research Methods of Transfer Learning for Multiclass Hair Disease Categorization
Transfer learning with three neural network architectures accurately classifies hair diseases.
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research Investigating Different Deep Learning Models for Classification of Folliculitis
GoogLeNet is the best model for identifying folliculitis.
research Deep Learning-Based Dermatological Condition Detection: A Systematic Review With Recent Methods, Datasets, Challenges, and Future Directions
Deep learning helps detect skin conditions and is advancing dermatology diagnosis and treatment.
research Challenges of Securing Insurance Approval for Oral Tofacitinib Treatment of Alopecia Areata: A Multi-Institutional Retrospective Review
Getting insurance to cover the hair loss treatment tofacitinib is hard because it's not officially approved for that use.
research Generative Adversarial Networks for Anonymous Acneic Face Dataset Generation
The method creates realistic, anonymous acne face images for research, achieving 97.6% accuracy in classification.
research Leveraging Deep Neural Networks to Uncover Unprecedented Levels of Precision in the Diagnosis of Hair and Scalp Disorders
A new AI model diagnoses hair and scalp disorders with 92% accuracy, better than previous models.
research Automating Hair Loss Labels for Universally Scoring Alopecia from Images
The AI system HairComb accurately scores hair loss severity, matching dermatologist assessments.
research Optimizing Skin Disease Diagnosis: Harnessing Online Community Data With Contrastive Learning and Clustering Techniques
Researchers improved a skin disease diagnosis model using online images, achieving up to 49.64% accuracy.
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.