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This article highlights that rivaroxaban, commonly associated with bleeding risks, may also cause rare non-bleeding adverse effects like liver injury and hypersensitivity.

This study reported that trichoscopy revealed distinctive patterns across different autoimmune bullous diseases, suggesting it can be a useful preliminary diagnostic tool for differentiating these conditions.

Dermoscopy helped diagnose discoid lupus erythematosus in two patients without needing skin biopsies.

This study found that metabolism-related genes significantly impact the prognosis and metastasis in breast cancer, and the development of prediction models may guide personalized therapeutic strategies.

This study found that anti-Müllerian hormone (AMH) is a valuable primary variable for classifying functional androgenization, especially in distinguishing ovarian-related groups, and supports the novel stratification system.

This study found that genetic polymorphisms of OCT1 influence the effectiveness of metformin treatment in improving insulin sensitivity among PCOS patients, suggesting a role for personalized treatment strategies.

This study presents a computational approach, CATNIP, which repurposes drugs using only their biological and chemical information, predicting new uses like adrenergic uptake inhibitors for Parkinson's and vandetanib for Type 2 Diabetes.

This study developed a detailed classification system for functional androgenization in females that may enhance diagnosis and personalized treatment by identifying individual dysfunctions.

This study observed that patients with COVID-19 had many conditions and phenotypes that increased post-infection, varying by demographics and infection wave, which could enhance understanding and diagnostics of Long-COVID.

This review focuses on recent advancements in understanding and treating ischemic and nonischemic priapism, but does not present new clinical results.

This review discusses medical therapies for benign prostatic hyperplasia, highlighting the importance of personalizing treatments to individual patient needs and preferences.

This study found that the proposed Bayesian measurement-error-driven hidden Markov regression model effectively calibrated inflated covariate effect sizes in a community-based survey on androgenetic alopecia regardless of misclassification type.

The document concludes that individualized treatment for malignant epithelial tumors is necessary and more research on metastatic squamous cell carcinoma treatments is needed.

This study found that using electronic healthcare record data can provide valuable early insights into the clinical context of about half of the new safety signals evaluated within a regulatory environment.

This rapid review found that health-related videos on TikTok often contain questionable information, with higher content quality observed in videos produced by healthcare providers compared to general users.

This review highlights current and future AI applications in hair restoration and diagnosis of hair disorders, including automated systems for hair detection and self-diagnosis, emphasizing the need for experts to understand their benefits and limitations.

This study found that dutasteride may reduce the likelihood of hospitalization for BPH-related surgery and newly detected prostate cancer, compared to finasteride, and suggests a budgetary benefit.

This study found that Follicular Maps, derived from trichoscopic images, remained consistent over time and unaffected by hair cycling or noncicatricial alopecia, offering a precise tool for diagnosing and monitoring hair and scalp conditions.

This study identified known and potential novel adverse events, such as squamous cell carcinoma and dehydration, for vismodegib, underlining the importance of monitoring especially in the first two months of treatment.

This study found that DALL-E 2 performed poorly in generating accurate images of most pediatric dermatological conditions, highlighting the need for more domain-specific and inclusive training data.

This study found that multiphoton microscopy imaging allows for detailed observation and quantitative analysis of collagen alterations in the progression of endometrial cancer, potentially offering a faster, more accurate method for early diagnosis compared to current protocols.

This study observed that using the Fisher score feature selection approach with capsule network models led to a promising 94% accuracy in diabetes detection, indicating its potential as a diagnostic tool.

In this study, topical nitroglycerine spray successfully prevented impending necrosis in 94% of hair transplant cases showing signs of vascular distress.

This review examined the dermatologic side effects and potential treatments benefits of metformin and GLP-1/GIP agonists in managing skin conditions related to hormonal and immune effects in individuals with type 2 diabetes who are overweight or obese.

This systematic review discusses the treatment characteristics and outcomes for frontal fibrosing alopecia specifically in Black patients with skin of color, addressing a gap in clinical evidence due to underrepresentation in studies.

This review discusses existing forensic DNA phenotyping panels for biogeographical ancestry and externally visible characteristics and highlights major technical limitations, including terminology issues, genetic knowledge gaps, and technological debates; it reports no new results.

This chapter reviews the development of skin-specific outcome instruments for autoimmune diseases like cutaneous lupus erythematosus and dermatomyositis, highlighting a need for a broader community-involved process across other diseases but reports no new results.

In this observational retrospective study, UVF-dermoscopy was found to be more effective than polarized dermoscopy in identifying follicular features and distinguishing between scarring and nonscarring alopecias, particularly in individuals with lighter skin tones.

This review discusses syphilis and reports no new clinical findings; it highlights the need for improved prevention and diagnosis to address increasing infection rates globally and in Hungary.

This study reviews methods to ensure the reliability of machine learning models in medical imaging, focusing on bias detection, data drift assessment, and accuracy estimation without ground truth labels to enhance integration into clinical settings.