Advancements in deep learning and computer vision provide promising solutions for
medical image analysis, potentially improving healthcare and patient outcomes. However …

A substantial body of research has been published in artificial intelligence due to the rising
incidence of skin cancer, the scarcity of specialized healthcare professionals, and rapid …

Early detection of skin cancer from skin lesion images using visual inspection can be
challenging. In recent years, research in applying deep learning models to assist in the …

Our goal is to construct a high-performance model that generates two types of fundus
disease images for both Diabetic Retinopathy (DR) and Age-Related Macular degeneration …

Purpose Human perception and decisions are biased toward previously seen stimuli. This
phenomenon is known as serial dependence and has been extensively studied for the last …

Even if more and more high-quality public datasets are available, one of the biggest
problems with deep learning for skin lesion diagnosis is still the paucity of training samples …

Deep learning-based diagnostic system has demonstrated potential in classifying skin
cancer conditions when labeled training example are abundant. However, skin lesion …

Early detection of whether a wound is a" healer" or a" non-healer" using image analysis
enables healthcare professionals to administer appropriate interventions. We propose a few …

Identification of skin diseases and treating it accordingly is one of the recent research areas
that is being worked upon and every improvement in it is beneficial for the mankind. This …

Inadequate skin type diversity, leading to racial bias, is a widespread problem in datasets
involving human skin. For example, skin lesion datasets used for training deep learning …