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This case report links sorafenib treatment in a 22-year-old man with relapsed acute myeloid leukemia to a rare instance of drug-induced pityriasis rubra pilaris-like eruption.

This book review examines various classification and treatment methods for acne scars, emphasizing the complexity and need for multiple therapeutic approaches, but reports no new clinical results.

In this case report, a 35-year-old man developed avascular necrosis after receiving intradermal corticosteroid injections for alopecia areata, marking the first documented instance of this side effect from such treatment.

This study observed that using the LMNN algorithm improved diagnostic accuracy in identifying biomarker correlations associated with hair loss, suggesting potential for advanced automated diagnostics.

This study found that women with post-COVID alopecia showed a diffuse telogen effluvium pattern and distinct trace element imbalances, such as reduced copper and increased selenium levels, helping differentiate this condition from androgenetic alopecia.

This study found that an automated tumor-infiltrating lymphocyte classification algorithm identified thin melanomas with less immune response, which were associated with higher mortality compared to other cases in the study.

This study employed multiple linear regressions to analyze hydantoin analogues and produced a model with strong predictive abilities for designing new androgen receptor modulators.

This study found that topical Vorinostat induced significant hair regrowth in mice with alopecia areata, suggesting it as a potential repurposable treatment for the condition.

This review found that AI in dermatology shows high diagnostic accuracy comparable to experienced clinicians, but integration into clinical practice faces challenges requiring further research.

This study identified distinct myeloid subsets in the scalp of men with androgenetic alopecia, potentially revealing new drug targets for treatment.

This study found that Mueller Matrix microscopy can accurately identify, detect, and evaluate hair follicles in mouse skin tissue, suggesting its potential for skin structure research and dermatological applications.

This case report describes a non-arteritic anterior ischemic optic neuropathy that resolved after discontinuing topical 5% minoxidil treatment.

This review examines the use of computer vision techniques, specifically deep learning architectures and image processing algorithms, for detecting and assessing skin conditions like vitiligo and dermatitis, and highlights the need for disease-specific datasets to improve automated diagnostic tools in dermatology.

This study reports that an Explainable AI-based hair health prediction system using a novel hybrid model outperformed traditional machine learning methods, achieving high accuracy in predicting key factors and providing personalized recommendations.

This review discusses the dermatologic manifestations and management of polycystic ovary syndrome, underscoring the need for mechanism-based, personalized treatments and integrated mental health support, but reports no new clinical results.

This review assesses the potential of smart dressings, engineered to respond to various stimuli, as advanced treatments for chronic inflammatory skin diseases by examining their activation mechanisms and proposing future developments like integrating AI and closed-loop monitoring for adaptive therapy.

This study found that a new FAW-FS algorithm improved recognition of depression in patients with androgenic alopecia, and comprehensive psychological interventions positively impacted their rehabilitation outcomes.

This paper introduces an algorithm for using smart device-mounted microscopes to analyze scalp images and diagnose hair loss by extracting specific hair loss features.

This study presented a new algorithm and camera-based system that successfully reconstruct high-quality, 3D representations of facial hair and underlying skin surfaces even in dense regions like eyebrows.

This study developed an algorithm for predicting the impact of innovations on economic growth and reported its potential to enhance innovation policy decisions.

This study presents an algorithm that may help physicians diagnose female hair loss by synthesizing patient history, clinical examination, and various diagnostic tests.

This consensus statement outlines a treatment algorithm for alopecia areata, discussing when to consider systemic treatment and how to assess outcomes, without providing new clinical results.

This review discusses the development of an algorithmic guideline for treating androgenetic alopecia in Asian patients, using the BASP classification to address limitations of previous guidelines, and reports no clinical results.

This review presents an evidence-based algorithm for managing hidradenitis suppurativa in primary care, highlighting the need for more research on treatment effectiveness and the disease's pathogenesis.

This article presents a computer imaging algorithm that may automate and enhance the Severity of Alopecia Tool scoring for alopecia areata through texture analysis of pediatric images.

This study demonstrated that an automated algorithm can effectively track epithelial cell movement within clusters, revealing that partial knockdown of E-cadherin reduces electrotactic potential in breast epithelial cells, particularly in free-moving clusters, and suggesting an adhesion-independent role of E-cadherin in regulating cell electrotaxis.

This consensus statement outlines a treatment algorithm for alopecia areata, detailing systemic treatment indications and options, including EMA-approved medications baricitinib and ritlecitinib for severe cases, as well as other off-label treatments and adjuvant therapies like oral minoxidil.

This study developed and tested a new algorithm for analyzing coat and skin coloration in laboratory animals, using digital images and hierarchical color clustering, which effectively quantified color proportions and tracked changes over time without specialized software.

This review outlines a basic diagnostic algorithm to help pediatricians identify causes of hair loss in children, emphasizing early diagnosis and treatment due to the significant psychosocial impact of conditions like alopecia areata and tinea capitis.

This study introduces diagnostic and therapeutic algorithms tailored for tailored management of alopecia areata based on patient-specific factors like age, disease severity, and quality of life.