research Geometric classification of scalp hair for valid drug testing, 6 more reliable than 8 hair curl groups
A 6-group hair classification is more reliable for drug testing than an 8-group system.
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30 / 1000+ results research Human scalp hair: geometry, biochemistry, growth parameters and mechanical characteristics
A 6-group geometric classification of human scalp hair is more reliable and objective for testing than an 8-group system.
research Reimagining Hair Science: A New Approach to Classify Curly Hair Phenotypes via New Quantitative Geometrical & Structural Mechanical Parameters
A new system for classifying curly hair types using precise measurements can improve hair care products and cultural inclusion.
research Systems Approach to Human Hair Fibers: Interdependence Between Physical, Mechanical, Biochemical and Geometric Properties of Natural Healthy Hair
Hair properties are interconnected; a comprehensive, cross-disciplinary approach is essential for understanding hair behavior.
research Reimagining Hair Science: A New Approach to Classify Curly Hair Phenotypes via New Quantitative Geometrical & Structural Mechanical Parameters
New methods to classify curly hair types were developed based on shape and strength.
research An Analysis of Alopecia Areata Classification Framework for Human Hair Loss Based on VGG-SVM Approach
The VGG-SVM method accurately identifies and classifies stages of Alopecia Areata and other hair loss conditions.
research Reimagining Hair Science: A New Approach to Classify Curly Hair Phenotypes via New Quantitative Geometric and Structural Mechanical Parameters
New methods can better classify curly hair types and lead to improved hair care products.
research Artificial neural networks algorithms for prediction of human hair loss related autoimmune disorder problem
Artificial neural networks can accurately diagnose Alopecia Areata.
research No difference in the proteome of racially and geometrically classified scalp hair sample from a South African cohort: Preliminary findings
Hair protein composition is similar across different races and shapes.
research How different is human hair? A critical appraisal of the reported differences in global hair fibre characteristics and properties towards defining a more relevant framework for hair type classification
Human hair varies widely and should be classified by curl type rather than race.
research Fractal geometry and topology abstracted from hair fibers
Hair fibers have fractal patterns with properties related to the golden mean, which may affect their functionality.
research The Role of Interface Geometry and Appendages on the Mesoscale Mechanics of the Skin
Skin's uneven surface and hair follicles affect its stress and strain but don't change its overall strength, and help prevent the skin from peeling apart.
research Optimized polycystic ovarian disease prognosis and classification using AI based computational approaches on multi-modality data
AI can improve early diagnosis and classification of PCOS, aiding in prevention of related health issues.
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 AB-MTEDeep Classifier Trained with AAGAN for the Identification and Classification of Alopecia Areata
The AI model accurately classifies Alopecia Areata with 96.94% accuracy.
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 Male Pattern Androgenetic Alopecia
Androgens contribute to common male hair loss; more research needed for hair growth medication.
research A new classification of early female pattern hair loss
The new system helps detect and track early female hair loss better.
research Pharmacophore Modeling and Three Dimensional Database Searching for Drug Design Using Catalyst: Recent Advances
The document concludes that Catalyst software is effective for drug design, identifying potent compounds for various medical conditions.
research Evaluation of hair loss
Detailed patient history and physical exams are crucial for diagnosing hair loss.
research Philosophy and technique in hair restoration surgery
Hair restoration surgery has evolved over time, with a focus on natural-looking results and managing patient expectations, while also considering potential complications and the lifelong progression of male pattern baldness.
research Pattern formation on regular polygons and circles
Domain shape greatly affects pattern formation.
research V Congress of the Portuguese Society of Cosmetological Sciences - Proceedings
The congress showed advancements in skin hydration, barrier function, and safe, effective new cosmetic formulations.
research Deep Insight of Design, Mechanism, and Cancer Theranostic Strategy of Nanozymes
Nanozymes show promise for effective and safe cancer treatment.
research Deep Clustering via Center-Oriented Margin Free-Triplet Loss for Skin Lesion Detection in Highly Imbalanced Datasets
The new method improves skin cancer detection in imbalanced datasets.
research Psychocutaneous disease
Many skin patients have mental health issues, but few dermatologists are well-versed in treating these conditions.
research Alopecia: Kids are not just little people
Hair loss in children is diagnosed and treated differently than in adults, with different common causes and a focus on less invasive methods.
research Etiopathogenesis of Alopecia Areata
Alopecia Areata is an autoimmune condition causing hair loss, influenced by genetics, environment, and possibly improved by anti-MIF therapy, with many patients experiencing regrowth within a year.
research Enhanced stratification of male pattern hair loss using AI through novel loss region ratio analysis
AI improves accuracy and consistency in diagnosing male pattern hair loss.
research Detection of Meibomian Gland Dysfunction by in vivo Confocal Microscopy Based on Deep Convolutional Neural Network
The model can effectively help diagnose meibomian gland dysfunction automatically.