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.
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research Critical study of hair growth analysis with computer-assisted methods
The Trichoscan system was found to be inaccurate for measuring hair growth, needing better software to be useful.
research 1040 Photographing alopecia - How many pixels are needed for clinical evaluation?
Higher resolution images are needed to identify scarring and fine hair in alopecia.
research Deep Learning-Powered Hair Disease Diagnosis: A ResNet50 Approach for Scalable and Accurate Classification
The model accurately diagnoses hair diseases with 95% accuracy using deep learning.
research The repression of mètis within digital organizations
Over-reliance on automation limits human problem-solving in emergencies.
research TrichoScan: combining epiluminescence microscopy with digital image analysis for the measurement of hair growth in vivo.
TrichoScan accurately measures hair growth and showed improved hair counts and thickness after finasteride treatment.
research TrichoScan
TrichoScan accurately measures hair growth and loss, showing increased hair counts and thickness with treatment.
research Research on hair removal algorithm of dermatoscopic images based on maximum variance fuzzy clustering and optimization Criminisi algorithm
The new hair removal algorithm for skin images works better for detecting and fixing hair, improving melanoma diagnosis.
research Role of Platelet-rich Plasma in the Management of Androgenetic Alopecia
PRP helps hair growth in common hair loss disorder.
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 Skinformatics: Navigating the big data landscape of dermatology
Clinicians and researchers must stay informed about big data to improve dermatology care.
research A Comprehensive Review of Alopecia Areata Detection Using Self-Supervised Auto ML Models: Systematic Insights and Emerging Challenges
AI models are effective for detecting alopecia areata but face challenges like explaining results and data bias.
research Unraveling the molecular basis of ROS-mediated cell wall biomechanics during Arabidopsis root hair cell growth
ROS influences the growth and structure of Arabidopsis root hairs.
research ISID0197 - Quantitative analysis of hair loss in mice utilizing imageJ improves the efficacy evaluation of alopecia areata induction in the C3H/HeJ mouse model
A new image-based method improves accuracy in measuring hair loss in mice.
research A Critical Evaluation of Evaluations for Long-form Question Answering
Current methods can't accurately predict which long-form answers people prefer; evaluations should consider different answer qualities separately.
research Natural swing frequency of human hair - a novel method to quantify natural hair collective movements
Human hair movement is affected by its inner structure and chemical treatments.
research Adipose tissue-derived stromal vascular fraction in regenerative medicine: a brief review on biology and translation
Fat tissue-derived cells show promise for repairing body tissues, but more research and regulation are needed for safe use.
research The emerging progress on wound dressings and their application in clinic wound management
Future wound dressings will be smart, multifunctional, and improve personalized medicine.
research Toward a Diagnostic Score in Cushing's Syndrome
The document suggests creating a validated score to diagnose Cushing's Syndrome and considers plasma steroid profiling as a simpler diagnostic method.
research LabeledIn: Cataloging labeled indications for human drugs
Researchers created LabeledIn, a detailed list of drug uses, showing the importance of human input in making such lists.
research Discrimination between basal cell carcinoma and hair follicles in skin tissue sections by Raman micro-spectroscopy
Raman micro-spectroscopy can help distinguish basal cell carcinoma from hair follicles in skin tissue.
research Advancements in 3D skin bioprinting: processes, bioinks, applications and sensor integration
3D skin bioprinting has advanced but still faces challenges like safety and the need for better integration with sensors.
research Integrated flow injection-solid phase spectrophotometric determination of minoxidil
New method measures minoxidil concentration faster, more accurately, and automatically.
research Dermoscopy: not just for dermatologists
Dermoscopy is useful for many health professionals, not just dermatologists, in improving skin condition diagnoses and reducing unnecessary biopsies.
research The atypical ‘hippocampal’ glutamate receptor coupled to phospholipase D that controls stretch‐sensitivity in primary mechanosensory nerve endings is homomeric purely metabotropic GluK2
A special receptor in sensory nerve endings helps control how they respond to stretching.
research Follicular unit extraction hair transplant automation: Options in overcoming challenges of the latest technology in hair restoration with the goal of avoiding the line scar
Follicular Unit Extraction (FUE) hair transplant is less invasive, leaves no scars, and has quicker recovery times, but it's more time-consuming and challenging. Automation helps speed up the process and improve graft survival, reducing the need for traditional strip surgery.
research Detection of Meibomian Gland Dysfunction by in vivo Confocal Microscopy Based on Deep Convolutional Neural Network
The model can effectively help diagnose meibomian gland dysfunction automatically.
research Update on Outcome Measures for Pediatric Systemic Lupus Erythematosus
New tools and criteria have been developed to better assess and treat pediatric lupus.
research A Quantitative Measurement Method for Nuclear-Pleomorphism Scoring in Breast Cancer
A new method accurately measures cell changes in breast cancer.
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.