research Local inflammation exacerbates cutaneous manifestations in a murine autoimmune pemphigus model
Local inflammation worsens autoimmune skin conditions by increasing antibody buildup.
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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.
research Image 4_Associations between ionomic profile and metabolic abnormalities in a murine model of sodium sulfide induced alopecia areata.tif
Targeting specific metabolic and ionic pathways may improve alopecia areata treatment.
research Image 3_Associations between ionomic profile and metabolic abnormalities in a murine model of sodium sulfide induced alopecia areata.tif
Linoleic acid and magnesium are key in alopecia areata progression, and tofacitinib can help by affecting their pathway.
research Image 2_Associations between ionomic profile and metabolic abnormalities in a murine model of sodium sulfide induced alopecia areata.tif
Linoleic acid and magnesium are key in alopecia areata progression, and tofacitinib can help by affecting their pathway.
research An in silico approach to the identification of potential proteomic and genomic diagnostic biomarkers for primary cicatricial alopecia
Certain genes and proteins may help diagnose and treat primary cicatricial alopecia.
research PEDL-XAI: A Hybrid Probabilistic Ensemble Deep Learning Approach for Hair Disorder Diagnosis
The new AI system accurately diagnoses hair disorders and offers personalized treatment recommendations.
research H11 More cancer, better counting or better at diagnosis? The history of skin cancer registration
High-quality data on skin cancer is crucial for understanding its trends and allocating healthcare resources effectively.
research 368 The Unanticipated Costs, Deficits, and Other Unexpected Burdens in a Diagnosis of Alopecia Areata
Alopecia areata requires addressing both emotional and financial challenges for better patient care.
research Serum-Based Assessment of Alopecia Areata Response to Treatment Using ATR-FTIR Spectroscopy
ATR-FTIR spectroscopy could help monitor alopecia areata treatment response non-invasively.
research Di-Genic Inheritance in Genodermatoses: Insights from Two Consanguineous Cases in a Reference Lebanese Center within the Middle East and North Africa (MENA) Region
A new genetic model may improve treatment and diagnosis for certain inherited skin diseases.
research Organoid‐Guided Precision Medicine: From Bench to Bedside
Organoid technology is improving personalized medicine by better predicting drug responses and treatments.
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 Guide to Studying Human Hair Follicle Cycling In Vivo
The document provides a method to classify human hair growth stages using a model with human scalp on mice, aiming to standardize hair research.
research Proteomic analysis of hair shaft and nail plate.
Hair and nail proteins, mainly keratins, are crucial for structure and can indicate health issues.
research HairLossMultinet: A Multi Scale Feature Fusion Method Using Deep Learning Approach
HairLossMultinet accurately classifies hair damage with 98% accuracy but needs a more diverse dataset for broader use.
research Female sexual dysfunction
Many women experience sexual dysfunction, but few seek help, and better treatment and medical training are needed.
research Development of gene therapy for inner ear disease: Using bilateral vestibular hypofunction as a vehicle for translational research
Gene therapy, especially using atoh1, shows promise for creating functional sensory hair cells in the inner ear, but dosing and side effects need to be managed for clinical application.
research Prediction of Alopecia Areata using CNN
A new CNN model can detect Alopecia Areata with 98% accuracy.
research Comparison of disease severity and ultrasonographic abdominal subcutaneous fatty tissue thickness in hirsute women
Women with more body hair tend to have thicker belly fat and more metabolic health issues.
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 Analyse trichoskopischer Bilder mit tiefen neuronalen Netzen zur Diagnose und Aktivitätsbewertung von Alopecia areata – eine retrospektive Studie
Deep-learning models can effectively diagnose and assess Alopecia areata using scalp images.
research Polycystic ovarian syndrome: Prevalence and its correlates among adolescent girls
About 15% of adolescent girls in a region of India have Polycystic Ovarian Syndrome, which is more common in those born by cesarean, with wisdom teeth, or with central obesity.
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 Severity Prediction of Hair Loss in Alopecia Areata with Hybrid Deep Learning Architecture
The model accurately predicts hair loss severity in alopecia areata.
research Mathematical Modeling of Alopecia Areata: Unraveling Hair Cycle Dynamics, Disease Progression, and Treatment Strategies
The model helps understand alopecia areata and suggests treatment strategies.
research Mathematical Modeling of Alopecia Areata: Unraveling Hair Cycle Dynamics, Disease Progression, and Treatment Strategies
The model helps understand alopecia areata and suggests better treatment strategies.
research SYNERGIA AI I MEDYCYNY: SZANSE I WYZWANIA
AI is transforming healthcare by improving diagnostics and therapy, despite challenges with data and trust.
research Optimized VGG19 Architecture for Precise and Efficient Multi-Class Hair Disease Classification
The optimized VGG19 model accurately classifies hair diseases with 98.64% accuracy.
research 574 A deep learning classifier for the analysis of tiger tail banding in trichothiodystrophy
A deep learning model was developed to help diagnose trichothiodystrophy by analyzing hair patterns.