research Identification and expression of the target gene SLC24A2 of oar-miR-377 and its novel SNPs effects on wool traits in sheep
The TT genotype of a specific SNP in sheep is linked to better wool quality.
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research Hair Follicle Classification and Hair Loss Severity Estimation Using Mask R-CNN
An intelligent system can classify hair follicles and measure hair loss severity with reasonable accuracy.
research Screened of long non-coding RNA related to wool development and fineness in Gansu alpine fine-wool sheep
Long non-coding RNAs help regulate wool fineness in Gansu alpine fine-wool sheep.
research DETECTION OF HAIR FALL AND SCALP DISORDERS THROUGH ML AND IMAGE PROCESSING
AI can effectively detect hair and scalp disorders from images.
research Leveraging deep neural networks to uncover unprecedented levels of precision in the diagnosis of hair and scalp disorders
A new AI model diagnoses hair and scalp disorders with 92% accuracy, better than previous models.
research Mind the Gap: A Solution to the Robustness Problem of Turing Patterns Through Patterning Mode Isolation
Pattern mode isolation improves the reliability and predictability of Turing patterns.
research NLKFill: high-resolution image inpainting with a novel large kernel attention
NLKFill improves high-resolution image inpainting by effectively capturing image details and enhancing speed.
research Research on Mental Stress Recognition of Depressive Disorders in Patients With Androgenic Alopecia Based on Machine Learning and Fuzzy K-Means Clustering
The FAW-FS algorithm improves depression recognition, and psychological interventions help AGA patients' mental health.
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 Comparative Analysis of Machine Learning Algorithms in Diagnosis of Polycystic Ovarian Syndrome
The Random Forest algorithm was the most accurate at diagnosing Polycystic Ovarian Syndrome.
research Deep Learning Approaches for Hair Disease Classification: A Comparative Analysis of MobileNetV2 and VGG19 Architectures
VGG19 is more accurate, but MobileNetV2 is faster and uses fewer resources.
research Trichoscopy of Alopecia Areata: Hair Loss Feature Extraction and Computation Using Grid Line Selection and Eigenvalue
Researchers developed an algorithm for self-diagnosing scalp conditions with high accuracy using smart device-attached microscopes.
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 AI06 ALUDWIG: an automated artificial intelligence-based assessment of female androgenic alopecia
ALUDWIG can help standardize female hair loss assessment from a single image.
research CircRNA-1926 Promotes the Differentiation of Goat SHF Stem Cells into Hair Follicle Lineage by miR-148a/b-3p/CDK19 Axis
circRNA-1926 helps goat stem cells turn into hair follicles by affecting miR-148a/b-3p and CDK19.
research Hair Disease Classification Using Convolutional Neural Network (CNN) Algorithm with VGG-16 Architecture
The system can accurately classify hair diseases with 94.5% accuracy using a CNN.
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 A modified Sobel filter-based automated numerical algorithm enables immediate trichoscopic assessment of hair diameter diversity in male and female pattern hair loss
A new computer tool quickly measures hair thickness differences in people with common types of hair loss.
research Genome Wide Differential Expression Profiles in Nevus Sebaceous Uncovered Low Expression of CDKN2AIP and Construction of a ceRNA Network
CDKN2AIP gene is less active in nevus sebaceous, affecting related RNA networks.
research Validation of alopecia coding in US claims data among women of childbearing age
The algorithm accurately identified alopecia in women of childbearing age using claims data.
research FRCNN based Deep Learning for Identification and Classification of Alopecia Areata
The model accurately detects alopecia areata with 84.3% accuracy.
research 1394 Long non-coding RNA AL136131.3 inhibits hair growth through mediating glycolysis in androgenetic alopecia
AL136131.3 slows hair growth by affecting energy processes in hair loss.
research 891 Comparison of phenotypes and transcriptomes of mouse skin-derived precursors and dermal mesenchymal stem cells
The search scheme SMRI is faster and more secure for retrieving encrypted data from the cloud.
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 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 identify genes related to wool traits in rabbits.
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 Enhanced stratification of male pattern hair loss using AI through novel loss region ratio analysis
AI improves accuracy and consistency in diagnosing male pattern hair loss.
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 Algorithms in Trichoscopy
Androgenetic alopecia is the only hair loss condition with specific diagnostic criteria in trichoscopy.
research A Feature-Preserving Hair Removal Algorithm for Dermoscopy Images
The algorithm effectively removes hair from skin images, improving melanoma diagnosis accuracy.