Rethinking Pattern Hair Loss Classification in the Era of Trichoscopy and Artificial Intelligence
March 2026
in “
Frontiers in Medicine
”
Research cited in this study
11 / 11 results
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 New Frontiers of Non-Invasive Detection in Scalp and Hair Diseases: A Review of the Application of Novel Detection Techniques
New non-invasive techniques can improve diagnosis and treatment of scalp and hair diseases.
research Trichoscopy of Androgenetic Alopecia: A Systematic Review
Trichoscopy shows hair diameter variability, vellus hairs, and the peripilar sign are key indicators for diagnosing Androgenetic Alopecia.
research The Value of Trichoscopy in the Follow-Up of Treatment Response in Patients With Androgenetic Alopecia
Trichoscopy is effective for tracking treatment progress in hair loss when used by an experienced doctor.
research Trichoscopy Patterns in Alopecia Areata: A Systematic Review and Meta-Analysis
Yellow dots and short vellus hairs are the most common signs of Alopecia Areata (AA), and trichoscopy can help diagnose AA and track treatment progress.
research Clinical and Trichoscopic Graded Live Visual Scale for Androgenetic Alopecia
Trichoscopy is crucial for diagnosing and managing androgenetic alopecia, showing increased vellus hairs, empty follicles, and fibrosis with severity.
research How Good Is Artificial Intelligence at Solving Hairy Problems? A Review of AI Applications in Hair Restoration and Hair Disorders
AI is effective in diagnosing and treating hair disorders, including detecting hair loss and scalp conditions with high accuracy, but it should supplement, not replace, doctor-patient interactions.
research Evaluation of Patients with Alopecia
Better tools are needed to assess alopecia effectively.
research Classification of Male-Pattern Hair Loss
No current system perfectly classifies male-pattern hair loss, indicating a need for a new system for better diagnosis and treatment.
research Classifications of Patterned Hair Loss: A Review
Different types of hair loss need specific treatments, and while many classification systems exist, each has its flaws; more research is needed to refine these systems and treatments.
research Reliability of the Pattern Hair Loss Classifications: A Comparison of the Basic and Specific and Norwood–Hamilton Classifications
The BASP classification is more reliable than the Norwood-Hamilton for classifying hair loss in men and women.