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Research 211–240 of 1000+
- DIAGNOSTIC VALUE OF TRICHOSCOPY IN THE DIFFERENTIAL DIAGNOSIS OF VARIOUS FORMS OF ALOPECIA
- Correction to ‘Retinoic acid drives hair follicle stem cell activation via Wnt/β‐catenin signalling in androgenetic alopecia’
- Application of big data analytics in minoxidil drug development: a data-driven model for predicting efficacy and side effect risks
- Predicting Polycystic Ovary Syndrome among Reproductive-Aged Women in Bangladesh Using Machine Learning Algorithms: Development of a Hospital-Based Predictive Model
- DETECTION OF HAIR FALL AND SCALP DISORDERS THROUGH ML AND IMAGE PROCESSING
- Comparison of Linear Regression, Decision Tree Regression, and Random Forest Regression Algorithms in Predicting Baldness Risk
- Quantitative Determination of α-Tocopherol and α-Tocopheryl Acetate in Pharmaceutical and Supplementary Soft Capsules by High Performance Liquid Chromatography
- Severity Prediction of Hair Loss in Alopecia Areata with Hybrid Deep Learning Architecture
- Circulating MicroRNA Signatures in Severe Alopecia Areata: Diagnostic Discrimination, Pathway Analysis, and Therapeutic Implications
- Automated early detection of androgenetic alopecia using deep learning on trichoscopic images from a Korean cohort: a retrospective model development and validation study
- BH20 A multicentre analysis of the adequacy of alopecia horizontal biopsy samples over 10 years
- Bad Hair Days: A Clinical and Trichoscopic Evaluation of Scalp Lesions
- Development and validation of new uv-visible spectrophotometric method for the estimation of minoxidil in bulk and pharmaceutical dosage form
- Demonstrating the potential of untargeted hair proteomics for personalized biomarkers in stress-associated disorders
- New Frontiers of Non‐Invasive Detection in Scalp and Hair Diseases: A Review of the Application of Novel Detection Techniques
- A Hybrid Transfer Learning Approach Using Obesity Data for Predicting Cardiovascular Diseases Incorporating Lifestyle Factors
- Advancing Hair Disease Diagnostics: A Deep Learning Approach Using Inception-ResNet v2 for Multi-Class Classification
- BIO-ANALYTICAL METHOD DEVELOPMENT AND VALIDATION OF FINASTERIDE, TADALAFIL, AND ITS APPLICATION TO PHARMACOKINETIC STUDIES IN RAT PLASMA BY USING LC-MS/MS
- Convolutional Neural Networks for Non-Invasive Diagnosis of Androgenetic Alopecia using Dermoscopic Hair Images
- FORENSIC DNA PHENOTYPING FOR CRIMINAL IDENTIFICATION
- Understanding hair disorders through artificial intelligence: DALLE's role in image creation
- Uncovering Shortcomings in Advertising Strategies for Over-the-Counter Minoxidil Products on Amazon
- Generative adversarial networks for anonymous acneic face dataset generation
- Predicting the Therapeutic Results of Unwanted Hair Growth with the Alexandrite Laser Device
- Hair cluster detection model based on dermoscopic images
- Transcriptome analysis of frontal fibrosis alopecia revealed involvement of immune cells and ferroptosis
- ADVANCES IN FUNCTIONAL NEUROSURGERY – MACHINE LEARNING, NEURAL ENGINEERING AND ROBOTICS IN TREATMENT OF NEURODEGENERATIVE DISORDERS
- RP-HPLC Technique for Dustasteride Quantitative Estimation in Tablet Dosage Form: Formulation and Validation of Analytical Technique
- CZAS TO SZTUCZNA INTELIGENCJA: OD TEORII DO ROZWIĄZAŃ RATUJĄCYCH ŻYCIE
- Methods of Transfer Learning for Multiclass Hair Disease Categorization