research Hair Loss Diagnosis Using Artificial Neural Networks
Neural networks can effectively predict hair loss.
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30 / 1000+ results research Artificial neural networks algorithms for prediction of human hair loss related autoimmune disorder problem
Artificial neural networks can accurately diagnose Alopecia Areata.
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 Hair & Scalp Disease Detection Using Machine Learning & Image Processing
AI can accurately diagnose hair and scalp conditions and suggest treatments.
research SNP variation in male pattern hair loss in Russians with different dihydrotestosterone levels
Certain gene variations increase male hair loss risk, influenced by hormone levels.
research A Novel Fusion Technique for Early Detection of Alopecia Areata Using ResNet-50 and CRSHOG
AlopeciaDet accurately detects Alopecia Areata early using advanced image analysis.
research An Approach to Detect Alopecia Areata Hair Disease Using Deep Learning
Deep learning can accurately detect Alopecia Areata with up to 98.3% accuracy.
research DETECTION OF HAIR FALL AND SCALP DISORDERS THROUGH ML AND IMAGE PROCESSING
AI can effectively detect hair and scalp disorders from images.
research Automating Hair Loss Labels for Universally Scoring Alopecia From Images
The AI system HairComb accurately scores hair loss severity, matching dermatologist assessments.
research A comparative study of linear and nonlinear ANNs as classifiers of animal hair fibers
Nonlinear artificial neural networks are better at identifying different types of animal hair than linear ones.
research Artificial intelligence in dermatology: а scoping review
AI in dermatology shows high accuracy in diagnosing skin diseases but needs more research for improvement.
research CZAS TO SZTUCZNA INTELIGENCJA: OD TEORII DO ROZWIĄZAŃ RATUJĄCYCH ŻYCIE
AI improves medical care by enhancing diagnosis and treatment for better patient outcomes.
research SYNERGIA AI I MEDYCYNY: SZANSE I WYZWANIA
AI is transforming healthcare by improving diagnostics and therapy, despite challenges with data and trust.
research 176 Characterising Neurotransmitter Signalling in Human Skin and Hair Follicles
Skin and hair cells release serotonin and histamine naturally, which could help improve skin health.
research A Comprehensive Review of Microneedles: Types, Materials, Processes, Characterizations and Applications
Microneedles are effective for drug delivery, vaccinations, fluid extraction, and treating hair loss, with advancements in manufacturing like 3D printing.
research Identification of Various Deficiencies Using Data Mining Techniques - A Survey
Data mining helps identify and address nutrition deficiencies affecting health.
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 Harnessing Deep Learning for Scalp and Hair Disease Classification: A Comparative Study of Convolutional Neural Networks Architectures
VGG16 and VGG19 are the most accurate for classifying scalp and hair diseases.
research The Dark Side of the Language: Syntax-Based Neural Networks Rivaling Transformers in Definitely Unseen Sentences
Syntax-based neural networks can match Transformers in handling unseen sentences.
research Detection of Meibomian Gland Dysfunction by in vivo Confocal Microscopy Based on Deep Convolutional Neural Network
The model can effectively help diagnose meibomian gland dysfunction automatically.
research Generative adversarial networks for anonymous acneic face dataset generation
The method creates realistic, anonymous acne face images for research, achieving 97.6% accuracy in classification.
research Malate-based polyester chemically shielded metal-phenolic networks coated artificial hair fibers with long-lasting antimicrobial and anti-inflammatory performance
research Deep Clustering via Center-Oriented Margin Free-Triplet Loss for Skin Lesion Detection in Highly Imbalanced Datasets
The new method improves skin cancer detection in imbalanced datasets.
research Trichoscopy of Alopecia Areata: Hair Loss Feature Extraction and Computation Using Grid Line Selection and Eigenvalue
Researchers developed an algorithm for self-diagnosing scalp conditions with high accuracy using smart device-attached microscopes.
research Quantitative analysis and development of alopecia areata classification frameworks
A new algorithm effectively classifies Alopecia Areata, aiding early detection and treatment.
research AB-MTEDeep Classifier Trained with AAGAN for the Identification and Classification of Alopecia Areata
The AI model accurately classifies Alopecia Areata with 96.94% accuracy.
research Innervated Biomaterials for Improved Cutaneous Wound Healing: A Review of Recent Advancements and Future Prospects
New biomaterials can improve wound healing by promoting nerve and tissue regeneration.
research Hair cluster detection model based on dermoscopic images
The new model detects hair clusters more accurately and efficiently, helping with early hair loss treatment and diagnosis.
research Trichoscopy and Computational Models for Hair and Scalp Disorders: Image Analysis, Quantification, and Clinical Integration
AI in hair and scalp analysis shows promise but lacks real-world clinical integration and validation.
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%.