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This study found that pharmacists using the EVInews database for self-medication information achieved significantly higher quality scores compared to those using other web-based sources.

This article introduces the Follicular Unit Excision-Linear Ellipse (FUE-LE) technique, which integrates both FUE and the linear ellipse method for optimal hair restoration, but presents no new clinical results.

EF and PXE not closely related.

This study found that the highest antioxidant-activity formulation of the RENTT herbal combination effectively stimulated hair growth in mice and may serve as a natural therapy for chemotherapy-induced alopecia.

This study introduced a single-stage network using large kernel attention that effectively restores high-resolution images by capturing both global and local details, reducing parameters and improving processing speed.

This study optimized efinaconazole spanlastic nanovesicles using risk management and multivariate analysis for potential transungual delivery to treat onychomycosis, achieving improved drug permeability and dissolution efficiency.

This study developed a method using Convolutional Neural Networks to detect nutritional deficiencies, such as iron, zinc, biotin, and vitamins, through high-resolution images of hair and nails, achieving an 89% accuracy rate in identifying these deficiencies.

This study developed an algorithm for predicting the impact of innovations on economic growth and reported its potential to enhance innovation policy decisions.

This study describes a system called FOLLYSIS©, which uses mathematics and image analysis to optimize Follicular Unit Extraction hair transplants, showing high accuracy in measuring donor area density and reducing donor site injury.

This review explores factors influencing export potential, including resource availability, technological innovation, and labor efficiency, but provides no new empirical results.

This study found that the optimized finasteride-loaded lyophilized tablets using a self-nanoemulsifying drug delivery system improved bioavailability in human volunteers compared to the marketed finasteride product.

This study reports that a robotic and AI-based system successfully analyzes FUE hair transplant procedures, aiding surgeons in planning and assessing operation success through detailed pre-op and post-op evaluations.

This research presents the Dodatek A model, elaborating on androgen function through new mathematical indices and methodological improvements, shifting focus from serum hormone concentrations to system interactions to better describe androgen activity comprehensively.

In this study, researchers modified an acellular scaffold with different concentrations of eggshell membrane protein, finding that a 5% concentration effectively enhanced tissue regeneration in mice with excisional wounds, achieving complete healing within 14 days without causing immunogenicity or inflammation.

This study developed a rapid and efficient in vitro method using high-performance liquid chromatography to screen for steroid 5 alpha-reductase inhibitors, determining inhibition constants for Finasteride and Epristeride.

This study reported that seed germination and root hair growth were significantly enhanced after exposure to an individual whose depression was treated with Emotional Freedom Techniques, suggesting that human mood may influence seed viability.

In this study, EC chemotherapy was found to be noninferior to TC in causing grade 3 or 4 neutropenia among HR+/HER2-negative breast cancer patients, but EC was associated with more other adverse events.

This study introduced a novel, weakly supervised method for segmenting hair in Scanning Electron Microscope images using simple image-level annotations, achieving over 30% improvement in mean Hausdorff Distance compared to Unet and SAM, while enhancing interpretability and refinement.

This article discusses hair angle manipulation using the Mega FUE® device but reports no clinical results; disclosure of the author's ownership of the manufacturing company is noted.

This study revealed that nestin-expressing progenitor cells capable of becoming ORS keratinocytes are present during both hair follicle development and in adult hair follicles.

This study introduces AlopeciaDet, a novel feature fusion technique, using camera images to detect Alopecia Areata with 99.45% accuracy, outperforming existing methods by leveraging CRSHOG and ResNet-50 features.

In this quasi-experimental study, researchers explored the optimal formulation of a nanoemulsion containing candlenut ethanol extract, finding that specific combinations of tween 80, span 80, and sonication time affected its physical properties and stability, although further activity testing is needed.

This study demonstrated that exposing hair follicle organ cultures to extremely low-frequency electromagnetic fields at 10 G intensity for 60 minutes promoted hair growth, suggesting its potential as a treatment for hair loss.

This study found that a topical transethosomal system may enhance the skin penetration and deposition of naftifine compared to a marketed cream, potentially overcoming the stratum corneum barrier.

This study found that etretinate treatment led to an increase in plucked telogen hair counts, suggesting a reduction in the duration of anagen as the primary cause.

In this study, researchers explored how hair follicle neural crest stem cell-derived exosomes, particularly those carrying miR-214-3p, promote neurite outgrowth and aid peripheral nerve regeneration, supported by detailed in vitro and in vivo data on nerve repair and functional recovery in rat models.

This document promotes an Erthwellness discount code that offers a 25% reduction on all their natural health products, without presenting any new research findings.

This study evaluated a novel, user-friendly approach for detecting hairfall trends over time using machine learning models. The Temporal Fusion Transformer model demonstrated high accuracy in identifying anomalies in hair shedding patterns, potentially aiding in the early detection of health risks related to hormonal fluctuations.

This study proposed and tested an Ensemble Pre-Learned Deep Learning and Optimized Long Short-Term Memory (EPL-OLSTM) model for classifying Alopecia Areata, achieving a 93.1% accuracy in differentiating healthy from varying severity levels of AA scalp hair using specific datasets.