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 Diagnosis of Scalp Disorders using Machine Learning and Deep Learning Approach -- A Review
Deep learning effectively diagnoses scalp disorders, but improvements are needed.
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 Evaluation of Automated Measurement of Hair Density Using Deep Neural Networks
Deep learning can accurately automate hair density measurement, with YOLOv4 performing best.
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 MSF-VMDNet for multi class segmentation of skin cancer whole slide images using a multi frequency dual encoder network
MSF-VMDNet accurately segments skin cancer images better than existing methods.
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 Scalp Disorder Imaging: How Deep Learning and Explainable Artificial Intelligence are Revolutionizing Diagnosis and Treatment
Deep learning and explainable AI are improving scalp disorder diagnosis, but challenges in transparency and data quality remain.
research Artificial Intelligence Deep Learning Ultrasound Discrimination of Cosmetic Fillers
AI can accurately identify some cosmetic fillers in ultrasound images but needs improvement for others.
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.