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Research 31–60 of 1000+
- Past, present, and future of global research on artificial intelligence applications in dermatology: A bibliometric analysis
- Hair & Scalp Disease Detection Using Machine Learning & Image Processing
- Investigating Different Deep learning Models for Classification of Folliculitis
- Optimized polycystic ovarian disease prognosis and classification using AI based computational approaches on multi-modality data
- An Early Hair Loss Detection and Prediction Method Based on Machine Learning
- Smart Diagnostic System for Health Risk Assessment
- Hair Disease Classification Using Convolutional Neural Network (CNN) Algorithm with VGG-16 Architecture
- Methods of Transfer Learning for Multiclass Hair Disease Categorization
- Optimized VGG19 Architecture for Precise and Efficient Multi-Class Hair Disease Classification
- Identification of Drug-Disease Associations Using Information of Molecular Structures and Clinical Symptoms via Deep Convolutional Neural Network
- Regenerative Strategies for Androgenetic Alopecia: Evidence, Mechanisms, and Translational Pathways
- Serum-Based Assessment of Alopecia Areata Response to Treatment Using ATR-FTIR Spectroscopy
- JAK-centric explainable few-shot gene-expression diagnosis framework for alopecia via MultiPLIER priors and relation-style set-to-set comparison
- Detecting shortcut learning for fair medical AI using shortcut testing
- Artificial Intelligence in Aesthetic Medicine: Applications, Challenges, and Future Directions
- Research Techniques Made Simple: Optical Clearing and Three-Dimensional Volumetric Imaging of Skin Biopsies
- Artificial Intelligence Deep Learning Ultrasound Discrimination of Cosmetic Fillers
- BaldGraphFormer: An Explainable Deep Learning Framework for Early Baldness Prediction by Integrating Swin Transformer, Graph Attention Networks and Clinical Features
- A machine learning approach for non-invasive PCOS diagnosis from ultrasound and clinical features
- Trichoscopy and Computational Models for Hair and Scalp Disorders: Image Analysis, Quantification, and Clinical Integration
- Hair cluster detection model based on dermoscopic images
- Deep Learning Approaches for Hair Disease Classification: A Comparative Analysis of MobileNetV2 and VGG19 Architectures
- Quantitative analysis and development of alopecia areata classification frameworks
- Scalp Disease Detection Using Deep Learning: A Hybrid Ensemble Approach with EfficientNetB0, DenseNet121 and MobileNetV2
- 200 Deep learning model to predict sentinel lymph node status in melanoma patients
- Enhanced stratification of male pattern hair loss using AI through novel loss region ratio analysis
- Research on Mental Stress Recognition of Depressive Disorders in Patients With Androgenic Alopecia Based on Machine Learning and Fuzzy K-Means Clustering
- Rapid Screening of Anticoagulation Compounds for Biological Target-Associated Adverse Effects Using a Deep-Learning Framework in the Management of Atrial Fibrillation
- Personalized scalp and hair care. Overview of trichological products and therapies
- KRDQN: An Interpretable Prediction Framework for Adverse Drug Reactions via Knowledge–Graph Reinforced Deep Q-Learning