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- Dermacen Analytica: A Novel Methodology Integrating Multi-Modal Large Language Models with Machine Learning in tele-dermatology
- Hair & Scalp Disease Detection Using Machine Learning & Image Processing
- Hair cluster detection model based on dermoscopic images
- Deep Learning-based Trichoscopic Image Analysis and Quantitative Model for Predicting Basic and Specific Classification in Male Androgenetic Alopecia
- BaldGraphFormer: An Explainable Deep Learning Framework for Early Baldness Prediction by Integrating Swin Transformer, Graph Attention Networks and Clinical Features
- Exploring machine learning strategies for single-cell transcriptomic analysis in wound healing
- MSF-VMDNet for multi class segmentation of skin cancer whole slide images using a multi frequency dual encoder network
- HairSentinel: a time-aware anomaly detection framework for forecasting hairfall trends using temporal fusion transformers
- Release systems based on self-assembling RADA16-I hydrogels with a signal sequence which improves wound healing processes
- Preparing regenerative therapies for clinical application: proposals for responsible translation
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