research Enhanced Hair Disease Classification Using Deep Learning
The model accurately classifies hair conditions with 97% accuracy.
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research A New Universal Follicular Unit Excision Classification System for Hair Transplantation Difficulty and Patient Outcome
The new SFS Scale predicts hair transplant difficulty using hair and skin types, with thick skin and coily hair being hardest to work with.
research Lonely Hair Sign: Not Specific for Frontal Fibrosing Alopecia
Hair diameter diversity is a key sign for diagnosing and managing male pattern baldness.
research Rethinking the classification of alopecia areata
The document concludes that a new system using the SALT score should replace the current alopecia areata classification for better accuracy in assessing severity and prognosis.
research Regenera activa AMT to treat androgenetic alopecia
Regenera Activa AMT effectively improves hair growth and reduces hair loss in androgenetic alopecia.
research LO-010 Relationship between the EULAR/ACR classification criteria and organ damage in systemic lupus erythematosus
Higher EULAR/ACR scores in SLE patients predict more organ damage.
research The Adapted Classification of Male Pattern Hair Loss Improves Reliability
Adapted classification better assesses male pattern hair loss and its link to heart disease.
research The Cohen hair loss classification system
Dr. Bernard Cohen created a new system to classify hair loss using numbers and a detailed scalp map.
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 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 Is there a relationship between androgenic alopecia and benign prostatic hyperplasia?
There's no link between hair loss type androgenic alopecia and benign prostatic hyperplasia, but early hair loss and family history can mean more severe alopecia.
research Hair diameter diversity: a clinical sign reflecting the follicle miniaturization.
Different thicknesses of hair strands can indicate the severity of hair thinning.
research Study of Hairfall through Cohen hair loss index with reference to different Mizaj
Hair loss patterns are linked to temperament and can help diagnose it.
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 Attention Balanced Multi-Dimension Multi-Task Deep Learning for Alopecia Recognition
The new deep learning system can accurately recognize hair loss conditions with a 95.11% success rate.
research Long-term (10-year) efficacy of finasteride in 523 Japanese men with androgenetic alopecia
Finasteride is effective and safe for long-term treatment of hair loss in Japanese men.
research An Explainable AI-Based Decision Support System for Teaching and Classifying Hair Loss Types
The AI system accurately classifies hair loss types and explains its decisions.
research Platelet Rich Plasma as Monotherapy in Androgenetic Alopecia
PRP therapy may help reduce hair loss and increase hair density in androgenetic alopecia.
research Research on Mental Stress Recognition of Depressive Disorders in Patients With Androgenic Alopecia Based on Machine Learning and Fuzzy K-Means Clustering
The FAW-FS algorithm improves depression recognition, and psychological interventions help AGA patients' mental health.
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.
research Hair Disease Classification Using Convolutional Neural Network (CNN) Algorithm with VGG-16 Architecture
The system can accurately classify hair diseases with 94.5% accuracy using a CNN.
research Harnessing Deep Learning for Scalp and Hair Disease Classification: A Comparative Study of Convolutional Neural Networks Architectures
VGG16 and VGG19 are the most accurate for classifying scalp and hair diseases.
research Optimized VGG19 Architecture for Precise and Efficient Multi-Class Hair Disease Classification
The optimized VGG19 model accurately classifies hair diseases with 98.64% accuracy.
research A Guide to Assessing Damage Response Pathways of the Hair Follicle: Lessons From Cyclophosphamide-Induced Alopecia in Mice
The document concludes that assessing hair follicle damage due to cyclophosphamide in mice involves analyzing structural changes and suggests a scoring system for standardized evaluation.
research Quantifying Alopecia Areata via Texture Analysis to Automate the SALT Score Computation
Researchers created a fast, accurate computer program to measure hair loss in alopecia areata patients.
research Role of Hair Prostheses (Wigs) in Patients with Severe Alopecia Areata
Wigs significantly improve the well-being of people with severe hair loss.
research The relation between the severity of androgenetic alopecia and cardiovascular atherosclerosis measured via carotid intima-media thickness and the syntax score
Severe hair loss (androgenetic alopecia) is linked to higher risk of heart disease (cardiovascular atherosclerosis).
research Hair Follicle Classification and Hair Loss Severity Estimation Using Mask R-CNN
An intelligent system can classify hair follicles and measure hair loss severity with reasonable accuracy.
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 Predicting hair cortisol levels with hair pigmentation genes: a possible hair pigmentation bias
Darker hair may lead to higher cortisol readings, suggesting a need to adjust for hair color in studies.