure AutoML for Images. These notebooks provide practical examples of building computer vision models for various ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...

This study aimed to develop a hybrid deep learning model for classifying multiple fundus diseases using ultra-widefield (UWF) images, thereby improving diagnostic efficiency and accuracy while ...