research Patient Validation of Estimation of Health Utility Values in Alopecia Areata
Patients with Alopecia Areata are willing to trade life duration for better quality of life.
Search
for
Sort by
Research
630-660 / 1000+ results research HairSentinel: a time-aware anomaly detection framework for forecasting hairfall trends using temporal fusion transformers
"HairSentinel" accurately detects hairfall trends using simple user data, helping identify health risks early.
research 701 Rethinking alopecia scores: Correlating measures of hair loss with established photographic scoring systems
The conclusion suggests that a new system for measuring hair loss could be created using automated analysis of photographs.
research Enhanced Hair Disease Classification Using Deep Learning
The model accurately classifies hair conditions with 97% accuracy.
research Supplemental Materials: Machine Learning Applications in Androgenetic Alopecia: A Systematic Review
research Supplemental Materials: Machine Learning Applications in Androgenetic Alopecia: A Systematic Review
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 Rapid Screening of Anticoagulation Compounds for Biological Target-Associated Adverse Effects Using a Deep-Learning Framework in the Management of Atrial Fibrillation
The framework helps predict adverse effects of blood thinners, improving drug selection for atrial fibrillation.
research 397 Predictive modeling of drug response and mechanism of action in alopecia areata clinical trials
Researchers found three different ways drugs work to treat hair loss from alopecia areata and identified key factors for personalized treatment.
research Trichoscopy for common hair loss diseases: Algorithmic method for diagnosis
The conclusion is that an algorithm using trichoscopy helps diagnose different types of hair loss but may need updates and a biopsy if results are unclear.
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 NEUROSENSORY ECOLOGY IN THE JEB
Different species have unique sensory adaptations to perceive their environments.
research Faculty Opinions recommendation of A new classification of pattern hair loss that is universal for men and women: basic and specific (BASP) classification.
The BASP classification is a detailed system for categorizing hair loss in both men and women, but it may be complex for beginners and not fully suitable for grading female hair loss.
research A discriminant multi-scale histopathology descriptor using dictionary learning
The new image descriptor helps identify skin cancer structures with good accuracy.
research Additional methods for diagnosing alopecia and appraising their severity.
The document concludes that objective methods are important for diagnosing different types of alopecia and monitoring treatment, and standardizing these techniques is necessary.
research A Simple Technique for Revealing the Surface Pattern of Hair
A simple method can show hair's surface pattern.
research An Evaluation System to Enhance Patient Selection for Alopecia-Reducing Surgery
The evaluation system improved patient selection for hair loss surgery, leading to better results and satisfaction.
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 A Simple Decision Tree Suited for Identification of Early Oral Drug Candidates With Likely Pharmacokinetic Nonlinearity by Intestinal CYP3A Saturation
The decision tree can predict drug absorption issues with good accuracy but needs more validation and adjustments for other factors.
research Azimuthal Scattering from Elliptical Hair Fibers
Light scatters differently from elliptical hair fibers than from circular ones, and a new model better predicts this behavior, especially for shiny highlights.
research Scattering from Elliptical Hair Fibers Based on Microfacet Theory
research Hair Loss Diagnosis Using Artificial Neural Networks
Neural networks can effectively predict hair loss.
research Light scattering from human hair fibers
Researchers developed a new model for more realistic computer graphics of hair by considering how light scatters on hair fibers.
research A Segmental Approach to Scoring Hair Density from Global Images: Introducing the Scalp Coverage Scoring Method for Clinical Trials and Practice
The Scalp Coverage Scoring method reliably measures hair density from images.
research Data-driven strategies for drug repurposing: insights, recommendations, and case studies
Data-driven methods can effectively identify existing drugs for new uses, especially in cancer, infections, and respiratory diseases.
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 Congress abstracts SPEDM
The Bethesda system is effective for identifying thyroid cancer but has low sensitivity.
research Peer Review #3 of "Computational drug repositioning based on side-effects mined from social media (v0.2)"
The study improved and was accepted despite initial concerns about data clarity, methodology, and potential overfitting.
research Analysis of trichoscopic images using deep neural networks for the diagnosis and activity assessment of alopecia areata – a retrospective study
AI can accurately diagnose and assess alopecia areata using scalp images.
research The inheritance of common baldness: Two B or not two B ?
Common baldness is likely inherited through multiple genes, not just one.