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.
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research Methods of Transfer Learning for Multiclass Hair Disease Categorization
Transfer learning with three neural network architectures accurately classifies hair diseases.
research Generative Adversarial Networks for Anonymous Acneic Face Dataset Generation
The method creates realistic, anonymous acne face images for research, achieving 97.6% accuracy in classification.
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 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 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 Evaluation of Automated Measurement of Hair Density Using Deep Neural Networks
Deep learning can accurately automate hair density measurement, with YOLOv4 performing best.
research Identification of Drug-Disease Associations Using Information of Molecular Structures and Clinical Symptoms via Deep Convolutional Neural Network
A new model can predict drug-disease links well, helping drug research.
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 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 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 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 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 Spironolactone for Treatment of Concomitant Female Pattern Hair Loss in Scarring Alopecia Patients
Spironolactone safely and effectively treats hair loss in female scarring alopecia patients.
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 Impact of Artificial Intelligence on Healthcare
AI is revolutionizing healthcare by improving diagnosis, treatment, and monitoring, but still needs close supervision.
research Androgen Signaling Regulates SARS-CoV-2 Receptor Levels and Is Associated with Severe COVID-19 Symptoms in Men
Male hormones affect COVID-19 severity and certain drugs targeting these hormones could help reduce the risk.
research Abstracts
The document reports findings on genetic research, including ethical concerns about genome editing, improved diagnosis of mitochondrial mutations, solving inherited eye diseases, confirming gene roles in epilepsy, linking a gene to aneurysms, and identifying genes associated with age-related macular degeneration.
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 American Society for Laser Medicine and Surgery - 2018 Late-Breaking Abstracts
New treatments and technologies in laser medicine show promise for improving skin conditions, fat reduction, cancer treatment, wound healing, and hair restoration.
research Glycogen Phosphorylase Inhibitor Promotes Hair Growth via Protecting from Oxidative Stress and Regulating Glycogen Breakdown in Human Hair Follicles
A new compound, HTPI, promotes hair growth by protecting cells from damage and regulating energy use.
research Review on Polycystic Ovarian Syndrome (PCOS) in Case of Pregnancy
Women with PCOS face many health risks, but exercise, a healthy diet, and weight management can help.
research Challenges of Securing Insurance Approval for Oral Tofacitinib Treatment of Alopecia Areata: A Multi-Institutional Retrospective Review
Getting insurance to cover the hair loss treatment tofacitinib is hard because it's not officially approved for that use.
research Imaging Tools for Noninvasive Hair Assessment
New imaging tools help doctors better examine hair and scalp health without surgery.
research Oxytocin Receptor Is Present in Keratinocytes Near Touch and Pain Sensory Neurons
Oxytocin receptors are found in skin cells near touch and pain neurons.
research Enhanced Hair Disease Classification Using Deep Learning
The model accurately classifies hair conditions with 97% accuracy.
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 Development and Assessment of an Artificial Intelligence-Based Tool for Skin Condition Diagnosis by Primary Care Physicians and Nurse Practitioners in Teledermatology Practices
The AI tool helped primary care doctors and nurse practitioners diagnose skin conditions more accurately.
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 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.