research Shape Variability and Classification of Human Hair: A Worldwide Approach
Human hair can be classified into eight types based on physical features, not ethnicity.
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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 A new practical classification for spatial distribution and morphology of human hair: Ahmad's LGMA classification
Dr. Muhammad Ahmad created a hair classification system to help improve hair restoration surgery outcomes.
research Revised NPRT Classification System Encompasses Additional Patterns of Male and Female Hair Loss
The updated NPRT system now covers different types of hair loss in men and women.
research Faculty Opinions recommendation of A new classification of pattern hair loss that is universal for men and women: basic and specific (BASP) classification.
The BASP classification is a detailed system for categorizing hair loss in both men and women, but it may be complex for beginners and not fully suitable for grading female hair loss.
research A new classification of pattern hair loss that is universal for men and women: Basic and specific (BASP) classification
The BASP classification is a detailed and accurate way to categorize hair loss in both men and women.
research Relationship between Illness Behavior and Hair Loss Pattern According to the Basic and Specific (BASP) Classification
The BASP classification helps predict patient behavior and improve treatment for hair loss.
research Frequency of Different Pattern of Hair Loss in Pakistani Men Using BASP Classification
M type hair loss is the most common in Pakistani men.
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 Classification and management of skin, hair, nail and mucosal side-effects of epidermal growth factor receptor (EGFR) inhibitors
EGFR inhibitors often cause skin problems and other side effects, but these are usually reversible and can be managed to keep patients comfortable.
research Hair casts: Classification, staining characteristics, and differential diagnosis
A new method helps identify and classify different types of hair casts.
research Reliability of the pattern hair loss classifications: A comparison of the basic and specific and N orwood–H amilton classifications
The BASP classification is more reliable than the Norwood-Hamilton for classifying hair loss in men and women.
research Application of the basic and specific classification on patterned hair loss in Indians
The BASP classification is effective for diagnosing pattern hair loss in Indian men and women.
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 Modified basic and specific (BASP) classification for pattern hair loss
The modified hair loss classification is more detailed but less user-friendly.
research Deep Learning Approaches for Hair Disease Classification: A Comparative Analysis of MobileNetV2 and VGG19 Architectures
VGG19 is more accurate, but MobileNetV2 is faster and uses fewer resources.
research Automated Trichoscopic Analysis for Hair Disorder Classification Using Semantic Segmentation
An automated system can accurately classify hair disorders using image analysis.
research Hair Transplant: Classification, Analysis, and Treatment Planning of Male Pattern Hair Loss and Newer Techniques in FUT Hair Restoration
Hair restoration surgery is becoming more common as male pattern baldness increases with age.
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 Enhanced Hair Disease Classification Using Deep Learning
The model accurately classifies hair conditions with 97% accuracy.
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 Depth control in follicular unit excision: A new classification from a detailed analysis of 30 patients undergoing FUE technique for hair restoration
A new classification for depth control in hair restoration surgery was proposed, dividing it into three grades based on the depth required for successful graft extraction.
research P154 Revised basic and specific (BASP) classification for pattern hair loss
The revised BASP classification for hair loss is less accurate and harder to use but could still be a viable option.
research Classification of hair disease
Classifying hair diseases, like alopecia, is difficult and needs more research to understand their causes.
research The Ziering Whorl Classification of Scalp Hair
The conclusion is that creating natural-looking hair restoration requires replicating natural scalp whorl patterns and inserting grafts at specific angles.
research A new classification of early female pattern hair loss
The new system helps detect and track early female hair loss better.
research Classification and Frequency of Crown Whirlpool Patterns in Male Hair Transplant Patients
Understanding crown whorl patterns can improve hair transplant results for men.
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 The Ziering Whorl Classification of Scalp Hair
Craig Ziering created a system to classify scalp hair patterns, important for improving hair restoration surgery results.
research 7 Pathogenesis and Classification of Male Pattern Hair Loss (Androgenic Alopecia)
Male pattern hair loss is mainly caused by genetics and hormones, especially DHT.