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 ...

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

Breast cancer is one of the major causes of female death in any part of the world, and the burden is highly ...

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 ...

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 ...

Abstract: The use of deep learning (DL) in medical image analysis has significantly improved the ability to predict lung cancer. In this study, we introduce a novel deep convolutional neural network ...