research The stem cell niche
Stem cell niches are essential for tissue health and repair.
Search
for
Sort by
Research
120-150 / 1000+ resultsresearch Risk of Suicide, Hair Loss, and Aspiration with GLP1-Receptor Agonists and Other Diabetic Agents: A Real-World Pharmacovigilance Study
GLP1-RAs may have higher reports of suicidal events and hair loss compared to other diabetes drugs.
research Evaluation of Guava Leaf Extract Hair Tonic (Psidium Guajava L.) on Cosmetology Education Students at Medan State
Guava leaf extract hair tonic is safe, well-liked, and may help strengthen hair and scalp.
research The Impact of Routine Skin Care on the Quality of Life
A good skin care routine improves happiness, self-esteem, and overall quality of life.
research CNN-KNN Model for Assessing Hair Health in Telogen Effluvium
The model accurately predicts hair breakage in Telogen Effluvium, aiding early detection and treatment.
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 HERBSNAP: Advanced Classification of Bhringaraja and Honegone Herbal Species
Machine learning can accurately tell apart False Daisy and Smooth Joy Weed.
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 The Cohen hair loss classification system
Dr. Bernard Cohen created a new system to classify hair loss using numbers and a detailed scalp map.
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 Derivation and validation of the Systemic Lupus International Collaborating Clinics classification criteria for systemic lupus erythematosus
The new criteria for classifying lupus are more accurate and comprehensive.
research An Explainable AI-Based Decision Support System for Teaching and Classifying Hair Loss Types
The AI system accurately classifies hair loss types and explains its decisions.
research Pre-trained classification of scalp conditions using image processing
The system can automatically classify scalp conditions with 85% accuracy.
research Classification of male-pattern hair loss
No current system perfectly classifies male-pattern hair loss, indicating a need for a new system for better diagnosis and treatment.
research Derivation and Validation of Systemic Lupus International Collaborating Clinics Classification Criteria for Systemic Lupus Erythematosus
The updated criteria improve the accuracy of diagnosing lupus.
research Derivation and validation of the Systemic Lupus International Collaborating Clinics classification criteria for systemic lupus erythematosus
The new SLICC criteria for diagnosing lupus are more sensitive and accurate than the old criteria.
research The New Classification Criteria of Systemic Lupus Erythematosus
The 2012 SLICC criteria provide an updated method for classifying Systemic Lupus Erythematosus.
research Big Self-Supervised Models Advance Medical Image Classification
Self-supervised learning improves medical image classification accuracy.
research Improved Hidden Markov Algorithm Based on Bayes in Low Dose CT Images
The improved algorithm enhances low-dose CT image quality significantly better than other methods.
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 In Vivo Confocal Microscopy for Automated Detection of Meibomian Gland Dysfunction: A Study Based on Deep Convolutional Neural Networks
research MultiKano: an automatic cell type annotation tool for single-cell multi-omics data based on Kolmogorov–Arnold network and data augmentation
MultiKano accurately identifies cell types in complex data better than existing methods.
research FRCNN based Deep Learning for Identification and Classification of Alopecia Areata
The model accurately detects alopecia areata with 84.3% accuracy.
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.
research Multi-Class Support Vector Machine Classification for Detecting Alopecia Areata and Scalp Diseases
The method accurately detects and classifies scalp diseases, including alopecia areata, with 89.3% accuracy.
research Automated Trichoscopic Analysis for Hair Disorder Classification Using Semantic Segmentation
An automated system can accurately classify hair disorders using image analysis.
research Curl pattern classification: A potential tool for communication and risk stratification
Classifying curl patterns might help doctors assess and treat hair loss better.
research A DEEP LEARNING APPROACH FOR DIAGNOSIS OF COVID-19 INFECTION AND ITS RELATED FACTORS: A POPULATION-BASED STUDY
The random forest model effectively helps diagnose COVID-19 using key factors like age and symptoms.
research 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 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.