research Deep Learning-Based Dermatological Condition Detection: A Systematic Review With Recent Methods, Datasets, Challenges, and Future Directions
Deep learning helps detect skin conditions and is advancing dermatology diagnosis and treatment.
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research Enhanced Hair Disease Classification Using Deep Learning
The model accurately classifies hair conditions with 97% accuracy.
research Investigating Different Deep Learning Models for Classification of Folliculitis
GoogLeNet is the best model for identifying folliculitis.
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 Learning-Based Automatic System for Diagnosis and Classification of Skin Dermatoses
The document concludes that an automatic system using deep learning can help diagnose skin disorders, but challenges and opportunities in this area remain.
research An Approach to Detect Alopecia Areata Hair Disease Using Deep Learning
Deep learning can accurately detect Alopecia Areata with up to 98.3% accuracy.
research Scalp Disease Analysis Using Deep Learning Models
Deep learning models can analyze scalp diseases effectively.
research Deep Learning-Based Trichoscopic Image Analysis and Quantitative Model for Predicting Basic and Specific Classification in Male Androgenetic Alopecia
A deep learning model accurately predicts male hair loss types using scalp images.
research Deep Learning Model to Predict Sentinel Lymph Node Status in Melanoma Patients
The AI model somewhat predicts lymph node status in melanoma patients using skin sample images.
research Evaluation of Automated Measurement of Hair Density Using Deep Neural Networks
Deep learning can accurately automate hair density measurement, with YOLOv4 performing best.
research Deep Review on Alopecia Areata Diagnosis for Hair Loss-Related Autoimmune Disorder
Machine learning and deep learning can effectively diagnose alopecia areata.
research Optimizing Skin Disease Diagnosis: Harnessing Online Community Data With Contrastive Learning and Clustering Techniques
Researchers improved a skin disease diagnosis model using online images, achieving up to 49.64% accuracy.
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 Methods of Transfer Learning for Multiclass Hair Disease Categorization
Transfer learning with three neural network architectures accurately classifies hair diseases.
research Deep Hair Phenomics: Implications in Endocrinology, Development, and Aging
A new tool can analyze hair to detect changes due to hormones, genetics, and aging.
research Inferring Spatially Resolved Transcriptomics Data from Whole Slide Images for the Assessment of Colorectal Tumor Metastasis: A Feasibility Study
Using deep learning to predict gene expression from images could help assess colorectal cancer metastasis.
research Hair and Scalp Disease Detection Using Machine Learning and Image Processing
The machine learning model accurately detected hair loss and scalp diseases using processed images.
research Detecting Shortcut Learning for Fair Medical AI Using Shortcut Testing
The ShorT method can detect and help reduce bias in medical AI by identifying shortcut learning.
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 How Good Is Artificial Intelligence at Solving Hairy Problems? A Review of AI Applications in Hair Restoration and Hair Disorders
AI is effective in diagnosing and treating hair disorders, including detecting hair loss and scalp conditions with high accuracy, but it should supplement, not replace, doctor-patient interactions.
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 Hair Disease Classification Using Convolutional Neural Network Algorithm with VGG-16 Architecture
The system can accurately classify hair diseases with 94.5% accuracy using a CNN.
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 Research Techniques Made Simple: Optical Clearing and Three-Dimensional Volumetric Imaging of Skin Biopsies
3D imaging of skin biopsies offers better accuracy but is time-consuming and can't clear melanin.
research American Society for Laser Medicine and Surgery 2019 Late Breaking Abstracts
The conference reported improvements in muscle volume, skin cancer diagnosis, facial and vaginal rejuvenation, and hair growth using various laser treatments.
research Automated Machine Learning Analysis of Patients With Chronic Skin Disease Using a Medical Smartphone App: Retrospective Study
Machine learning can predict symptoms and quality of life in chronic skin disease patients using smartphone app data, and shows that app use varies with patient characteristics.
research Editorial: Machine Learning Techniques on Gene Function Prediction Volume II
Machine learning is effective in predicting gene functions and their relationships with diseases.
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 Classification Framework for Healthy Hair and Alopecia Areata: A Machine Learning Approach
Machine learning can accurately identify Alopecia Areata, aiding in early detection and treatment of this hair loss condition.
research A Machine Learning-Based Scalp Hair Inspection and Diagnosis System for Scalp Health
The system can automatically identify different hair and scalp conditions using machine learning.