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This literature review explores the role of biomarkers in personalized medicine for various dermatological conditions like Hidradenitis Suppurativa, Psoriasis, and Atopic Dermatitis, highlighting how they guide targeted therapies and the limitations of current markers in specificity, as reported by the authors.

This study found higher serum prolactin levels in patients with psoriasis, vitiligo, and alopecia areata compared to controls, and prolactin levels correlated with disease severity in psoriasis and alopecia areata but not vitiligo.

This review summarizes current literature associating mitochondrial dysfunction with dermatologic issues like skin aging, hair loss, and poor wound healing, noting potential benefits in targeting mitochondrial components for treatments.

In this study, researchers found that differences in skin condition distribution are the main source of errors when AI algorithms classify dermatological conditions from new, previously unseen sources, and proposed steps to improve their generalizability based on available information.

This study discusses the development of AI in dermatology and cosmetology, noting its use in skin cancer diagnosis and personalized cosmetics, while highlighting uncertainties about whether recent advancements represent significant medical progress or are influenced by marketing strategies.

This narrative review explored how blue light therapy may offer therapeutic benefits for various skin disorders by affecting microbial activity and immune responses, promoting hair growth, and aiding skin rejuvenation and healing.

This review discusses ischemia-modified albumin as a potential new marker of oxidative stress in dermatological diseases but reports no new clinical findings.

In this review, several studies on Astragalus species, particularly Astragalus membranaceus, highlight their skin rejuvenating, photoprotective, antimicrobial, and wound-healing properties, though the authors note limitations due to reliance on non-human studies and short trial durations.

This study discusses the potential of advanced imaging technologies in dermatology to improve diagnostic accuracy and reduce the need for invasive procedures like biopsies, while noting significant barriers in adoption and accessibility in India due to costs and infrastructure constraints.

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.

In this study, the Tibot AI application showed high diagnostic accuracy for adnexal and pigmentary disorders and cutaneous tumors in dermatology, but was less effective for immunological disorders and infestations, suggesting the need for further dataset refinement.

This research guide explores the diverse types, functions, benefits, and considerations of home-based dermatology devices, emphasizing their convenience, cost-effectiveness, and privacy benefits, while also warning of potential risks like improper use and limited effectiveness compared to professional treatments.

In this study, analysis of FDA data revealed a substantial risk of dermatologic adverse events with aromatase inhibitors, especially anastrozole and exemestane, highlighting the importance of dermatologic monitoring during such therapies.

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.

In this study, researchers used Google Search ads to gather an open access dataset of 10,408 dermatological images from over 5,000 U.S. internet users, enhancing the diversity and representativeness of skin condition images available for research and artificial intelligence development.

This research discusses the shift in cosmetic dermatology towards integrating regenerative medicine, AI, and personalized care, highlighting their potential to improve aesthetic outcomes and skin function while considering ethical and regulatory challenges.

This article describes current advancements and future possibilities in skin imaging technology, teledermatology, and AI in dermatology, without reporting new research results.

This study suggests that while AI shows promise as a diagnostic tool for assessing disease severity in dermatology, understanding its limitations is essential before broad clinical adoption, and it identifies gaps in research that need addressing.

This review examines advancements in deep learning methods for detecting dermatological conditions from dermoscopic images, summarizing available datasets and suggesting future research directions, but reports no new results.

This review outlines the key principles and clinical applications of multimodal non-invasive skin imaging technologies, emphasizing their combined strengths in enhancing diagnosis and treatment assessment in dermatology.

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 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 discusses the transformative potential and challenges of using AI in cosmetic dermatology, highlighting how AI is enhancing diagnostics, treatment personalization, and patient satisfaction while addressing issues such as data quality and ethical concerns in order to ensure responsible and ethical implementation.

This review highlights recent advances in the design of nanocarrier systems for transdermal drug delivery, detailing their potential to improve treatment precision for dermatologic conditions despite challenges like formulation stability and scalability.

This review highlights current and future AI applications in hair restoration and diagnosis of hair disorders, including automated systems for hair detection and self-diagnosis, emphasizing the need for experts to understand their benefits and limitations.

This review discusses recent advancements in mobile technology and artificial intelligence for dermatology, offering an overview of their current applications but reports no new clinical findings.

This study used bibliometric analysis to evaluate global research on AI applications in dermatology, identifying 406 relevant papers and highlighting current priorities such as machine learning for wound progression, AI in teledermatology, and applications for skin diseases.

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.

This study reports that telogen effluvium, a reversible hair loss condition following COVID-19, is influenced by factors like stress and inflammation, but appropriate dermatological treatment can aid recovery, as highlighted by a clinical case example.

In this study, post-COVID-19 patients showed substantial multisystem symptoms six to eight months after infection compared to controls, with a higher burden in non-respiratory areas like fatigue and neurocognitive issues, despite respiratory symptoms largely resolving.