The Epidemiological Pattern of Skin Cancer from 2011 to 2022 among the Population of the Aseer Region, Kingdom of Saudi Arabia

Alenizi F, Varzeghani AN, Asghari P, Darwesh A, Malik MH, Lee SW. A model for skin cancer using combination of ensemble learning and deep learning

Skin cancer has a significant impact on the lives of many individuals annually and is recognized as the most prevalent type of cancer. In the United States, an estimated annual incidence of approximately 3.5 million people receiving a diagnosis of skin cancer underscores its widespread prevalence. Furthermore, the prognosis for individuals afflicted with advancing stages of skin cancer experiences a substantial decline in survival rates. This paper is dedicated to aiding healthcare experts in distinguishing between benign and malignant skin cancer cases by employing a range of machine learning and deep learning techniques and different feature extractors and feature selectors to enhance the evaluation metrics. In this paper, different transfer learning models are employed as feature extractors, and to enhance the evaluation metrics, a feature selection layer is designed, which includes diverse techniques such as Univariate, Mutual Information, ANOVA, PCA, XGB, Lasso, Random Forest, and Variance. Among transfer models, DenseNet-201 was selected as the primary feature extractor to identify features from data. Subsequently, the Lasso method was applied for feature selection, utilizing diverse machine learning approaches such as MLP, XGB, RF, and NB. To optimize accuracy and precision, ensemble methods were employed to identify and enhance the best-performing models. The study provides accuracy and sensitivity rates of 87.72% and 92.15%, respectively.

Understanding the charismatic potential of nanotechnology to treat skin carcinoma

Carcinoma is a condition that continues to pose a significant challenge, despite current medical advances. Skin carcinoma is the leading cause of cancer, and it has seen a massive increase all over the world. The challenges with current treatment are due to toxicity that leads to many more skin complications. Due to this to avoid such complications by designing diverse nanoparticles as delivery carriers, nanomedicine is employed as a hub for diagnostics and therapy. Liposomes, gold nanoparticles, transferases, nanofibers, etc., can all be used as delivery nanocarriers. These nanoparticles' structures and characteristics protect the medicine from degradation and improve its stability. Surface modifying agents and procedures are employed to functionalize nanoparticles, resulting in smart delivery systems. The application of nanotechnology-based approaches systematically increases drug delivery to target cells. Skin cancer has several challenges, including a long time to diagnose early types of cancer and a slower growth rate. This review focuses on innovative skin cancer therapy techniques, focusing on nanotechnology and the challenges associated with current treatment of skin cancer.