research Clinical Considerations of Bioequivalence for Topical Dermatologic Drugs
Current methods for assessing bioequivalence of topical drugs are limited and lack standardization.
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research Clinical manifestations of alopecia in autoimmune blistering diseases: A cross-sectional study
Most patients with autoimmune blistering diseases experienced some hair loss, which may be underreported and linked to disease severity.
research Overview of the Role of 308 Monochromatic Excimer Phototherapy for the Treatment of Alopecia Areata
308 excimer phototherapy is a safe and effective way to treat hair loss from Alopecia Areata.
research Machine learning-based steroid metabolome analysis reveals three distinct subtypes of polycystic ovary syndrome and implicates 11-oxygenated androgens as major drivers of metabolic risk
PCOS has three subtypes, with 11-oxygenated androgens increasing metabolic risk.
research Machine learning‐guided multi‐omics suggests iron‐dependent hormonal signaling drives root morphological plasticity in wheat under temperature stress
Iron-dependent hormones help wheat roots adapt to temperature stress.
research Machine Learning-Driven Optimization of Therapeutic Substance Composition for High-Hardness, Fast-Dissolving Microneedles for Androgenetic Alopecia Treatment.
Machine learning optimized microneedles for hair loss treatment showed better hair regrowth than minoxidil without safety risks.
research 0040 Machine learning algorithms as tools for identifying predictive autoantibody biomarkers in pemphigus vulgaris
Machine learning can help identify biomarkers for personalized Pemphigus vulgaris treatment.
research OR20-01 Machine Learning-based Steroid Metabolome Analysis In Women With Polycystic Ovary Syndrome Reveals Three Distinct Androgen Excess Subtypes With Different Metabolic Risk Profiles.
Machine learning identified three unique subtypes of androgen excess in women with PCOS, each with different metabolic risks.
research Supplemental Materials: Machine Learning Applications in Androgenetic Alopecia: A Systematic Review
research Supplemental Materials: Machine Learning Applications in Androgenetic Alopecia: A Systematic Review
research Investigation on the Mechanism of Platycladus orientalis in the Treatment of Androgenetic Alopecia Based on Machine Learning and Molecular Dynamics
research A Hybrid Deep Learning System for Automatic Detection of Scalp Diseases and Hair Fall Stage Classification
The system effectively detects scalp diseases and classifies hair fall stages with high precision.
research An Explainable AI-Based Decision Support System for Teaching and Classifying Hair Loss Types
The AI system accurately classifies hair loss types and explains its decisions.
research From Diagnosis to Prognosis: A Scoping Review of Artificial Intelligence in Alopecia Research
AI in alopecia research needs better tools for predicting treatment outcomes and ensuring fairness.
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 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 Hair analysis based on medical history and spatial-temporal data
Machine learning can predict hair health accurately using personal data.
research MachineLearning-Driven Optimization of TherapeuticSubstance Composition for High-Hardness, Fast-Dissolving Microneedlesfor Androgenetic Alopecia Treatment
Machine learning optimized microneedles promote hair regrowth better than minoxidil without safety risks.
research Uncharted waters
New DNA analysis and machine learning are advancing forensic science, improving accuracy and expanding into non-human applications.
research MachineLearning-Driven Optimization of TherapeuticSubstance Composition for High-Hardness, Fast-Dissolving Microneedlesfor Androgenetic Alopecia Treatment
Optimized microneedles promote hair regrowth better than minoxidil without safety risks.
research G2 stem cells orchestrate time-directed, long-range coordination of calcium signaling during skin epidermal regeneration
G2 stem cells control calcium signaling for skin regeneration.
research DNN-DTIs: improved drug-target interactions prediction using XGBoost feature selection and deep neural network
The DNN-DTIs method accurately predicts drug-target interactions and is useful for drug repositioning.
research Skinformatics: Navigating the big data landscape of dermatology
Clinicians and researchers must stay informed about big data to improve dermatology care.
research Learning Curve for the Hair Implanter Pen
The Hair Implanter Pen increases speed and is gentle on grafts, with users mastering it after a few tries.
research Comprehensive Program Planning for the Integration of 21st Century Learning Center After-School Programs with Regular Day Programs and Community Partners.
The report expanded knowledge of MBTPS1-related disorders by identifying new symptoms.
research Euphemism as a core feature of patientese: A comparative study between English and French
People use different types of euphemisms for medical terms in English and French, which can cause confusion for non-native speaking healthcare professionals. Also, medical TV shows and the internet might make these terms more technical over time.
research Characterization of the role of Facebook groups for patients who use scalp cooling therapy: a survey study
Facebook groups help patients using scalp cooling therapy by offering support, advice, and product recommendations.
research Artificial intelligence in dermatology: а scoping review
AI in dermatology shows high accuracy in diagnosing skin diseases but needs more research for improvement.
research Exploring New Horizons: Surgical Robots Supported by Artificial Intelligence
AI-assisted surgical robots improve surgery precision and safety.
research Diagnosis of childhood and adolescent growth hormone deficiency using transcriptomic data
Childhood growth hormone deficiency can be accurately diagnosed using gene expression data and random forest analysis.