Skin cancer is one of the most dangerous forms of cancer. Skin cancer is caused by un-repaired deoxyribonucleic acid (DNA) in skin cells, which generate genetic defects or mutations on the skin. Skin cancer tends to gradually spread over other body parts, so it is more curable in initial stages, which is why it is best detected at early stages. The increasing rate of skin cancer cases, high mortality rate, and expensive medical treatment require that its symptoms be diagnosed early. Considering the seriousness of these issues, researchers have developed various early detection techniques for skin cancer. Lesion parameters such as symmetry, color, size, shape, etc. are used to detect skin cancer and to distinguish benign skin cancer from melanoma. This paper presents a detailed systematic review of deep learning techniques for the early detection of skin cancer. Research papers published in well-reputed journals, relevant to the topic of skin cancer diagnosis, were analyzed. Research findings are presented in tools, graphs, tables, techniques, and frameworks for better understanding.

Introduction: Atopic dermatitis (AD) is associated with various systemic diseases. However, its association with diabetes mellitus (DM) was discussed controversially. Few researchers reviewed the association of these two common morbid disorders. This meta-analysis aimed to assess the relationship between AD and DM. Methods: We systematically searched PubMed including Epub and ahead of print (198 articles identified) and Cochrane (13 articles) databases. The searching engine was set to include case-control, prospective and retrospective cohorts, and cross-sectional studies from the first published up to February 12, 2021. Two hundred and eleven were identified, eighteen full texts were screened; of them, six were included in the final meta-analysis. The keywords used were AD, diabetes mellitus, type 1 diabetes, and type 2 diabetes. A datasheet was used to record the author's name, year of publication, country and type of the studies, number of events, and total number in the two arms (patients and controls). Results: Out of the 211 references identified, six studies were pooled to test the association between diabetes mellitus and AD. The studies showed that AD is lower among patients with DM, odds ratio, 0.69, 95% CI, and 0.67-0.72. No heterogeneity was observed (Chi-Square, 4.12, degree of freedom (df.)= 5, and I² = 0%, P-value), 0.53 and P-value for overall effect, <0.001. The included studies were published in Europe (five) and Canada (one study) and included 162,882 patients and 12,164 events, four of the studied articles were case-control studies, one retrospective, and one cross-sectional. Conclusion: AD was lower among patients with DM compared to their counterparts without the disease. Further studies focusing on the genetic and environmental factors linking AD and diabetes are needed.

Background: Laser hair removal (LHR) is a widely used cosmetic procedure; however, misconceptions and anxiety regarding its safety and effectiveness remain common and may influence treatment decisions. Objective: The aim of this study was to assess attitudes, misconceptions, and anxiety related to LHR among adult dermatology clinic attendees in Saudi Arabia and to identify factors associated with LHR-related anxiety and knowledge levels. Methods: A cross-sectional clinic-based survey was conducted among adults in Saudi Arabia between August and December 2025 using a structured Arabic/English questionnaire. Data collected included sociodemographic characteristics, LHR-related anxiety measured on a visual analog scale (VAS), and LHR knowledge. Anxiety was analyzed as both a continuous score and a categorical variable, while knowledge was scored using an 11-item questionnaire. Associations were examined using chi-square tests, and independent predictors were assessed using multinomial logistic regression. Results: A total of 400 participants were included (mean age 24.5 ± 7.9 years; 89.5% female). Overall anxiety was low (mean VAS 2.5 ± 2.9), although 32.2% reported moderate-to-severe anxiety. Adequate knowledge was observed in 39.5% of participants. In adjusted analyses, adequate knowledge was independently associated with lower likelihood of severe anxiety. Female sex and Saudi nationality were strong predictors of higher knowledge levels. Conclusions: In this clinic-based sample, LHR-related anxiety was generally low, although misconceptions persisted in a substantial proportion of participants. Improving patient knowledge through targeted, evidence-based education may help reduce anxiety, support realistic expectations, and promote informed decision-making regarding LHR.

In this chapter, we aim to provide a detailed overview of the role of Janus Kinase (JAK) inhibitors in the management of atopic dermatitis (AD). Atopic dermatitis (AD) is a chronic inflammatory skin disorder with a huge economic and health burden. The chapter will investigate the immunopathogenesis of AD with the focus on the JAK-STAT signaling pathway. Additionally, we target to demonstrate its dysregulation and its contribution to disease progression. The chapter will importantly examine the current evidence on the efficacy and safety of both selective and non-selective JAK inhibitors based on current clinical trials. Moreover, it will discuss the practical recommendations for clinical use, monitoring approaches, and patient selection principles. Emerging data, challenges, and future research directions of the long-term safety and efficacy of JAK inhibitors in the AD treatment algorithm will also be addressed. This chapter will serve as a comprehensive resource for clinicians and researchers for the targeted therapy in atopic dermatitis.