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.
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research Two mutations at KRT74 and EDAR synergistically drive the fine-wool production in Chinese sheep
Two mutations in KRT74 and EDAR genes cause sheep to have finer wool.
research Two-Stage Machine Learning-Based GWAS for Wool Traits in Central Anatolian Merino Sheep
Machine learning can effectively identify genes to improve wool quality in sheep.
research Automating Hair Loss Labels for Universally Scoring Alopecia From Images
The AI system HairComb accurately scores hair loss severity, matching dermatologist assessments.
research ISID1394 - Long non-coding RNA AL136131.3 inhibits hair growth through mediating glycolysis in androgenetic alopecia
The RNA AL136131.3 slows down hair growth and speeds up hair loss by affecting sugar breakdown in hair follicles.
research CHROMALENS PRECISION MAPPING AS AN INNOVATIVE SYSTEM FOR MICROZONAL HAIR ANALYSIS: STRUCTURE, ALGORITHM, AND COMPARISON WITH CLASSICAL COLORING TECHNIQUES
research Long non-coding RNA AL136131.3 inhibits hair growth through mediating PPARγ in androgenetic alopecia
A specific RNA molecule blocks hair growth by affecting a protein related to hair loss conditions.
research Systematic Analysis of Non-coding RNAs Involved in the Angora Rabbit (Oryctolagus cuniculus) Hair Follicle Cycle by RNA Sequencing
Non-coding RNAs play key roles in the hair growth cycle of Angora rabbits.
research Quantifying Alopecia Areata via Texture Analysis to Automate the SALT Score Computation
Researchers created a fast, accurate computer program to measure hair loss in alopecia areata patients.
research Understanding hair disorders through artificial intelligence: DALLE's role in image creation
DALL-E 2 can create realistic hair images but struggles with specific hair disorders.
research Enhancing Hairfall Prediction: A Comparative Analysis of Individual Algorithms and An Ensemble Method
Combining multiple algorithms predicts hair fall more accurately than using single algorithms.
research Penerapan Algoritma Naive Bayes untuk Prediksi Kerontokan Rambut
Naive Bayes algorithm can help predict hair loss risk early.
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 Coupled 3D reconstruction of sparse facial hair and skin
The new algorithm accurately captures both facial hair and skin in 3D using a camera-based system.
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 Optimized VGG19 Architecture for Precise and Efficient Multi-Class Hair Disease Classification
The optimized VGG19 model accurately classifies hair diseases with 98.64% accuracy.
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 Gene variants associated with acne vulgaris presentation and severity: a systematic review and meta-analysis
Certain gene variants can influence acne risk and severity.
research A homozygous missense mutation in the fibroblast growth factor 5 gene is associated with the long-hair trait in Angora rabbits
A specific gene mutation causes long hair in Angora rabbits.
research Patient Selection, Hair Transplant Design, and Hairstyle
Dr. Norwood's analysis highlights the need for careful patient selection and strategic hair transplant design to create a natural-looking hair density.
research Genetic variation in the ovine KAP22-1 gene and its effect on wool traits in Egyptian sheep
Certain genetic changes in the KAP22-1 gene are linked to better wool quality in Egyptian sheep.
research Genome-wide detection and sequence conservation analysis of long non-coding RNA during hair follicle cycle of yak
Different long non-coding RNAs in yaks change during hair growth cycles and are involved in key growth pathways.
research Identification and Expression of the Target Gene SLC24A2 of oar-miR-377 and Its Novel SNPs Effects on Wool Traits in Sheep
A specific genetic variation affects wool quality in sheep.
research GAN-Based ROI Image Translation Method for Predicting Image after Hair Transplant Surgery
The new method predicts post-hair transplant images more accurately than other methods.
research Cost-effectively dissecting the genetic architecture of complex wool traits in rabbits by low-coverage sequencing
Low-coverage sequencing is a cost-effective way to find genetic factors affecting rabbit wool traits.
research A Three-Step Diagnostic Algorithm for Alopecia: Pattern Analysis in Trichoscopy
A new method improves alopecia diagnosis using non-invasive steps.
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 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.
research DEEP REVIEW ON ALOPECIA AREATA DIAGNOSIS FOR HAIR LOSS-RELATED AUTOIMMUNE DISORDER PROBLEM
Machine learning and deep learning can effectively diagnose alopecia areata.