research A Hybrid Transfer Learning Approach Using Obesity Data for Predicting Cardiovascular Diseases Incorporating Lifestyle Factors
Adding obesity data to machine learning models improves heart disease prediction accuracy.
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research Molecular heterogeneity of quiescent melanocyte stem cells revealed by single-cell RNA-sequencing
Different types of inactive melanocyte stem cells exist with unique characteristics and potential to develop into other cells.
research A human prenatal skin cell atlas reveals immune cell regulation of skin morphogenesis
Immune cells are essential for early hair and skin development and healing.
research Ethnomedicinal and Phytochemical Studies of Eclipta alba (A Review)
Eclipta alba shows promise for treating various health issues and needs more research.
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 Weakly-Supervised Hair SEM Microscope Image Segmentation Using a Priori Structure Information
The method improves hair image segmentation accuracy while reducing annotation costs.
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 Prediction of Alopecia Areata using CNN
A new CNN model can detect Alopecia Areata with 98% accuracy.
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 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 A Combinatorial Tweet Clustering Methodology Utilizing Inter and Intra Cosine Similarity
The method effectively grouped tweets into categories without knowing the number of groups beforehand.
research A discriminant multi-scale histopathology descriptor using dictionary learning
The new image descriptor helps identify skin cancer structures with good accuracy.
research KRDQN: An Interpretable Prediction Framework for Adverse Drug Reactions via Knowledge–Graph Reinforced Deep Q-Learning
KRDQN effectively predicts adverse drug reactions with high accuracy and clear explanations.
research A Genome-Wide Association Study and Machine-Learning Algorithm Analysis on the Prediction of Facial Phenotypes by Genotypes in Korean Women
The model accurately predicts skin conditions in Korean women using genetic information, aiding personalized skincare.
research Methods of Transfer Learning for Multiclass Hair Disease Categorization
Transfer learning with three neural network architectures accurately classifies hair diseases.
research Quantitative analysis and development of alopecia areata classification frameworks
A new algorithm effectively classifies Alopecia Areata, aiding early detection and treatment.
research Artificial neural networks algorithms for prediction of human hair loss related autoimmune disorder problem
Artificial neural networks can accurately diagnose Alopecia Areata.
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 ANTI‐HAIR KERATIN MONOCLONAL ANTIBODY (HKN‐2)
HKN-2 antibody targets specific skin and hair cells, showing keratin complexity.
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 Hair analysis based on medical history and spatial-temporal data
Machine learning can predict hair health accurately using personal data.
research DETECTION OF HAIR FALL AND SCALP DISORDERS THROUGH ML AND IMAGE PROCESSING
AI can effectively detect hair and scalp disorders from images.
research FRCNN based Deep Learning for Identification and Classification of Alopecia Areata
The model accurately detects alopecia areata with 84.3% accuracy.
research An Early Hair Loss Detection and Prediction Method Based on Machine Learning
Machine learning can accurately predict hair loss early, improving treatment options.
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 Penerapan Algoritma Naive Bayes untuk Prediksi Kerontokan Rambut
Naive Bayes algorithm can help predict hair loss risk early.
research AI04 A novel machine learning software application for prognosticating cutaneous malignant melanoma based on data from 78 351 patients from the Surveillance, Epidemiology, and End Results (SEER) database
The new AI software predicts melanoma outcomes more accurately than traditional methods.
research An Analysis of Alopecia Areata Classification Framework for Human Hair Loss Based on VGG-SVM Approach
The VGG-SVM method accurately identifies and classifies stages of Alopecia Areata and other hair loss conditions.
research HERBSNAP: Advanced Classification of Bhringaraja and Honegone Herbal Species
Machine learning can accurately tell apart False Daisy and Smooth Joy Weed.
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.