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This study proposed and tested an Ensemble Pre-Learned Deep Learning and Optimized Long Short-Term Memory (EPL-OLSTM) model for classifying Alopecia Areata, achieving a 93.1% accuracy in differentiating healthy from varying severity levels of AA scalp hair using specific datasets.

This review outlines current European legislation and manufacturing standards for platelet-rich plasma (PRP) products and provides guidance for clinicians implementing autologous PRP treatments, without reporting new clinical results.

This scoping review describes the current use of artificial intelligence in alopecia research, highlighting AI's evolution from diagnostic to prognostic applications in dermatology and identifying gaps in multimodal integration and fairness across demographics.

This review outlines a diagnostic framework for clinicians to distinguish different types of inherited ichthyoses and suggests further testing and treatment strategies, but reports no new clinical results.

This study found that paracellular transport significantly contributes to the intestinal permeability of minoxidil, suggesting its limited suitability as a Biopharmaceutics Classification System reference drug due to potential variability.

This review explores advancements in bioprinting technologies for developing in vitro skin models that replicate immune-mediated skin diseases, highlighting their potential to reduce animal testing and enhance research and product testing capabilities in dermatology.

In this study, researchers developed a deep learning model that efficiently classifies five degrees of harm with high accuracy, achieving up to 98% precision, recall, and F1-score across various harm levels, indicating strong potential for practical application in automated harm evaluation.

This review provides a framework for diagnosing acquired scalp alopecias and discusses both non-scarring and scarring types, but reports no new clinical results.

This article describes a framework for evaluating new health technologies by integrating quantitative evidence with qualitative assessments and using precedents to guide policy decisions, without reporting new clinical results.

This article discusses the classification of acne lesions and emphasizes the importance of evidence-based treatment and nursing care, without presenting new research results.

This study defines classification criteria for hair follicle dystrophy using a mouse model of chemotherapy-induced alopecia, providing tools for standardized hair damage assessment.

This article provides a framework for understanding hair disorders and treatment options in transgender individuals undergoing hormonal therapy and reports no new clinical results.

This review discusses the classification and regulation challenges of anti-ageing cosmetics in Europe and reports no new findings; it calls for increased transparency to help consumers make informed choices.

This study introduces PROMETHEUS, a framework that organizes causal claims from scientific texts into navigable and persistent "causal atlases," enhancing research by highlighting localized evidence, agreement, and contradictions within complex data sets.

This study experimentally validated Lockhart's viscoplastic framework for tip growth in Arabidopsis root hairs by demonstrating alignment with observed growth rates and estimating yield turgor pressure and cell wall viscosity, offering a methodology adaptable to other species and conditions.

This study demonstrates that a proposed multi-stage framework improves the accuracy and faithfulness of drug-related responses generated by language models, compared to traditional methods.

This review outlines the current regulatory framework for cosmetics under the FD&C Act, highlighting that they are less strictly regulated than drugs, but notes potential future changes due to proposed legislations requiring stronger safety measures.

This review proposes an anatomy-based framework for understanding recipient site scalp necrosis in hair transplantation, emphasizing regional vascular vulnerability and surgical factors, but does not provide new clinical results.

This paper argues that both the modern biomedical model and existing supplementary frameworks fail to adequately capture the complexities of empathy and healing within the context of postmodern thinking.

This study introduced ElixirSeeker2, a computational framework for designing anti-aging peptides, and found that some newly identified peptides significantly delayed cellular senescence and enhanced cellular and locomotor functions in aged Caenorhabditis elegans.

This study reported that the PM-DBiGRU model enhances aspect-level sentiment classification in drug reviews, outperforming existing methods on the newly proposed SentiDrugs dataset.

This review examines psychosomatic hair diseases, discussing their classification, implications, and the need for tailored psychosomatic therapy, without reporting new clinical results.

This paper reviews seven major systemic causes of hair loss and provides a clinical evaluation framework but reports no new experimental results.

In this study, researchers developed a novel computational framework using deep reinforcement learning to identify strategies for cellular reprogramming in gene regulatory networks, showing its effectiveness in a model of immune response against infection.

This review highlights that bacteriophage therapy shows promise for acne treatment by specifically targeting Cutibacterium acnes, but larger clinical trials and improved regulatory frameworks are needed for further development.

This source provides a comprehensive overview of amenorrhea, detailing its classification, potential causes such as hormonal imbalances and structural abnormalities, and the various management strategies including hormone therapy and lifestyle modifications tailored to its underlying causes.

This review discusses the lack of explicit theoretical foundations in empirical studies on transgender men and emphasizes the need for bioethical frameworks to guide decision-making.

This review discusses the developments over the past five years in nanozyme-based theranostics for tumor therapy, including their classification, design, and synergistic strategies. It also outlines the challenges and prospects of using nanozymes to enhance selectivity, biosafety, repeatability, and stability in therapeutic applications.

This study explores the complex mechanisms of skin aging, including cellular senescence and disrupted communication, and highlights rejuvenation strategies like gene expression rewiring and microbiome modulation, offering potential frameworks for regenerative therapies and precise interventions in skin and systemic aging.

In this review of autonomous robotic surgery, the authors explore the integration of AI and machine learning in surgical procedures, detailing both the advancements and challenges of these technologies, including ethical concerns and current regulatory frameworks.