research Objective quantification of chemotherapy-induced madarosis: a pilot study of an automated computer vision pipeline for eyebrow density assessment
The tool accurately tracks eyebrow hair loss in chemotherapy patients.
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research ScalpEye: A Deep Learning-Based Scalp Hair Inspection and Diagnosis System for Scalp Health
ScalpEye accurately diagnoses scalp issues like dandruff and hair loss.
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 Analysis of modern approaches to hair care: An overview of products and techniques
Personalized hair care using modern techniques and science is essential for healthy hair.
research How good is artificial intelligence (AI) 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 Using artificial intelligence to compute Severity of Alopecia Tool scores
AI can accurately measure hair loss severity in alopecia areata.
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 Skin image analysis for detection and quantitative assessment of dermatitis, vitiligo and alopecia areata lesions: a systematic literature review
Computer vision techniques can help detect and assess skin conditions like vitiligo, alopecia areata, and dermatitis.
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.
research Harnessing Deep Learning for Scalp and Hair Disease Classification: A Comparative Study of Convolutional Neural Networks Architectures
VGG16 and VGG19 are the most accurate for classifying scalp and hair diseases.
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 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 DETECTION OF HAIR FALL AND SCALP DISORDERS THROUGH ML AND IMAGE PROCESSING
AI can effectively detect hair and scalp disorders from images.
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 Amplitude-guided deep reinforcement learning for semi-supervised layer segmentation
The new method improves accuracy in segmenting scalp tissue layers.
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 A Comprehensive Survey on Vitiligo Detection Using Deep Learning
Better datasets and methods are needed for reliable vitiligo detection using deep learning.
research Quantitative analysis and development of alopecia areata classification frameworks
A new algorithm effectively classifies Alopecia Areata, aiding early detection and treatment.
research Regenerative Strategies for Androgenetic Alopecia: Evidence, Mechanisms, and Translational Pathways
New regenerative treatments show promise in improving hair growth for androgenetic alopecia.
research Artificial neural networks algorithms for prediction of human hair loss related autoimmune disorder problem
Artificial neural networks can accurately diagnose Alopecia Areata.
research Trichoscopy and Computational Models for Hair and Scalp Disorders: Image Analysis, Quantification, and Clinical Integration
AI in hair and scalp analysis shows promise but lacks real-world clinical integration and validation.
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 Hair cluster detection model based on dermoscopic images
The new model detects hair clusters more accurately and efficiently, helping with early hair loss treatment and diagnosis.
research 575 An extract of Leontopodium alpinum prolongs anagen phase in human hair follicles ex vivo
Leontopodium alpinum extract may help reduce hair shedding by keeping hair in the growth phase longer.
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 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 A Quantitative Measurement Method for Nuclear-Pleomorphism Scoring in Breast Cancer
A new method accurately measures cell changes in breast cancer.
research KEBOT: An Artificial Intelligence Based Comprehensive Analysis System for FUE Based Hair Transplantation
The KEBOT system is a highly accurate AI tool for analyzing hair transplants.
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 Classification Framework for Healthy Hairs and Alopecia Areata: A Machine Learning (ML) Approach
Machine learning can accurately identify Alopecia Areata, aiding in early detection and treatment of this hair loss condition.