Background: As the use of smartphones continues to surge globally, mobile applications (apps) have become a powerful tool for healthcare engagement. Prominent among these are dermatology apps powered by Artificial Intelligence (AI), which provide immediate diagnostic guidance and educational resources for skin diseases, including skin cancer.Objective: This article, authored by the EADV AI Task Force, seeks to offer insights and recommendations for the present and future deployment of AI‐assisted smartphone applications (apps) and web‐based services for skin diseases with emphasis on skin cancer detection.Methods: An initial position statement was drafted on a comprehensive literature review, which was subsequently refined through two rounds of digital discussions and meticulous feedback by the EADV AI Task Force, ensuring its accuracy, clarity and relevance.Results: Eight key considerations were identified, including risks associated with inaccuracy and improper user education, a decline in professional skills, the influence of non‐medical commercial interests, data security, direct and indirect costs, regulatory approval and the necessity of multidisciplinary implementation. Following these considerations, three main recommendations were formulated: (1) to ensure user trust, app developers should prioritize transparency in data quality, accuracy, intended use, privacy and costs; (2) Apps and web‐based services should ensure a uniform user experience for diverse groups of patients; (3) European authorities should adopt a rigorous and consistent regulatory framework for dermatology apps to ensure their safety and accuracy for users.Conclusions: The utilisation of AI‐assisted smartphone apps and web‐based services in diagnosing and treating skin diseases has the potential to greatly benefit patients in their dermatology journeys. By prioritising innovation, fostering collaboration and implementing effective regulations, we can ensure the successful integration of these apps into clinical practice.

Line-field confocal optical coherence tomography (LC-OCT) is a new, noninvasive imaging technique for the diagnosis of skin cancers. A total of 243 benign (54%) and malignant (46%) skin lesions were consecutively enrolled from 27 August 2020, to 6 October 2021 at the Dermatology Department of the University Hospital of Siena, Italy. Dermoscopic- and LC-OCT-based diagnoses were given by an expert dermatologist and compared with the ground truth. Considering all types of malignant skin tumours (79 basal cell carcinomas (BCCs), 22 squamous cell carcinomas, and 10 melanomas), a statistically significant increase (p = 0.013) in specificity was observed from dermoscopy (0.73, CI 0.64–0.81) to LC-OCT (0.87, CI 0.79–0.93) while sensitivity was the same with the two imaging techniques (0.95 CI 0.89–0.98 for dermoscopy and 0.95 CI 0.90–0.99 for LC-OCT). The increase in specificity was mainly driven by the ability of LC-OCT to differentiate BCCs from other diagnoses. In conclusion, our real-life study showed that LC-OCT can play an important role in helping the noninvasive diagnosis of malignant skin neoplasms and especially of BCCs. LC-OCT could be positioned after the dermoscopic examination, to spare useless biopsy of benign lesions without decreasing sensitivity.

(1) Background: The Controlling Nutritional Status (CONUT) score is an immuno-nutritional screening tool based on serum albumin, total cholesterol, and lymphocyte count. The aim of the study was to assess the CONUT score as a potential prognostic factor of response to therapy in patients with advanced thyroid cancer treated with tyrosine kinase inhibitors (TKIs). (2) Methods: We retrospectively evaluated 42 metastatic thyroid cancer patients (54.8% female). The median age at the time of TKI treatment was 69 years. Histological diagnosis was differentiated thyroid cancer in 66.7%, poorly differentiated thyroid cancer in 21.4%, and medullary thyroid cancer in 11.9% of patients. CONUT score was assessed before starting TKI therapy. (3) Results: Progression-free survival (PFS) and overall survival (OS) were significantly influenced by baseline CONUT score. The best CONUT cut-off able to predict the response to treatment was 3. Both PFS and OS were better in patients with CONUT score <3 than in those with CONUT score ≥3 (p < 0.0001). CONUT score was the only independent prognostic factor associated with PFS (p = 0.021) and OS (p = 0.007). (4) Conclusions: CONUT score represents a relatively new screening tool, easily applicable in clinical practice and potentially useful in predicting prognosis in thyroid cancer patients treated with TKIs.

Background: Recent data suggest that systemic inflammation can negatively affect atrioventricular conduction, regardless of acute cardiac injury. Indeed, gap‐junctions containing connexin43 coupling cardiomyocytes and inflammation‐related cells (macrophages) are increasingly recognized as important factors regulating the conduction in the atrioventricular node. The aim of this study was to evaluate the acute impact of systemic inflammatory activation on atrioventricular conduction, and elucidate underlying mechanisms. Methods and Results: We analyzed: (1) the PR‐interval in patients with inflammatory diseases of different origins during active phase and recovery, and its association with inflammatory markers; (2) the existing correlation between connexin43 expression in the cardiac tissue and peripheral blood mononuclear cells (PBMC), and the changes occurring in patients with inflammatory diseases over time; (3) the acute effects of interleukin(IL)‐6 on atrioventricular conduction in an in vivo animal model, and on connexin43 expression in vitro. In patients with elevated C‐reactive protein levels, atrioventricular conduction indices are increased, but promptly normalized in association with inflammatory markers reduction, particularly IL‐6. In these subjects, connexin43 expression in PBMC, which is correlative of that measured in the cardiac tissue, inversely associated with IL‐6 changes. Moreover, direct IL‐6 administration increased atrioventricular conduction indices in vivo in a guinea pig model, and IL‐6 incubation in both cardiomyocytes and macrophages in culture, significantly reduced connexin43 proteins expression. Conclusions: The data evidence that systemic inflammation can acutely worsen atrioventricular conduction, and that IL‐6‐induced down‐regulation of cardiac connexin43 is a mechanistic pathway putatively involved in the process. Though reversible, these alterations could significantly increase the risk of severe atrioventricular blocks during active inflammatory processes.