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This study reviews AI's role in aesthetic medicine, noting it enhances diagnostic accuracy and personalized treatment planning, but faces challenges like ethical concerns, algorithmic biases, and regulatory issues that need addressing for successful integration.

This study introduces a novel method for capturing and digitally rendering the color appearance of physical hair samples using deep neural networks.

This review highlights the potential of transcranial photobiomodulation (tPBM) as a non-invasive and affordable treatment for brain diseases, summarizing recent advances and successful protocols based on over two decades of research.

In this study, researchers used computational modeling and virtual screening to identify two FDA-approved drugs, Tadalafil and Finasteride, that may effectively inhibit key proteins involved in melanoma progression, suggesting potential for new therapeutic strategies against aggressive melanoma.

This paper reviews advancements in 3D human skin models using bioprinting, organoid, and organ-on-a-chip technologies, noting improvements in physiological realism through vascularization and multi-omics data, but also highlighting challenges such as cost and lack of standardization that hinder clinical adoption.

This review highlights the potential of microfluidic skin-on-a-chip models in skin research, emphasizing their ability to mimic human skin structure and improve control over cellular and molecular distribution compared to traditional in vitro models.

In this study, researchers developed a method to automatically detect androgen receptor nuclear translocation in dermal papilla cells using fluorescence markers and image analysis, finding that the receptor's nuclear signal peaks about 20 minutes after DHT exposure.

In this case report, researchers described a patient with Cushing's Disease exhibiting no detectable mass, where Metyrapone therapy was effectively used to manage symptoms, suggesting a treatment option for similar diagnostic challenges.

This study developed a follicular automaton model that simulates human hair cycle dynamics and can replicate hair pattern changes associated with diffuse or androgenetic alopecia.

This study suggests that cepharanthine may play an important role in treating SARS-CoV-2 infection by targeting multiple pathways and related targets associated with COVID-19.

This study used a new statistical approach, PLACO, to identify several novel shared genetic regions associated with both Type 2 Diabetes and Prostate Cancer in two large GWAS datasets.

This review introduces a framework to integrate bioinspired conductive materials and advanced 3D/4D printing in regenerative medicine for dynamic, responsive tissue regeneration, emphasizing the potential of smart scaffolds to adapt to physiological cues.

This systematic review provides an in-depth evaluation of non-invasive imaging and biophysical methods for diagnosing and monitoring vitiligo, emphasizing the need for studies with larger sample sizes to verify their use in clinical practice and research.

This study introduces Cell Journey, a new platform for visualizing RNA velocity in 3D, which aims to better capture complex cellular transitions in single-cell datasets compared to current 2D methods.

This case report describes a Japanese man with severe COVID-19 who regained independence and returned to work after undergoing rehabilitation therapy, highlighting its potential benefits for recovery.

This article discusses the dynamics of the "mole gaze" and cybersexism on the Web, analyzing interactions through personal and theoretical lenses, and suggests the need for both structural and psychological change to counteract these issues.

This study observed that using the Fisher score feature selection approach with capsule network models led to a promising 94% accuracy in diabetes detection, indicating its potential as a diagnostic tool.

This review reports that while deep learning shows promise in diagnosing scalp disorders from images, challenges remain with data quality and model interpretability, suggesting that integrating explainable AI techniques is crucial for building trust and facilitating clinical adoption.

This article discusses the use of low-level laser therapy for hair regrowth in men and women but reports no new clinical results; it reviews types of lasers and evidence from animal and human studies.

This study introduced an innovative metric for assessing college students' mental health, incorporating temporal perception and a hybrid clustering algorithm, and found it achieved over 90% accuracy, outperforming existing methods in evaluating mental health during public health challenges.

This study used artificial neural networks to predict hair loss by analyzing factors like gender and zinc deficiency, suggesting neural networks may effectively model hair loss prediction.

This review explores the complex interrelationships among different properties of natural hair fibers and underscores the need for a holistic taxonomy to improve data interpretation across disciplines, but it reports no new experimental results.

This research elucidates the molecular mechanisms underlying carbamazepine and griseofulvin's inclusion complex channel formations with polymers, revealing why carbamazepine forms stable channels independently, while griseofulvin requires polymeric support due to weaker interactions.

This study presents a new approach to automatically remove hair artifacts from dermoscopic images, which reportedly performed well compared to existing methods like DullRazor using the PH2 datasets.

This study developed a new neural network model (AA-GAN-AB-MTEDeep) to enhance Alopecia Areata classification using synthetic scalp images, achieving an accuracy of 96.94%.

In this study, researchers demonstrated that treating platelet rich plasma with microsecond pulsed electric fields effectively activates platelets and induces similar or higher growth factor release compared to traditional bovine thrombin, suggesting a potential clinical use that may be more cost-effective and practical.

This study found that all four evaluated large language models generated a significant proportion of inappropriate responses when prompted with or without LGBTQIA+ identity terms, with more severe bias observed in prompts mentioning LGBTQIA+ identities.

This review examines the reliance on formalized and automated protocols in fields like aviation and medicine, suggesting that such approaches may hinder the human capability of mètis needed to handle emergencies and dynamic ambiguities; it reports no new results.

This study found that in a sample of girls and adolescents aged 15–24 years, the prevalence of PCOS was 22.5% according to the Rotterdam criteria.

The document listed various medical job opportunities with competitive benefits and living conditions.