This review examines the increasing use of artificial intelligence (AI) in rheumatology, focusing on its potential impact in key areas. AI, including machine learning (ML) and deep learning (DL), is revolutionizing diagnosis, treatment personalization, and prognosis prediction in rheumatologic diseases. Specifically, AI models based on convolutional neural networks (CNNs) demonstrate significant efficacy in analyzing medical images for disease classification and severity assessment. Predictive AI models also have the ability to forecast disease trajectories and treatment responses, enabling more informed clinical decisions. The role of wearable devices and mobile applications in continuous disease monitoring is discussed, although their effectiveness varies across studies. Despite existing challenges, such as data privacy concerns and issues of model generalizability, the compelling results highlight the transformative potential of AI in rheumatologic disease management. As AI technologies continue to evolve, further research will be essential to address these challenges and fully harness the potential of AI to improve patient outcomes in rheumatology.

Atopic dermatitis (AD) is a chronic inflammatory skin disorder with significant implications for patient quality of life and a well-documented association with the atopic march. Recent advancements in biomarker research have unveiled critical insights into AD pathogenesis, diagnosis, prognosis, and therapeutic monitoring. This comprehensive review evaluates the utility of emerging biomarkers, including cytokines, chemokines, genetic markers, and microbiome-related components, in understanding the disease mechanisms and stratifying patient care. The role of minimally invasive diagnostic techniques, such as tape stripping and RNA monitoring, is highlighted, offering innovative approaches to pediatric populations. Furthermore, this review explores the biomarkers that predict disease progression, therapeutic response, and comorbidities, including food allergies and asthma. Personalized treatment strategies based on endotype-specific biomarkers are discussed as a future direction for improving clinical outcomes. Despite promising findings, the integration of biomarkers into routine practice necessitates further validation through large-scale studies. This work underscores the transformative potential of biomarker-driven approaches in enhancing the management of AD in children and its associated conditions.

This review examines the growing role of biological therapies in managing severe asthma in children aged 6–11 years. Severe asthma, characterized by persistent symptoms and frequent exacerbations, presents significant challenges in pediatric care. Biologic treatments, including mepolizumab, omalizumab, and dupilumab, provide targeted interventions for patients with high eosinophilic inflammation or allergic asthma (T2-high asthma). Alongside their therapeutic benefits, the review evaluates the safety profiles of these biologics, highlighting potential side effects and the necessity for monitoring during long-term use. Cost considerations and treatment adherence also emerge as important challenges that need to be addressed in clinical practice. Additionally, the review emphasizes the need for identifying patients who would derive the most benefit from biologic therapies, advocating for the development of biomarkers to aid in treatment decisions. Emerging biologics, such as tezepelumab, are introduced as promising alternatives with the potential to target upstream inflammatory pathways, offering hope for treating T2-low asthma forms, which currently lack effective treatment options in children.

The "hallucinations" of Large Language Models (LLMs) raise concerns about their accuracy in pediatrics. This study aimed to evaluate whether integrating information from the Nelson Textbook of Pediatrics through a Retrieval-Augmented Generation (RAG) system could enhance the performance of Llama3.2 in addressing complex pediatric clinical cases. We assessed the RAG system performance using 1,713 multiple-choice pediatric clinical questions from the MedQA dataset (n = 1,572) and Archives of Disease in Childhood-Education and Practice (n = 141). Each question was presented to Llama3.2 both in standalone mode and with RAG integration. The percentage of correct answers between models was compared using the chi-square test. p < 0.05 was considered statistically significant. The RAG-integrated system significantly outperformed standalone Llama3.2, achieving an overall accuracy of 67.78 % (1,161/1,713) compared to 46.18 % (791/1,713) for Llama3.2 alone (p = 1.5e-112). The improvement was consistent across all pediatric subspecialties. Incorporating RAG systems into clinical decision-making can enhance reliability and safety.

Background: Organ transplantation in children is a vital procedure for those with end-stage organ failure, but it has been linked to the development of post-transplant allergies, especially food allergies. This phenomenon, known as transplant-acquired food allergy (TAFA), is becoming increasingly recognized, though its mechanisms remain under investigation. Pediatric transplant recipients often require lifelong immunosuppressive therapy to prevent graft rejection, which can alter immune function and heighten the risk of allergic reactions. Our review aimed to gather the latest evidence on TAFA. Methods: We conducted a PubMed search from 25 June to 5 July 2024, using specific search terms, identifying 143 articles. After screening, 36 studies were included: 24 retrospective studies, 1 prospective study, 2 cross-sectional researches, and 9 case reports/series. Results: Most studies focused on liver transplants in children. The prevalence of food allergies ranged from 3.3% to 54.3%. Tacrolimus, alongside corticosteroids, was the most commonly used immunosuppressive therapy. In addition to food allergies, some patients developed atopic dermatitis, asthma, and rhinitis. Allergic symptoms typically emerged within a year post-transplant, with common allergens including milk, eggs, fish, nuts, soy, wheat, and shellfish. Both IgE-mediated and non-IgE-mediated reactions were observed, with treatment often involving the removal of offending foods and the use of adrenaline when necessary. Conclusions: Consistent immunological monitoring, such as skin prick tests and IgE level assessments, is essential for early detection and management of allergies in these patients. Understanding the link between transplantation and allergy development is crucial for improving long-term outcomes for pediatric transplant recipients.