research Severity Prediction of Hair Loss in Alopecia Areata with Hybrid Deep Learning Architecture
The model accurately predicts hair loss severity in alopecia areata.
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90-120 / 1000+ resultsresearch Hair and scalp disease detection using deep learning
Deep learning can effectively detect hair and scalp diseases early.
research A Hybrid Deep Learning System for Automatic Detection of Scalp Diseases and Hair Fall Stage Classification
The system effectively detects scalp diseases and classifies hair fall stages with high precision.
research The Hair Cell Analysis Toolbox: A machine learning-based whole cochlea analysis pipeline
The Hair Cell Analysis Toolbox automates and improves the analysis of cochlear hair cells using machine learning.
research Hair & Scalp Disease Detection Using Machine Learning & Image Processing
AI can accurately diagnose hair and scalp conditions and suggest treatments.
research Leveraging deep neural networks to uncover unprecedented levels of precision in the diagnosis of hair and scalp disorders
A new AI model diagnoses hair and scalp disorders with 92% accuracy, better than previous models.
research Attention Balanced Multi-Dimension Multi-Task Deep Learning for Alopecia Recognition
The new deep learning system can accurately recognize hair loss conditions with a 95.11% success rate.
research Methods of Transfer Learning for Multiclass Hair Disease Categorization
Transfer learning with three neural network architectures accurately classifies hair diseases.
research Hair Disease Classification Using Convolutional Neural Network (CNN) Algorithm with VGG-16 Architecture
The system can accurately classify hair diseases with 94.5% accuracy using a CNN.
research Diagnosis of Scalp Disorders using Machine Learning and Deep Learning Approach -- A Review
Deep learning effectively diagnoses scalp disorders, but improvements are needed.
research Hair Color Digitization through Imaging and Deep Inverse Graphics
A new method accurately captures and renders hair color for real and synthetic images.
research Hair color digitization through imaging and deep inverse graphics
A new method accurately captures and renders hair color for virtual reality and hair dye use.
research Research Techniques Made Simple: Optical Clearing and Three-Dimensional Volumetric Imaging of Skin Biopsies
3D imaging of skin biopsies offers better accuracy but is time-consuming and can't clear melanin.
research Deep Learning-Powered Hair Disease Diagnosis: A ResNet50 Approach for Scalable and Accurate Classification
The model accurately diagnoses hair diseases with 95% accuracy using deep learning.
research A Machine Learning-Based Scalp Hair Inspection and Diagnosis System for Scalp Health
The system can automatically identify different hair and scalp conditions using machine learning.
research An Early Hair Loss Detection and Prediction Method Based on Machine Learning
Machine learning can accurately predict hair loss early, improving treatment options.
research DEEP REVIEW ON ALOPECIA AREATA DIAGNOSIS FOR HAIR LOSS-RELATED AUTOIMMUNE DISORDER PROBLEM
Machine learning and deep learning can effectively diagnose alopecia areata.
research Research on Mental Stress Recognition of Depressive Disorders in Patients With Androgenic Alopecia Based on Machine Learning and Fuzzy K-Means Clustering
The FAW-FS algorithm improves depression recognition, and psychological interventions help AGA patients' mental health.
research KRDQN: An Interpretable Prediction Framework for Adverse Drug Reactions via Knowledge–Graph Reinforced Deep Q-Learning
KRDQN effectively predicts adverse drug reactions with high accuracy and clear explanations.
research HairLossMultinet: A Multi Scale Feature Fusion Method Using Deep Learning Approach
HairLossMultinet accurately classifies hair damage with 98% accuracy but needs a more diverse dataset for broader use.
research Optimized VGG19 Architecture for Precise and Efficient Multi-Class Hair Disease Classification
The optimized VGG19 model accurately classifies hair diseases with 98.64% accuracy.
research DEEP REINFORCEMENT LEARNING FOR SCALABLE CONTROL OF BOOLEAN MODELS IN THE CONTEXT OF CELLULAR REPROGRAMMING
pbn-STAC effectively finds strategies for cellular reprogramming using deep reinforcement learning.
research PandaOmics: An AI-Driven Platform for Therapeutic Target and Biomarker Discovery
PandaOmics uses AI to find new disease treatment targets and biomarkers.
research Hair and Scalp Disease Detection using Machine Learning and Image Processing
The machine learning model accurately detected hair loss and scalp diseases using processed images.
research Investigating Different Deep learning Models for Classification of Folliculitis
GoogLeNet is the best model for identifying folliculitis.
research Ensemble of pre-learned deep learning model and an optimized LSTM for Alopecia Areata classification
The new model improves Alopecia Areata classification accuracy to 93.1%.
research Nanotechnology-Based Strategies for Hair Regeneration: Mechanistic Insights and Translational Perspectives for Androgenetic Alopecia
Nanotechnology offers promising new treatments for hair loss by improving targeted delivery and addressing key causes.
research Efficient integration of human skin single-cell RNA sequencing data
A comprehensive human skin cell atlas was created to better understand skin biology and disease.
research Efficient integration of human skin single-cell RNA sequencing data
A comprehensive human skin cell atlas was created to better understand skin biology and disease.
research Artificial Intelligence in Aesthetic Medicine: Applications, Challenges, and Future Directions
AI improves aesthetic medicine but faces challenges like biases and privacy issues that need addressing for successful integration.