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Research 271–300 of 1000+
- Hair & Scalp Disease Detection Using Machine Learning & Image Processing
- Dermacen Analytica: A Novel Methodology Integrating Multi-Modal Large Language Models with Machine Learning in tele-dermatology
- Detecting shortcut learning for fair medical AI using shortcut testing
- Machine learning-based steroid metabolome analysis reveals three distinct subtypes of polycystic ovary syndrome and implicates 11-oxygenated androgens as major drivers of metabolic risk
- Machine Learning Guided Discovery of Superoxide Dismutase Nanozymes for Androgenetic Alopecia
- Machine learning for nanozyme development in anti‐inflammatory applications
- Predicting Hair Loss with AI: A Deep Learning Framework Combining Genetic and Scalp Health Data
- Automated Machine Learning Analysis of Patients With Chronic Skin Disease Using a Medical Smartphone App: Retrospective Study
- Early prediction of alopecia areata using machine learning modeling of neuro stress immune signatures from multi datasets
- Artificial Intelligence Deep Learning Ultrasound Discrimination of Cosmetic Fillers
- Machine learning driven multi-omics analysis of the genetic mechanisms behind the double-coat fleece formation in Hetian sheep
- Deep Learning Approaches for Hair Disease Classification: A Comparative Analysis of MobileNetV2 and VGG19 Architectures
- Hair and scalp disease detection using deep learning
- Optimizing skin disease diagnosis: harnessing online community data with contrastive learning and clustering techniques
- Diagnosis of Scalp Disorders using Machine Learning and Deep Learning Approach -- A Review
- Deep Learning-Based Dermatological Condition Detection: A Systematic Review With Recent Methods, Datasets, Challenges, and Future Directions
- Machine Learning Approach for Predicting Systemic Lupus Erythematosus in Oman-based Cohort
- Automated measurement of hair density and projected apparent width via deep learning–based phototrichogram analysis
- Machine Learning–Enhanced Pharmacovigilance Assessment of Cardiac Adverse Events Associated with Minoxidil
- Machine Learning–Enhanced Pharmacovigilance Assessment of Cardiac Adverse Events Associated with Minoxidil
- Machine learning applications in androgenetic alopecia: a systematic review
- BaldGraphFormer: An Explainable Deep Learning Framework for Early Baldness Prediction by Integrating Swin Transformer, Graph Attention Networks and Clinical Features
- Machine learning‐guided multi‐omics suggests iron‐dependent hormonal signaling drives root morphological plasticity in wheat under temperature stress
- Scalp Disease Detection Using Deep Learning: A Hybrid Ensemble Approach with EfficientNetB0, DenseNet121 and MobileNetV2
- PEDL-XAI: A Hybrid Probabilistic Ensemble Deep Learning Approach for Hair Disorder Diagnosis
- Deep Learning Based Non-Invasive Framework for Nutritional Deficiency Detection Using Hair and Nail Images
- A Hybrid Deep Learning System for Automatic Detection of Scalp Diseases and Hair Fall Stage Classification
- Machine Learning--Enhanced Pharmacovigilance Assessment of Cardiac Adverse Events Associated With Minoxidil
- An Early Hair Loss Detection and Prediction Method Based on Machine Learning
- Machine learning predicts scarring progression in lichen planopilaris: A multidimensional model integrating trichoscopy, vitamin D, and diagnostic timelines