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.
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research Quantitative analysis and development of alopecia areata classification frameworks
A new algorithm effectively classifies Alopecia Areata, aiding early detection and treatment.
research An Analysis of Alopecia Areata Classification Framework for Human Hair Loss Based on VGG-SVM Approach
The VGG-SVM method accurately identifies and classifies stages of Alopecia Areata and other hair loss conditions.
research How different is human hair? A critical appraisal of the reported differences in global hair fibre characteristics and properties towards defining a more relevant framework for hair type classification
Human hair varies widely and should be classified by curl type rather than race.
research Rethinking pattern hair loss classification in the era of trichoscopy and artificial intelligence
A hybrid model using traditional methods, trichoscopy, and AI improves hair loss assessment.
research Deep Learning-based Automatic System for Diagnosis and Classification of Skin Dermatoses
The document concludes that an automatic system using deep learning can help diagnose skin disorders, but challenges and opportunities in this area remain.
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 Situation-Specific Purposes and Epistemic Games: A Framework for Teaching the Evaluation of Causal Information
The framework helps people evaluate scientific information for specific needs.
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 Phenotype-Specific Lifestyle Prediction for PCOS Using Machine Learning Multi-Class Classification and SHAP Explainability
Machine learning can accurately predict PCOS phenotypes using lifestyle and symptom data.
research Derivation and validation of the Systemic Lupus International Collaborating Clinics classification criteria for systemic lupus erythematosus
The new criteria for classifying lupus are more accurate and comprehensive.
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 Machine Learning Approach for Predicting Systemic Lupus Erythematosus in Oman-based Cohort
The machine learning model accurately predicts Systemic Lupus Erythematosus in Omani patients.
research A Comprehensive Study on Quasi-Drugs Regulations in Japan and South Korea
Quasi-drugs in Japan and South Korea are regulated to ensure safety and effectiveness, offering products with mild therapeutic effects.
research Hidradenitis Suppurativa as a Potential Subtype of Autoinflammatory Keratinization Disease
Hidradenitis suppurativa might be a type of autoinflammatory skin disease.
research <b>An Explainable AI-Based Decision Support System for Teaching and Classifying Hair Loss Types</b><b></b>
The AI system accurately classifies hair loss types and explains its decisions.
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 S2k guideline for the treatment of hidradenitis suppurativa / acne inversa – Short version
The guideline recommends using specific drugs and surgery together for treating hidradenitis suppurativa effectively.
research Congenital atrichia and hypotrichosis
The document emphasizes the importance of correctly identifying and classifying genetic hair disorders to help diagnose related health conditions.
research Artificial neural networks algorithms for prediction of human hair loss related autoimmune disorder problem
Artificial neural networks can accurately diagnose Alopecia Areata.
research Data-driven strategies for drug repurposing: insights, recommendations, and case studies
Drug repurposing can speed up and reduce costs in drug discovery, especially for cancer treatment.
research Intestinal Permeability Study of Minoxidil: Assessment of Minoxidil as a High Permeability Reference Drug for Biopharmaceutics Classification
Minoxidil works well as a high permeability reference drug for biopharmaceutics classification.
research Developing a Framework for Sources of New Product Ideas
The authors suggest systematically sourcing new product ideas from various internal and external places to improve innovation.
research Framework guidelines for the process of caring for the health of adolescent transgender (T) and non-binary (NB) people experiencing gender dysphoria — the position statement of the expert panel
Provide individualized, supportive care for transgender and non-binary adolescents to improve their well-being.
research Korean Consensus Criteria for the Severity Classification of Alopecia Areata
The criteria help doctors diagnose and treat alopecia areata more effectively.
research Proposed ICD-10 framework for identifying emergency department visits that may be impacted by community pharmacy care clinics
Pharmacy care clinics can reduce some emergency visits by managing certain conditions and medication issues.
research Standardizing the Classification and Description of Follicular Unit Transplantation and Mini-Micrografting Techniques
Surgeons suggested a standard system for hair transplant methods to improve communication and results.
research A machine learning and network framework to discover new indications for small molecules
A machine learning model called CATNIP can predict new uses for existing drugs, like using antidepressants for Parkinson's disease and a thyroid cancer drug for diabetes.
research Optimized polycystic ovarian disease prognosis and classification using AI based computational approaches on multi-modality data
AI can improve early diagnosis and classification of PCOS, aiding in prevention of related health issues.
research JAK-centric explainable few-shot gene-expression diagnosis framework for alopecia via MultiPLIER priors and relation-style set-to-set comparison
A new method helps diagnose alopecia areata using specific gene markers and could guide targeted treatments.