research Quantitative analysis and development of alopecia areata classification frameworks
A new algorithm effectively classifies Alopecia Areata, aiding early detection and treatment.
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30-60 / 1000+ results 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 Hair and scalp disease detection using deep learning
Deep learning can effectively detect hair and scalp diseases early.
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 Deep Learning Based Non-Invasive Framework for Nutritional Deficiency Detection Using Hair and Nail Images
A deep learning method can detect nutritional deficiencies from hair and nail images with 89% accuracy.
research From Diagnosis to Prognosis: A Scoping Review of Artificial Intelligence in Alopecia Research
AI in alopecia research needs better tools for predicting treatment outcomes and ensuring fairness.
research DETECTION OF HAIR FALL AND SCALP DISORDERS THROUGH ML AND IMAGE PROCESSING
AI can effectively detect hair and scalp disorders from images.
research BaldPredict: AI-Driven Prediction Model for Alopecia Areata
AI can improve alopecia areata diagnosis with high accuracy.
research Automated early detection of androgenetic alopecia using deep learning on trichoscopic images from a Korean cohort: a retrospective model development and validation study
The model accurately detects early-stage hair loss using images.
research Methods of Transfer Learning for Multiclass Hair Disease Categorization
Transfer learning with three neural network architectures accurately classifies hair diseases.
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 Deep Learning-based Trichoscopic Image Analysis and Quantitative Model for Predicting Basic and Specific Classification in Male Androgenetic Alopecia
A deep learning model accurately predicts male hair loss types using scalp 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 Prediction of Alopecia Areata using CNN
A new CNN model can detect Alopecia Areata with 98% accuracy.
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 Hair Tone Estimation at Roots via Imaging Device with Embedded Deep Learning
The device accurately estimates natural hair color at the roots in real time.
research PEDL-XAI: A Hybrid Probabilistic Ensemble Deep Learning Approach for Hair Disorder Diagnosis
The new AI system accurately diagnoses hair disorders and offers personalized treatment recommendations.
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 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 1301 STIM1, but not STIM2, is the calcium sensor critical for sweat secretion
STIM1 is essential for sweat secretion.
research Abnormal neuronal differentiation and mitochondrial dysfunction in hair follicle-derived induced pluripotent stem cells of schizophrenia patients
Schizophrenia patients' stem cells show abnormal neuron development and mitochondrial issues.
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 574 A deep learning classifier for the analysis of tiger tail banding in trichothiodystrophy
A deep learning model was developed to help diagnose trichothiodystrophy by analyzing hair patterns.
research Human dermal fibroblast‐derived secretory proteins for regulating nerve restoration: A bioinformatic approach
Human dermal fibroblast proteins help restore nerves during healing.
research NLKFill: high-resolution image inpainting with a novel large kernel attention
NLKFill improves high-resolution image inpainting by effectively capturing image details and enhancing speed.
research HERBSNAP: Advanced Classification of Bhringaraja and Honegone Herbal Species
Machine learning can accurately tell apart False Daisy and Smooth Joy Weed.
research A Comprehensive Survey on Vitiligo Detection Using Deep Learning
Better datasets and methods are needed for reliable vitiligo detection using deep learning.
research SYNERGIA AI I MEDYCYNY: SZANSE I WYZWANIA
AI is transforming healthcare by improving diagnostics and therapy, despite challenges with data and trust.
research The Dark Side of the Language: Pre-trained Transformers in the DarkNet
Pre-trained Transformers need extreme retraining to perform well on DarkNet data.
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.