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This study developed a deep-learning model using unannotated dermatology images from online forums, achieving 49.64% accuracy in classifying 22 skin diseases and 61.76% accuracy in detecting monkeypox, highlighting the potential of these images for skin disease diagnostics in China.

This study presents a new hair removal algorithm for dermatoscopic images of skin lesions that improves hair detection accuracy by 2–7% and hair repair accuracy by 2–5% on average, using advanced techniques like maximum variance fuzzy clustering, Criminisi priorities, and the ant colony algorithm.

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

This case report describes successful moustache restoration in an 18-year-old with a cleft lip scar using single-follicular-unit graft hair transplantation, highlighting its application in corrective cosmetic surgeries.

This case report describes a successful restoration of moustache hair in an 18-year-old patient with a cleft lip scar using single-follicular-unit graft hair transplantation in one procedure.

This study explored a multidimensional approach to examine body hairs' physico-chemical properties, potentially supporting their use over scalp hairs in forensic and intoxication studies.

In this study, researchers analyzed the chemical constituents of male and female Gynostemma longipes plants and different parts like roots and leaves, identifying significant variations in metabolites which could aid in assessing and selecting quality medicinal materials.

This review discusses the multifactorial etiology of hypospadias, including genetic predispositions and possible environmental factors, and highlights the need for further studies on genetic and environmental contributions to its increasing prevalence, without presenting new findings.

This study introduced a novel deep clustering approach for melanoma detection from dermoscopic images, demonstrating improved performance over existing methods by mitigating class imbalance issues using a center-oriented margin-free triplet loss.

This study bibliometrically evaluated 5741 articles on PRP from 1980 to 2024, highlighting Türkiye's contribution and identifying prominent research areas such as orthopedics and wound healing.

This review discusses existing forensic DNA phenotyping panels for biogeographical ancestry and externally visible characteristics and highlights major technical limitations, including terminology issues, genetic knowledge gaps, and technological debates; it reports no new results.

This study explores how Astragaloside A from traditional Chinese medicine may combat lung adenocarcinoma by regulating key signaling molecules like STAT3 and AKT, using techniques such as network pharmacology and molecular docking to understand its mechanisms in cellular models.

This study found that manipulating SIMK expression in alfalfa affects root hair growth, infection thread and nodule formation, and overall plant biomass, highlighting its potential biotechnological applications.

Researchers created a fully functional, bioengineered skin system with hair from stem cells that successfully integrated when transplanted into mice.

This review discusses common hair loss conditions and explores how advancements in hair follicle biology might lead to more effective treatments but reports no new results.

This study identified key genes and signaling pathways involved in cashmere goat hair follicle growth cycles, influenced by melatonin implantation, suggesting a basis for further research on melatonin's regulatory mechanism.

This study found that Dermal Fibroblast Progenitors have repressed chromatin profiles which hinder their ability to reform skin in allograft assays despite their differentiation potential.

This study developed lipid-core nanocapsules for encapsulating menthol, improving its solubility and thermal stability, and demonstrated their safety and rapid skin absorption in ex vivo tests, highlighting potential applications for cosmeceuticals.

Machine learning is effective in predicting gene functions and their relationships with diseases.

This review discusses various topical medication instillation techniques for managing glaucoma but reports a lack of evidence on their effectiveness compared to usual care.

This study introduces AlopeciaDet, a novel feature fusion technique, using camera images to detect Alopecia Areata with 99.45% accuracy, outperforming existing methods by leveraging CRSHOG and ResNet-50 features.

This review examines genetic variation in the ovine KRTAP1.1 gene and its potential impact on wool quality, reporting no new findings but suggesting opportunities for developing gene markers for wool and pelt traits.

This review discusses the integration of omics analyses in androgenetic alopecia research, reporting no new clinical results but suggesting that collaborative multi-omics studies may enhance understanding of AGA's pathomechanisms.

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 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 found that using PRP with the FUE method of hair restoration led to better graft survival, aesthetic outcomes, and patient satisfaction compared to not using PRP.

This review found that current forensic DNA phenotyping panels for biogeographical ancestry and visible traits face significant limitations due to inconsistencies in terminology, genetic understanding, and genotyping technologies, highlighting the need for harmonization and further research.

This review highlights recent research using single-cell RNA sequencing and machine learning in wound healing, revealing significant insights into fibroblast diversity, immune cell dynamics, and the spatial organization of cells, which may transform therapeutic strategies for chronic wounds, fibrosis, and tissue regeneration.

In this study, the integration of obesity-related features and machine learning techniques significantly enhanced cardiovascular disease detection, with the XGBoost classifier achieving a 74% accuracy rate and improved metrics compared to other models.

This review discusses potential causes of alopecia and hair overgrowth in pediatric patients, detailing diagnostic techniques and treatments, but presents no new research findings.