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Research 19
- Scalp Disease Detection Using Deep Learning: A Hybrid Ensemble Approach with EfficientNetB0, DenseNet121 and MobileNetV2
- Leveraging deep neural networks to uncover unprecedented levels of precision in the diagnosis of hair and scalp disorders
- A Hybrid Deep Learning System for Automatic Detection of Scalp Diseases and Hair Fall Stage Classification
- Investigating Different Deep learning Models for Classification of Folliculitis
- Skin development in the gray short‐tailed opossum (<i>Monodelphis domestica</i>)—From skin respiration to thermoregulation
- Analyse trichoskopischer Bilder mit tiefen neuronalen Netzen zur Diagnose und Aktivitätsbewertung von Alopecia areata – eine retrospektive Studie
- DETECTION OF HAIR FALL AND SCALP DISORDERS THROUGH ML AND IMAGE PROCESSING
- Penetration and storage of particles in human skin: Perspectives and safety aspects
- Deep Clustering via Center-Oriented Margin Free-Triplet Loss for Skin Lesion Detection in Highly Imbalanced Datasets
- Quantitative analysis and development of alopecia areata classification frameworks
- Harnessing Deep Learning for Scalp and Hair Disease Classification: A Comparative Study of Convolutional Neural Networks Architectures
- 448 Challenges of securing insurance approval for oral tofacitinib treatment of alopecia areata: A multi-institutional retrospective review
- Hair and scalp disease detection using deep learning
- Effectiveness and safety of triple-diode laser with or without adjunctive topical eflornithine in female hirsutism
- Integration of Colorimetric Sensing Dyes and Multi‐Substrate Arrays for Food Quality and Safety Monitoring: Design, Optimization, and Analysis
- HairSentinel: a time-aware anomaly detection framework for forecasting hairfall trends using temporal fusion transformers
- An Early Hair Loss Detection and Prediction Method Based on Machine Learning
- Artificial intelligence in dermatology: а scoping review
- Topical drug delivery strategies for enhancing drug effectiveness by skin barriers, drug delivery systems and individualized dosing