Background: Using artificial intelligence (AI) with the concept of a deep learning-based
automated computer-aided diagnosis (CAD) system has shown improved performance for …

Simple Summary The Internet of Things (IoT) uses connected devices and sensors, like high-
resolution cameras and specific sensors in wearable devices, for the collection of skin …

ABSTRACT The International Skin Imaging Collaboration (ISIC) datasets are pivotal
resources for researchers in machine learning for medical image analysis, especially in skin …

Skin cancer is a severe and potentially lethal disease, and early detection is critical for
successful treatment. Traditional procedures for diagnosing skin cancer are expensive, time …

Cancers of the skin are particularly dangerous. Skin cancer may arise due to genetic
abnormalities or mutations in DNA that are not correct. Deaths have skyrocketed due to a …

One out of three cancers now is skin cancer, a figure that has exploded in the previous
several decades. Melanoma is the worst kind of skin cancer and occurs in 4% of cases. It is …

This study introduces SkinLiTE, a lightweight supervised contrastive learning model, tailored
to enhance the detection and typification of skin lesions in dermoscopic images. The core of …

Using computer technology for automatic diagnosis of various skin lesions from
dermoscopic images has remained a challenging task up to now. Skin cancer, one of the …

Skin cancer, a pervasive threat to global health, prompts a critical need for enhanced
diagnostic accuracy Conventional methods relying on image segmentation struggle with the …

The precise identification and categorization of cutaneous lesions and melanoma are of
paramount importance in the timely discovery and successful management of these …