research Application of 3D Reflectance Confocal Microscopy: Melanocytic Proliferations as 3D Models; JAAD Supplemental Material
3D models from confocal microscopy improve melanoma detection on sun-damaged skin.
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research A Comprehensive Survey on Vitiligo Detection Using Deep Learning
Better datasets and methods are needed for reliable vitiligo detection using deep learning.
research Hair color digitization through imaging and deep inverse graphics
A new method accurately captures and renders hair color for virtual reality and hair dye use.
research Revolutionizing Hair Fall Analysis: The Advanced Precipitation U-Net Model
The Advanced Precipitation U-Net Model improves early hair fall detection with 92% accuracy.
research Metamorph analysis and quantification of activated eccrine glands in alopecia areata
Eccrine gland activity may be linked to alopecia areata.
research 198 Reliable and interpretable segmentation for remote assessment of atopic dermatitis severity using digital images
The improved EczemaNet more reliably and clearly identifies and assesses the severity of atopic dermatitis from photos.
research Genetic Fate Mapping Using Site-Specific Recombinases
The document concludes that careful design of genetic fate mapping experiments is crucial for accurate cell lineage tracing in mice.
research Automated quantitative analysis of coat and skin coloration in laboratory animals
A new algorithm accurately analyzes animal coat and skin colors quickly and easily.
research Development of a New Grading Scale for Evaluating Overall Hair Density
A new reliable scale improves accuracy in measuring hair density and treatment response.
research Multi-scale spatial mapping of cell populations across anatomical sites in healthy human skin and basal cell carcinoma
The research created a detailed map of skin cells, showing that certain cells in basal cell carcinoma may come from hair follicles and could help the cancer grow.
research A Novel Fusion Technique for Early Detection of Alopecia Areata Using ResNet-50 and CRSHOG
AlopeciaDet accurately detects Alopecia Areata early using advanced image analysis.
research DEEP REVIEW ON ALOPECIA AREATA DIAGNOSIS FOR HAIR LOSS-RELATED AUTOIMMUNE DISORDER PROBLEM
Machine learning and deep learning can effectively diagnose alopecia areata.
research Multiscale spatial mapping of cell populations across anatomical sites in healthy human skin and basal cell carcinoma
The research created a detailed map of skin cells, showing that certain cells in basal cell carcinoma may come from hair follicles and could help the cancer grow.
research Hair & Scalp Disease Detection Using Machine Learning & Image Processing
AI can accurately diagnose hair and scalp conditions and suggest treatments.
research Hair and Scalp Disease Detection using Machine Learning and Image Processing
The machine learning model accurately detected hair loss and scalp diseases using processed images.
research Validation of scalp coverage scoring methods for scalp hair loss in male pattern hair loss (androgenetic alopecia)
Scalp coverage scoring accurately measures hair loss and treatment effectiveness.
research Optogenetically Controlled TrkA Activity Improves the Regenerative Capacity of Hair‐Follicle‐Derived Stem Cells to Differentiate into Neurons and Glia
Blue-light activation of TrkA improves hair-follicle stem cells' ability to become neurons and glial cells.
research Coordinated Activation of Wnt in Epithelial and Melanocyte Stem Cells Initiates Pigmented Hair Regeneration
Wnt signaling is crucial for pigmented hair regeneration by controlling stem cell activation and differentiation.
research A semiquantitative grading scale for frontal and vertex of androgenetic alopecia
New grading scale accurately measures hair loss severity and treatment effectiveness.
research Poster 147 Determination of Individual in Vivo Hip Muscle Forces Using an EMG‐to‐Force Processing Model
The EMG-to-force model accurately predicts hip muscle forces during walking.
research Clinically relevant skull models and optical measurement method to evaluate programmable hydrocephalus valve tool kit usability
Three skull models were found most useful for testing hydrocephalus valve programming.
research Identification of Stress-Related Hair Loss and Prevention Through the Application of a KNN Model Based on Machine Learning
Machine learning can predict stress-related hair loss and suggest prevention tips.
research Competitive balance of intrabulge BMP/Wnt signaling reveals a robust gene network ruling stem cell homeostasis and cyclic activation
BMP and Wnt signaling balance controls hair follicle stem cell activity and hair growth.
research Ultrasound-Activated GelMA Hydrogel Loaded with MSC-EVs Promotes Functional Regeneration of Skin Vasculature, Nerves, and Appendages
Ultrasound-activated gel with stem cell vesicles improves skin healing and regeneration.
research A Fuzzy Logic-Based Computational Framework for Precision Triage in Androgenetic Alopecia: A Simulated Biomarker-Driven Approach
The TPAP method effectively categorizes androgenetic alopecia patients with high accuracy, but needs real-world validation.
research Hair analysis based on medical history and spatial-temporal data
Machine learning can predict hair health accurately using personal data.
research Classification and Scoring of Androgenetic Alopecia (Male and Female Pattern)
The document explains how hair loss patterns in men and women, known as Androgenetic alopecia, are classified using the Hamilton-Norwood system for men and the Ludwig grade system for women.
research Spatial transcriptomics of a giant pilomatricoma
The analysis of a large pilomatricoma revealed five distinct areas with different gene activity related to hair growth and tumor development.
research Scalp disease analysis using deep learning models
Deep learning models can analyze scalp diseases effectively.
research Wnt/β-catenin signaling pathway activates melanocyte stem cells in vitro and in vivo
The Wnt/β-catenin pathway can activate melanocyte stem cells and may help regenerate hair follicles.