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- Scalp Disorder Imaging: How Deep Learning and Explainable Artificial Intelligence are Revolutionizing Diagnosis and Treatment
- Application of big data analytics in minoxidil drug development: a data-driven model for predicting efficacy and side effect risks
- Convolutional Neural Networks for Non-Invasive Diagnosis of Androgenetic Alopecia using Dermoscopic Hair Images
- Radiomics and radiogenomics in ovarian cancer: a review with a focus on ultrasound applications
- Advancing Hair Disease Diagnostics: A Deep Learning Approach Using Inception-ResNet v2 for Multi-Class Classification
- Deep Learning-Powered Hair Disease Diagnosis: A ResNet50 Approach for Scalable and Accurate Classification
- 198 Reliable and interpretable segmentation for remote assessment of atopic dermatitis severity using digital images
- KRDQN: An Interpretable Prediction Framework for Adverse Drug Reactions via Knowledge–Graph Reinforced Deep Q-Learning
- BaldGraphFormer: An Explainable Deep Learning Framework for Early Baldness Prediction by Integrating Swin Transformer, Graph Attention Networks and Clinical Features
- Artificial Intelligence in Patient Education for Androgenetic Alopecia: A Comparative Study of ChatGPT, Gemini, and Deepseek R1
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