research Pili Annulati: A case series and proposal for classification
Pili annulati may be more common than thought, so recognizing its features is important for diagnosis.
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research Phenotype-Specific Lifestyle Prediction for PCOS Using Machine Learning Multi-Class Classification and SHAP Explainability
Machine learning can accurately predict PCOS phenotypes using lifestyle and symptom data.
research Integrating Biomarkers from Correlation Analysis and Metric Learning for Hair Loss Classification
Combining biomarker analysis and advanced algorithms improves hair loss detection accuracy.
research Clinical characteristics, subtype classification, and prognostic factors of ophiasis: A retrospective study of 150 patients with therapeutic implications
Ophiasis mainly affects females, lasts longer, and has lower regrowth rates, with a new classification system helping predict treatment response.
research Chemical Structure, Classification and Clinical Significance of Steroid Hormones: A Review Article
Steroid hormones are vital for body functions and disease management.
research LB1012 The development of a pediatric alopecia areata treatment classification system based on results from a systematic review
Topical corticosteroids are recommended first for treating pediatric alopecia areata due to safety and ease of use.
research Research Progress in Composition, Classification and Influencing Factors of Hair
Lipids are important for healthy hair, but their exact role is not fully understood and needs more research.
research Zinc deficiency and its management in the pediatric population: A literature review and proposed etiologic classification
Zinc deficiency in children can cause skin issues and can be serious if not diagnosed and treated properly.
research Dissecting folliculitis (dissecting cellulitis) of the scalp: a 66‐patient case series and proposal of classification
Researchers found that dissecting folliculitis of the scalp is linked to obesity, severity increases with duration and number of nodules, and early treatment is important to prevent scarring.
research Human hair morphology: a scanning electron microscopy study on a male Caucasoid and a computerized classification of regional differences.
Hair varies in size and features depending on body region.
research Epithelial keratin and filaggrin expression in seborrheic keratosis: evaluation based on histopathological classification
Seborrheic keratosis shows varied cell differentiation, and keratin analysis helps diagnose skin tumors.
research Dose‐response of human follicles during laser‐based hair removal: Ex vivo photoepilation model with classification system embracing morphological and histological features
Higher light doses cause more damage to hair follicles, predicting better hair removal results.
research Note on Isocholesterol, Coprosterol and the Classification of the Sterols
Isocholesterol is a confirmed and recognized sterol.
research Reversing Time with Peptides: Mechanisms, Classifications, and Innovations in Anti-aging Interventions
Anti-aging peptides can improve skin appearance but need better delivery methods and more research.
research A Comprehensive Review on Alopecia: Mechanisms, Classification, and Therapeutic Strategies
Alopecia treatments are improving, but future therapies need to target underlying causes for better results.
research A Comprehensive Review on Alopecia: Mechanisms, Classification, and Therapeutic Strategies
Alopecia treatments are improving, but future therapies need to target underlying causes for better results.
research A Hybrid Deep Learning System for Automatic Detection of Scalp Diseases and Hair Fall Stage Classification
The system effectively detects scalp diseases and classifies hair fall stages with high precision.
research Deep Learning-Powered Hair Disease Diagnosis: A ResNet50 Approach for Scalable and Accurate Classification
The model accurately diagnoses hair diseases with 95% accuracy using deep learning.
research Advancing Hair Disease Diagnostics: A Deep Learning Approach Using Inception-ResNet v2 for Multi-Class Classification
The model accurately identifies hair diseases using deep learning.
research MON-317 Prognostic Factors and Mortality According to the Structural and Functional Classification of Acromegaly
Type 3 acromegaly patients have more health issues and higher death risk.
research Figure 8, The Hamilton-Norwood classification of male androgenetic Alopecia
research Advanced polymer hydrogels that promote diabetic ulcer healing: mechanisms, classifications, and medical applications
Special gels help heal diabetic foot sores and reduce the risk of amputation or death.
research Platelet‐rich plasma in hair loss—Mechanism, preparation, and classification
Platelet-rich plasma may help with hair loss by promoting hair growth.
research The Dermatological Spectrum of Coronavirus Disease-19 Disease: Cutaneous Signs for Diagnostics and Prognosis and an Expanded Classification
Skin problems like rashes and hair loss can help diagnose and predict COVID-19.
research The Life and Legacy of O'Tar T. Norwood: A Founding Father of the Norwood-Hamilton Classification System for Male Pattern Baldness, the Forum, and the ISHRS
O'Tar T. Norwood was a key figure in creating a system to classify male baldness and founding hair restoration societies.
research Tratamiento ortobiológico con plasma rico en plaquetas. Revisión sistemática y clasificación de la evidencia
PRP treatment lacks strong evidence for routine use due to poor study quality.
research Rosacea: I. Etiology, pathogenesis, and subtype classification
Rosacea is a skin condition with unclear causes, classified into four subtypes.
research How Rich is Platelet Rich Plasma? A Simple Preparation Method of PRP and Its Quality According to Various Classification Systems
A simple, cost-effective method to prepare high-quality PRP is suitable for smaller medical institutions.
research Prevalence of Male Pattern Hair Loss in 18–49 Year Old Men
Hair loss is more common in men aged 18-49 and increases with age.
research Scarring Alopecias: Pathology and an Update on Digital Developments
New digital tools are improving the diagnosis and understanding of irreversible hair loss conditions.