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Hair transplantation and micrografting, used for baldness, involve moving hair follicles from hair-rich to bald areas, requiring careful procedure and post-care for success.

This study reported that a new deep learning algorithm using Mask R-CNN improved hair follicle classification accuracy by 4 to 15%, suggesting potential clinical application for enhanced hair loss diagnosis.

In this study, a novel GAN-based image translation method focusing on regions of interest showed improved predictive performance for post-hair transplant images compared to existing methods, using an ensemble approach to enhance robustness and detection accuracy.

In this study, researchers developed a machine learning model that accurately diagnosed scalp conditions like fine dandruff and perifollicular erythema with 75% and 82% accuracy, respectively, and created a user-friendly web platform for scalp health self-assessment, which achieved high user satisfaction.

This study suggests that using ex vivo dermatoscopy can improve the accuracy of scalp biopsy processing by correctly guiding tissue bisection and potentially reducing laboratory costs and turnaround time.

This article reviews the unique management skills necessary for building a successful hair restoration surgery team and contrasts them with managing a general cosmetic surgery practice, without reporting new research findings.

A surgeon is defined by their ability to operate, not just formal training, and dermatologists can safely perform cosmetic surgeries.

This study found that U.S. dermatology residents receive insufficient LGBT education, potentially affecting their readiness to address the specific needs of LGBT patients in dermatologic care.

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.

This article discusses the potential safety of platelet-rich plasma therapy for cicatricial alopecia but highlights that its effectiveness is still uncertain; no new empirical results are provided.

This study reports that deep learning models, particularly CNN and FCN, achieved high accuracy in diagnosing scalp and skin disorders, suggesting potential for improved diagnostic systems with further advancements.

This chapter reports that essential oil-based therapy, or aromatherapy, poses potential benefits for managing various disorders, such as pain, psychological issues, and skin conditions, although toxicity risks necessitate careful use under professional supervision.

This review discusses transplantation of melanocyte stem cells for vitiligo treatment and reports no new clinical results; it suggests the procedure could be effective in reactivating melanocyte precursors for repigmentation.

In this narrative review, the authors highlighted that AI-supported electronic health record analysis could help recognize Polycystic Ovary Syndrome/Polyendocrine Metabolic Ovarian Syndrome earlier, but also warned that these systems might perpetuate historical biases if not properly validated and interpreted.

In this study, researchers developed a hybrid deep learning model called ScalpViT that accurately diagnosed scalp diseases with 94.3% accuracy, surpassing existing methods like ResNet-50 and EfficientNet-B3, and providing visual explainability for clinicians using GradCAM and Attention Rollout techniques.

This study introduces ScalpViT, a new deep learning model that accurately diagnoses visually similar scalp diseases with 94.3% accuracy, outperforming other methods like ResNet-50 and EfficientNet-B3, and providing dual visual explainability through GradCAM and Attention Rollout, potentially benefiting diagnosis in resource-limited settings in India.

In this study, researchers developed ScalpViT, a novel deep learning model, to improve the automated diagnosis of visually similar scalp diseases, achieving 94.3% accuracy and outperforming existing models like ResNet-50 and EfficientNet-B3 when tested on a diverse dataset of 7,000 images.

This study found that cationic surfactant-based conditioning systems significantly improve hair combability by forming a stable low-friction film on hair surfaces, reducing friction and enhancing sensory performance compared to standard systems, as confirmed by both instrumental and sensory evaluations.

This study found that cationic surfactant-based conditioning systems significantly reduce friction on hair fibers, improving wet and dry combability by forming a stable film layer on the hair’s surface, as verified by both instrumental and sensory evaluations.

This case report suggests that herpes zoster ophthalmicus with secondary preseptal cellulitis may occur as a rare adverse reaction following platelet-rich plasma injections for androgenetic alopecia.

This study introduces ALUDWIG, an automated tool for assessing female androgenic alopecia severity from smartphone images, which may offer a more consistent alternative to current scoring methods like the Ludwig scale.

In this cross-sectional survey conducted in Lahore, Pakistan, 64% of LGBTQ participants experienced dermatological conditions such as androgenic alopecia, atopic eczema, melasma, and infections like scabies, highlighting the need for specialized dermatological care within this community.

ChatGPT is more accurate at diagnosing hair disorders in lighter skin tones than darker ones.

This study clarifies the fundamental aspects of intradermotherapy or mesotherapy, tracing its historical development and highlighting its benefits as well as the negative consequences of improper use, specifically addressing its decline due to severe side effects from treatment errors.

This study emphasizes the importance of dermatologists practicing cultural sensitivity and providing appropriate recommendations for Black women experiencing hair loss, as understanding textured hair can present diagnostic challenges.

This study developed a hat-shaped device with wearable sensors to estimate scalp moisture content using machine learning, demonstrating that it can provide accurate measurements comparable to professional scalp analyzers without the need for high-cost equipment.

This study suggests that histological features of primary melanoma can partially predict lymph node metastasis using AI, achieving a best prediction AUROC of 0.65.

Psychiatrists are crucial in pain management teams because they help treat severe pain and related mental health issues.

The InCISE score is a promising tool for assessing wound healing in head and neck surgery but needs more research for broader use.

In this study, the DIET-AI model, developed from a large dataset of over 200,000 images, demonstrated diagnostic performance for 31 skin diseases comparable to dermatologists of varying experience levels in 15 hospitals across China, supporting its potential effectiveness in clinical settings.