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This study demonstrated that current facial recognition software can accurately identify individuals from MRI head scans within minutes, highlighting significant privacy concerns for clinical trial participants and the need for enhanced data protection measures.

This letter compares automated digital image analysis (TrichoScan) with manual marking of hairs in male patients with androgenetic alopecia but reports no new results.

Hair shaft malformation contributes to Central Centrifugal Cicatricial Alopecia.

This guide reviews the biology of sebaceous glands and their evaluation methods, emphasizing their roles beyond lipid production in skin health and disease, and reports no new research results.

This study found that laboratory-formulated natural shampoos condition hair better than commercial herbal shampoos, as shown by SEM micrograph analysis of hair microstructure.

This study validated that both tape-based and image-based methods for measuring head crown areas, and the CASLite NOVA as well as Image-Pro software for hair count, showed acceptable agreement, supporting their interchangeable use in hair care research settings.

This study developed a high-resolution phototrichogram system that can automatically and accurately assess hair growth metrics in cosmetic trials, achieving over 90% correlation with manual measurements.

QIA-64 software can measure straight wire lengths accurately but needs improvement for curved wires and width measurements.

This study demonstrated that using morphometric and 3D reconstruction software to evaluate scalp biopsies in non-cicatricial alopecias may be feasible and sensitive for detecting subtle follicular changes.

This study describes a new method using ImageJ to quantitatively assess hair loss in mice with alopecia areata, offering a more precise and reproducible alternative to traditional visual scoring systems by employing image-based analysis techniques.

A new image-based method improves accuracy in measuring hair loss in mice.

This study presents a new approach to automatically remove hair artifacts from dermoscopic images, which reportedly performed well compared to existing methods like DullRazor using the PH2 datasets.

This study captured digital images of hair regions in healthy individuals and patients with androgenetic alopecia to analyze and compare the number of follicular units and hairs using software.

This study developed and tested a new algorithm for analyzing coat and skin coloration in laboratory animals, using digital images and hierarchical color clustering, which effectively quantified color proportions and tracked changes over time without specialized software.

In this study, researchers validated a software-based method that quantitatively assesses the effectiveness of treatments for hair loss by calculating the area of hair loss using contrast in standardized photographs, proving effective for both early and advanced cases of androgenetic alopecia and telogen effluvium.

This study found that a new 3D image analysis method from SEM images enables quick and accurate measurement of cuticle scale heights in hair fibers.

This study introduces the Hair Cell Analysis Toolbox (HCAT), a machine-learning software that automates the analysis of cochlear hair cells, enabling unbiased and comprehensive imaging data interpretation.

This editorial discusses the impact of 'Industry 4.0' on laboratory research, highlighting innovations like advanced software and directed enzyme evolution that promise to revolutionize biological understanding and research methods but provides no new experimental data.

This study identified several genetic variants associated with cattle hair coat length, which may help breed more heat-tolerant animals by facilitating efficient heat loss.

This study described a new wig coating technique using keratin and graphene oxide that significantly enhanced UV resistance, antistatic properties, and durability compared to traditional methods.

This study reported that Trichoscan, a computer-assisted hair measurement system, was not supported as accurate for clinical trials due to errors in signal detection, despite its analysis speed.

In this study, VVF was found to be a highly variable and unreliable measure of void space in granular scaffolds, sensitive to various input parameters and less predictive than particle count.

This article introduces teletrichoscopy as a method for diagnosing hair disorders during the COVID-19 pandemic and reports no new clinical results.

This study found that TikTok provides valuable insights into experiences with lupus erythematosus, highlighting distress from symptoms, negative perceptions of pharmacologic treatments, and issues with feeling "medically gaslighted.

In this study, a new shading model for hair was developed that better matches real-life light scattering, thanks to detailed new measurements of hair fiber scattering not predicted by existing models.

This study introduced a new hair shading model that more accurately simulates light scattering on hair fibers, capturing effects not predicted by previous models.

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.

In this study, the researchers reported that their novel algorithm for hair restoration in dermoscopy images achieved high accuracy and texture preservation, outperforming other techniques in diagnostic accuracy and texture quality measures.

This study concluded that TrichoScan is error-prone in its current form and overestimates certain hair growth parameters, with results not aligning with clinical severity of alopecia.

This study found that obesity and a negative body image negatively impact health-related quality of life and mental health in women with PCOS, indicating the need for healthcare professionals to address these issues with effective treatments.