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This article highlights both the opportunities and challenges of using big data in dermatology, noting potential benefits like improved diagnostics and public health monitoring, alongside challenges such as data quality and AI training disparities.

This thesis presents research conducted in partial fulfillment of a Master's degree in Software Systems Engineering but does not report new empirical findings.

In this study, researchers evaluated deep learning methods for diagnosing Alopecia Areata and found that a modified Inception-Resnet-v2 model achieved a high validation accuracy of 97.94% and loss of 10.4%, suggesting it as an effective tool for classifying alopecia-affected hair.

This study suggests that artificial intelligence could significantly enhance histology education for medical and dental students, but its implementation faces challenges like cost, accuracy, and ethical considerations.

In this observational study, dutasteride treatment was associated with statistically significant stabilization of frontal fibrosing alopecia compared to other systemic therapies, with a dose-dependent effect observed across the frontal and bilateral temporal hairlines.

Among families with pediatric brain disease, this study identified over 200 novel genetic causes, revealing potential treatment points using drug repurposing or nutritional supplementation.

This article examines the emergence of predictive analytics with big data and concludes that Foucault's concept of biopower is now a hybrid involving various technologies to monitor and model behavior and risk.

This study found that Raman spectroscopy has potential for detecting biophysical differences in basal cell carcinoma compared to normal skin structures, supporting its future use in Mohs surgery.

This review discusses therapeutic principles for managing hirsutism and androgenetic alopecia during the menopausal transition and peri-/postmenopause but reports no new clinical results.

This article reviews seborrheic scalp dermatitis management in Italy, outlining expert recommendations on diagnosis and treatment, but reports no new clinical results.

In this study, researchers introduced a machine learning approach to discover new nanozymes through the DiZyme platform, enabling the accurate prediction of multiple catalytic activities, and providing a comprehensive database and assistant resources for users.

This study reports that deep learning models, particularly CNN and FCN, achieved high accuracy in diagnosing scalp and skin disorders, suggesting potential for improved diagnostic systems with further advancements.

This review explains various types of hair loss and unwanted hair growth in women, emphasizing the complexity of treatment due to their diverse causes, but it reports no new clinical results.

The abstract contains only graphic design specifications and reports no new research findings.

This study reports that keratin-based materials derived from human hair have potential for use in tissue engineering, showing promising bioactivity and mechanical support in preliminary evaluations.

This news review reports on the latest developments in lipid technology but presents no new research findings.

The document reviews various hair and nail disorders, their causes, and treatments, emphasizing the need for proper diagnosis and the link between nail changes and systemic diseases.

This article reviews a comprehensive textbook on cosmetic dermatology techniques and devices, noting its practicality and usefulness for both novice and experienced clinicians, but reports no new clinical findings.

New therapies for burn wounds show promise in reducing pain, infection risk, and improving healing and physical outcomes.

This study developed a new method for analyzing multivariate time-series data that successfully predicts website competition dynamics and outperforms conventional methods in identifying and predicting competitive structures.

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 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 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.

This source reviews the common skin-related side effects of tyrosine kinase inhibitors in treating endocrine cancers and emphasizes that proactive, multidisciplinary management can effectively control these adverse events without compromising cancer treatment efficacy.

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.