research Predicting Hair Loss with AI: A Deep Learning Framework Combining Genetic and Scalp Health Data
AI can predict hair loss by analyzing genetic, scalp, and lifestyle data.
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900-930 / 1000+ resultsresearch Advancing Hair Disease Diagnostics: A Deep Learning Approach Using Inception-ResNet v2 for Multi-Class Classification
The model accurately identifies hair diseases using deep learning.
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 Comparison of large language models in generating patient handouts for the dermatology clinic: A blinded study
ChatGPT is preferred for creating dermatology patient handouts, but all models can be useful with oversight.
research A case of multifocal acquired demyelinating sensory and motor neuropathy with whole body alopecia
Immunological treatment improved both neuropathy and alopecia.
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 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 A Mutational Hotspot in the 2B Domain of Human Hair Basic Keratin 6 (hHb6) in Monilethrix Patients
A common mutation in the hHb6 gene is linked to monilethrix, but other factors may also play a role.
research Real-World Outcomes and Healthcare Utilization of Lanadelumab in Spain: Insights from First Cohort of Difficult-to-Treat Hereditary Angioedema Cases
Lanadelumab greatly reduces hospital visits and angioedema episodes, improving life quality for hereditary angioedema patients.
research INTRADERMOTERAPIA CAPILAR: BENEFÍCIOS NO TRATAMENTO DA ALOPECIA
Hair intradermotherapy effectively treats hair loss and boosts self-esteem.
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 Methods of Transfer Learning for Multiclass Hair Disease Categorization
Transfer learning with three neural network architectures accurately classifies hair diseases.
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 Identification of Novel Mutations in Basic Hair Keratins hHb1 and hHb6 in Monilethrix: Implications for Protein Structure and Clinical Phenotype
New mutations in hair keratin genes can change hair structure and cause monilethrix, with nail issues more common in certain gene mutations.
research Mapping of monilethrix to the type II keratin gene cluster at chromosome 12q13 in three new families, including one with variable expressivity
Monilethrix is linked to the type II keratin gene on chromosome 12q13.
research BC05 Technological and clinical demonstration of a skin ageing analysis prototype
The prototype for analyzing skin aging works technically and clinically.
research Distinct mutations in human basic hair keratins 1 and 6 cause monilethrix: Implications for protein structure and clinical phenotype
research Mutation in human hair keratin hHb6 in monilethrix: clinical variation is not due to genetic variation.
research Rethinking pattern hair loss classification in the era of trichoscopy and artificial intelligence
A hybrid model using traditional methods, trichoscopy, and AI improves hair loss assessment.
research Modeling share dynamics by extracting competition structure
The model can predict website market shares by identifying competition among them.
research Analyse trichoskopischer Bilder mit tiefen neuronalen Netzen zur Diagnose und Aktivitätsbewertung von Alopecia areata – eine retrospektive Studie
Deep-learning models can effectively diagnose and assess Alopecia areata using scalp images.
research Deep Learning-based Automatic System for Diagnosis and Classification of Skin Dermatoses
The document concludes that an automatic system using deep learning can help diagnose skin disorders, but challenges and opportunities in this area remain.
research A Comparative Analysis of Large Language Model Accuracy for Image-Based Hair Disease Identification in Diverse Skin Tones
ChatGPT is more accurate at diagnosing hair disorders in lighter skin tones than darker ones.
research Investigating Different Deep learning Models for Classification of Folliculitis
GoogLeNet is the best model for identifying folliculitis.
research The pathogenesis model research of alopecia areata: from animal experiments to mathematical prediction models
Animal and mathematical models help understand and develop treatments for alopecia areata.
research Deep skin diseases diagnostic system with Dual-channel Image and Extracted Text
The AI model DIET-AI effectively diagnoses skin diseases as well as doctors.
research Convolutional Neural Networks for Non-Invasive Diagnosis of Androgenetic Alopecia using Dermoscopic Hair Images
Deep learning can improve non-invasive alopecia diagnosis using hair images.
research Bayesian measurement-error-driven hidden Markov regression model for calibrating the effect of covariates on multistate outcomes: Application to androgenetic alopecia
Model improves accuracy in predicting hair loss effects.
research Identification of Hypoxia and Mitochondrial-related Gene Signature and Prediction of Prognostic Model in Lung Adenocarcinoma
A gene-based model predicts lung adenocarcinoma outcomes and helps guide treatment decisions.
research Modeling using discriminant analysis of the possibility of occurrence and features of the course of various forms of urticaria in ukrainian women depending on the features of anthropo-somatotypological indicators
The models accurately predicted urticaria in Ukrainian women but struggled to differentiate between mild and severe cases based on body structure.