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This study reviews the complexities of burn-related skin complications, highlighting postburn pruritus, dyspigmentation, and the risk of malignant ulcers, while offering a framework for evidence-based management through various treatment approaches.

In this case report, a 38-year-old woman with Parry–Romberg syndrome displayed left-sided facial atrophy and subclinical central nervous system involvement detectable by neuroimaging, suggesting that even symptom-free cases may benefit from systematic brain evaluations.

This review discusses the integration of Artificial Intelligence in non-surgical cosmetic procedures, highlighting its potential to improve personalized aesthetic care and operational efficiency while addressing ethical and regulatory challenges; it presents no new clinical findings.

This study demonstrates that an AI-based grading framework using a novel area ratio metric improves the accuracy and consistency of male pattern hair loss classification, especially in advanced grades, compared to traditional methods.

This review summarizes the application of genome wide association studies and selection signature analyses in sheep and goat breeding in China, highlighting genomic regions that influence traits like reproductive performance and body size.

In this update, researchers incorporated TGA-approved Janus Kinase inhibitors into the Australian treatment guidelines for chronic, moderate to severe Alopecia areata, aiming to enhance recommended therapies by providing guidance on the use and management of these systemic medications.

This expert panel review developed consensus recommendations for managing androgenetic alopecia in Canadian adults, endorsing seven interventions like oral and topical medications and platelet-rich plasma.

In this study, machine learning-based computer-aided diagnosis significantly improved accuracy in diagnosing alopecia areata compared to traditional visual methods, achieving up to 91.9% accuracy using different classifiers like CNN, SVM, and random forest models.

This study outlines trichodynia, a painful scalp condition often linked with various types of alopecia and psychiatric disorders, noting the absence of specific treatments and highlighting the need for further research on therapeutic options.

This review explores the skin benefits of exercise and discusses how artificial intelligence can tailor exercise programs to individual skin health needs, emphasizing the potential of AI-driven strategies in cosmetic dermatology for more personalized and adaptive skincare approaches.

This review highlights evidence that exercise benefits skin health by enhancing collagen synthesis and reducing oxidative stress and discusses the potential of AI technology to personalize exercise programs, optimizing skin benefits based on individual needs and environmental factors.

Smart microneedles using advanced tech could improve psoriasis treatment.

This source reports that clinical trials using advanced Deep Brain Stimulation systems, augmented with AI to integrate kinematic data, eye tracking, and cognitive assessments, show promise in improving diagnostic accuracy and monitoring symptoms for patients with Parkinson's disease.

This abstract outlines a lecture discussing the rise of influencers alongside the internet, highlighting their impact on user behavior in social media by sharing personal experiences and engaging in political and medical discourse.

This consensus statement from Saudi Arabia outlines evidence- and experience-based recommendations for diagnosing and managing alopecia areata, focusing on severity assessment, prognostic indicators, and therapeutic options, with special attention to pediatric patients and uncommon cases.

In this case report from Cipto Mangunkusumo Hospital Jakarta, alopecia areata was identified as the most common type of baldness in the facility's skin and genital polyclinics from 2009 to 2011, representing 39.7% of cases.

This study found that tissue transcriptomics and a normalization approach can effectively cluster nine inflammatory skin diseases and identify specific biomarkers, including PTEN as a marker for cutaneous lupus erythematosus.

This study suggests that distinct alopecia scoring systems measure percent hair loss as a common underlying feature, with strong correlations observed between different types of hair loss assessments.

In this study, the researchers used machine learning techniques on an image dataset to diagnose Alopecia Areata, achieving a maximum accuracy of 98.3%.

This study identified the combination of NCBP3, SDHA, and PTPRA as stable reference genes for normalizing gene expression in goat skin tissue research.

This article discusses factors contributing to aseptic loosening of implants and explores the challenges of determining metal hypersensitivity testing in patients, but provides no new clinical results.

This study outlines a methodological approach for developing dermato-cosmetic remedies using natural raw materials that may aid in the prevention and treatment of androgenic alopecia and telogen effluvium.

This case study reported an improvement in lower limb edema for a patient with type 2 diabetes mellitus after starting dulaglutide treatment, suggesting a potential role of the drug in sodium retention disorders.

This review examines the effectiveness of current treatments for androgenetic alopecia, offering plastic surgeons evidence-based guidance for choosing safe and effective options, but reports no new results.

In this study, white females with Ludwig I female pattern hair loss had higher hair density on the occipital scalp, while Asian females had thicker hair diameters in both frontal and occipital areas.

The digital system for measuring melasma shows promise but needs more development for better accuracy and automation.

This study presents evidence suggesting that populations now categorized as Black American are the original inhabitants of the Americas, with genetic heritage and identity obscured by historical reclassification to strip sovereign rights.

This systematic review found that digital health interventions may improve quality of life for dermatology patients, especially through telemedicine, which often matched or exceeded in-person care. However, the evidence is limited by study variability and short follow-up periods.

This study developed a leakage-resistant machine learning framework for classifying hair loss types, emphasizing transparency through explainable AI. Among tested models, Extreme Gradient Boosting excelled, achieving high accuracy and stability on both cross-validation and holdout datasets.

This paper critically evaluates the role of AI in cosmetic surgery, highlighting its potential to enhance precision, tailor treatment, and improve patient outcomes, while also addressing ethical, legal, and regulatory challenges that complicate its integration into clinical practice.