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- Deep Learning-Based Dermatological Condition Detection: A Systematic Review With Recent Methods, Datasets, Challenges, and Future Directions
- Automated early detection of androgenetic alopecia using deep learning on trichoscopic images from a Korean cohort: a retrospective model development and validation study
- Hair and scalp disease detection using deep learning
- Polycystic ovary syndrome: pragmatic management across levels of care
- Crowdsourcing Dermatology Images with Google Search Ads: Creating a Real-World Skin Condition Dataset
- Understanding hair disorders through artificial intelligence: DALLE's role in image creation
- Skin image analysis for detection and quantitative assessment of dermatitis, vitiligo and alopecia areata lesions: a systematic literature review
- Androgenetic alopecia and emotional impact: a perspective from dermatological nursing and aesthetic care
- A quantitative technique to analyze and evaluate microstructures of skin hair follicles based on mueller matrix polarimetry
- BaldGraphFormer: An Explainable Deep Learning Framework for Early Baldness Prediction by Integrating Swin Transformer, Graph Attention Networks and Clinical Features
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