Simple Summary The proposed research aims to provide a deep insight into the deep
learning and machine learning techniques used for diagnosing skin cancer. While …

Clinical examination is critical for the diagnosis and identification of response to treatment. It
is fortunate that technologies are continuing to evolve, enabling augmentation of classical …

Background Previous studies of artificial intelligence (AI) applied to dermatology have
shown AI to have higher diagnostic classification accuracy than expert dermatologists; …

Skin cancer is one of the major types of cancer with an increasing incidence in recent
decades. The source of skin cancer arises in various dermatologic disorders. Skin cancer is …

Efficient skin cancer detection using images is a challenging task in the healthcare domain.
In today's medical practices, skin cancer detection is a time-consuming procedure that may …

Skin cancer is being a most deadly type of cancers which have grown extensively worldwide
from the last decade. For an accurate detection and classification of melanoma, several …

AI image classification algorithms have shown promising results when applied to skin
cancer detection. Most public skin cancer image datasets are comprised of dermoscopic …

Simple Summary Skin tumors are appearing with increasing frequency worldwide. To face
this health problem, new technologies and devices have been developed in recent years …

This article presents a highly sensitive gold/Ti 3 C 2 T x coated photonic crystal fiber (PCF)-
based surface plasmon resonance (SPR) sensor for cancer cells detection. The hybrid …

Dermoscopy is increasingly used by clinicians (dermatologists, family physicians,
podiatrists, doctors of osteopathic medicine, etc) to inform clinical management decisions …