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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 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 DEEP REINFORCEMENT LEARNING FOR SCALABLE CONTROL OF BOOLEAN MODELS IN THE CONTEXT OF CELLULAR REPROGRAMMING
pbn-STAC effectively finds strategies for cellular reprogramming using deep reinforcement learning.
research An algorithm for the diagnosis of female hair loss
The algorithm can effectively diagnose different types of female hair loss with proper history, examination, and tests.
research Algorithms in Trichoscopy
Androgenetic alopecia is the only hair loss condition with specific diagnostic criteria in trichoscopy.
research FRCNN based Deep Learning for Identification and Classification of Alopecia Areata
The model accurately detects alopecia areata with 84.3% accuracy.
research Perbandingan Algoritma Multi-Thresholding, Konversi Biner, Low-Pass Filtering pada Segmentasi Rambut Kaki
Multi-thresholding is the best method for separating hair from skin in laser hair removal.
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 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 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 Screening of circRNAs Associated with Secondary Wool Follicle Development in Fine-Wool Sheep and Construction of Their ceRNA Network
Key circRNAs play a role in wool follicle development, aiding in breeding better quality wool sheep.
research Penerapan Algoritma Naive Bayes untuk Prediksi Kerontokan Rambut
Naive Bayes algorithm can help predict hair loss risk early.
research Deep Clustering via Center-Oriented Margin Free-Triplet Loss for Skin Lesion Detection in Highly Imbalanced Datasets
The new method improves skin cancer detection in imbalanced datasets.
research Construction of regulatory network for alopecia areata progression and identification of immune monitoring genes based on multiple machine-learning algorithms
Researchers found four genes that could help diagnose severe alopecia areata early.
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 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 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 Automating Hair Loss Labels for Universally Scoring Alopecia From Images
The AI system HairComb accurately scores hair loss severity, matching dermatologist assessments.
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 Enhancing Low-Light Sports Motion Images with Improved Bilateral Filtering and Auto MSRCR
The method greatly improves low-light sports images' quality and reduces artifacts.
research Optimized polycystic ovarian disease prognosis and classification using AI based computational approaches on multi-modality data
AI can improve early diagnosis and classification of PCOS, aiding in prevention of related health issues.
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 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 Identification of a recurrent nonsense mutation in HR gene responsible for atrichia with papular lesions in two Kashmiri families
A mutation in the HR gene causes a rare form of irreversible hair loss in two Kashmiri families. Whole exome sequencing is effective for finding such mutations.
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 ISID0199 – Computer vision AI-based androgenetic alopecia analysis using a novel mobile web app.
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 A New Technique for Quantitative Analysis of Hair Loss in Mice Using Grayscale Analysis
A new method measures mouse hair loss using shades of gray.