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- Predicting Hair Loss with AI: A Deep Learning Framework Combining Genetic and Scalp Health Data
- BaldGraphFormer: An Explainable Deep Learning Framework for Early Baldness Prediction by Integrating Swin Transformer, Graph Attention Networks and Clinical Features
- Deep Learning Based Non-Invasive Framework for Nutritional Deficiency Detection Using Hair and Nail Images
- Neurospectrum: A Geometric and Topological Deep Learning Framework for Uncovering Spatiotemporal Signatures in Neural Activity
- Rapid Screening of Anticoagulation Compounds for Biological Target-Associated Adverse Effects Using a Deep-Learning Framework in the Management of Atrial Fibrillation
- KRDQN: An Interpretable Prediction Framework for Adverse Drug Reactions via Knowledge–Graph Reinforced Deep Q-Learning
- Deep Learning-based Automatic System for Diagnosis and Classification of Skin Dermatoses
- Quantitative analysis and development of alopecia areata classification frameworks
- A Hybrid Deep Learning System for Automatic Detection of Scalp Diseases and Hair Fall Stage Classification
- Deep Learning-Powered Hair Disease Diagnosis: A ResNet50 Approach for Scalable and Accurate Classification
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