research Classification of hair disease
Classifying hair diseases, like alopecia, is difficult and needs more research to understand their causes.
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300-330 / 1000+ results research Alopecia classifications
Classifying alopecia helps diagnose and treat different types of hair loss accurately.
research Limitations of Treatment-Induced Alopecia Grading Instruments in Evaluating Therapeutic Response
Current methods for grading hair loss from cancer treatment are not accurate enough and need improvement.
research Enhanced Hair Disease Classification Using Deep Learning
The model accurately classifies hair conditions with 97% accuracy.
research Classification and Scoring of Androgenetic Alopecia (Male and Female Pattern)
research Classification and Scoring of Androgenetic Alopecia (Male and Female Pattern)
The document explains how hair loss in men and women, known as Androgenetic alopecia, is categorized using the Hamilton-Norwood system for men and the Ludwig grade system for women.
research 1375 Cutaneous adnexal cysts revisited: A novel classification based on morphological and molecular features
The conclusion introduces a new way to classify skin cysts using their shape and genetic markers.
research Obsessive-compulsive skin disorders: a novel classification based on degree of insight
The new classification system for skin disorders emphasizes the importance of understanding a patient's awareness of their condition for better treatment.
research Classification of male-pattern hair loss
No current system perfectly classifies male-pattern hair loss, indicating a need for a new system for better diagnosis and treatment.
research Classifications of patterned hair loss: a review
Different types of hair loss need specific treatments, and while many classification systems exist, each has its flaws; more research is needed to refine these systems and treatments.
research Classification and Scoring of Androgenetic Alopecia (Male and Female Pattern)
The document explains how hair loss patterns in men and women, known as Androgenetic alopecia, are classified using the Hamilton-Norwood system for men and the Ludwig grade system for women.
research The utility of the classification tools in National Institute of Health and Clinical Excellence’s Clinical Knowledge Summaries for primary care
Nearly half of the classification tools in the National Institute of Health and Clinical Excellence's Clinical Knowledge Summaries might not effectively guide management for general practitioners.
research The Immunological Association between Alopecia Areata and Respiratory Diseases: A Systematic Review
People with alopecia areata may also have allergic rhinitis and should be checked for respiratory allergies.
research Curl pattern classification: A potential tool for communication and risk stratification
Classifying curl patterns might help doctors assess and treat hair loss better.
research Exploring the Medication Pattern of Externally Used Traditional Chinese Medicine Compound for Hair Loss in the National Patent Database Based on R Language Data Mining
Traditional Chinese medicine for hair loss focuses on "tonifying and activating blood, nourishing the liver and kidney."
research DEEP REVIEW ON ALOPECIA AREATA DIAGNOSIS FOR HAIR LOSS-RELATED AUTOIMMUNE DISORDER PROBLEM
Machine learning and deep learning can effectively diagnose alopecia areata.
research Shape Variability and Classification of Human Hair: A Worldwide Approach
Human hair can be classified into eight types based on physical features, not ethnicity.
research The Cohen hair loss classification system
Dr. Bernard Cohen created a new system to classify hair loss using numbers and a detailed scalp map.
research Faculty Opinions recommendation of A new classification of pattern hair loss that is universal for men and women: basic and specific (BASP) classification.
The BASP classification is a detailed system for categorizing hair loss in both men and women, but it may be complex for beginners and not fully suitable for grading female hair loss.
research Korean Consensus Criteria for the Severity Classification of Alopecia Areata
The criteria help doctors diagnose and treat alopecia areata more effectively.
research Using disease symptomatology to guide treatment in patients with central centrifugal cicatricial alopecia: introduction of C-CAT scoring tool
The C-CAT tool helps assess and improve treatment for central centrifugal cicatricial alopecia.
research A new practical classification for spatial distribution and morphology of human hair: Ahmad's LGMA classification
Dr. Muhammad Ahmad created a hair classification system to help improve hair restoration surgery outcomes.
research Modified basic and specific (BASP) classification for pattern hair loss
The modified hair loss classification is more detailed but less user-friendly.
research Worldwide diversity of hair curliness: a new method of assessment
A new method accurately classifies hair types, showing global hair diversity.
research Standardizing the Nomenclature of Grafts
The authors suggest using a standard system to name hair grafts to improve communication in hair restoration.
research A discriminant multi-scale histopathology descriptor using dictionary learning
The new image descriptor helps identify skin cancer structures with good accuracy.
research The Knudsen Nomenclature
Dr. Russell Knudsen's system classifies hair grafts by class, shape, and size for clearer communication in hair restoration surgery.
research Reclassification of Botryococcus braunii chemical races into separate species based on a comparative genomics analysis
Botryococcus braunii's three chemical races should be reclassified as separate species.
research Advances in Chitosan-Based Nanoparticles for Drug Delivery
Chitosan, a natural substance, can be used to create tiny particles that effectively deliver various types of drugs, but more work is needed to improve stability and control of drug release.
research YouTube/ Bilibili/ TikTok videos as sources of medical information on laryngeal carcinoma: cross-sectional content analysis study
Social media videos on laryngeal cancer need better quality and professional input.