Thematic landscapes and temporal trends of disability technology adoption: insights from Structural Topic Modelling

IntroductionIn recent years, the importance of accessible and inclusive technologies has increasingly supported people with disabilities. However, prior studies on the adoption of technology remain fragmented, often focusing on specific disabilities or tools without exploring broader connections. Addressing this, the current study addresses the gaps by identifying core topics, examining temporal variations, and analyzing interrelations […]

Performance of federated versus centralized learning for mammography classification across film–digital domain shift

IntroductionLarge, diverse datasets are essential for reliable deep learning in mammography, yet clinical data remain siloed due to privacy and governance constraints. Federated learning enables collaborative training without sharing raw data, but its robustness under strong imaging-domain heterogeneity, such as film–digital shifts, remains uncertain.MethodsWe conducted a comparative evaluation of centralized learning and cross-silo federated learning […]

Explainable and reproducible AI: culturally responsive AI for health equity in minoritized groups

Artificial intelligence (AI) is transforming healthcare by enabling advanced diagnostics, personalized treatments, and improved operational efficiencies. By identifying complex data patterns and correlations, AI could supplement clinical decision-making, enabling more rapid diagnoses and treatment decisions tailored to meet the unique needs of diverse communities. However, realizing these benefits requires that clinical AI models be consistent, […]

Large language models in healthcare quality management: a European perspective on process automation and compliance

Large Language Models (LLMs) are transforming back-office quality management processes in European healthcare systems through automation of compliance monitoring, quality assurance, and process optimization without direct patient interaction. This narrative review synthesizes evidence from recent systematic reviews and implementation studies (2023-2025) examining LLM deployment within the European regulatory framework encompassing the Medical Device Regulation (MDR), […]

Negotiating privacy and responsibility in digital public health: a qualitative study of the social and ethical implications of peer-to-peer health data sharing

IntroductionPeer-to-peer sharing of personal health data on social media is increasingly used as a strategy to support public health goals. Such sharing is often assumed to motivate individuals to adopt or maintain healthy behaviors. However, the social and ethical implications of sharing-based interventions remain insufficiently examined. This paper offers an empirical and theoretical contribution by […]

Prediction of maturity-onset diabetes of the young subtypes using machine learning

IntroductionMaturity-onset diabetes of the young (MODY) is a monogenic type of diabetes caused by different pathogenic genetic variants in glucose metabolism-related genes, with GCK-MODY and HFN1A-MODY subtypes being the most frequent. Diagnosing the specific MODY subtype is essential for correct treatment and follow-up, but it requires gene sequencing, a time-consuming and costly process that depends […]

Value, development challenges, and strategies for gaining internal endorsement of digitally connected subcutaneous drug delivery devices: a survey of pharmaceutical stakeholders

IntroductionConnected drug delivery devices such as combination products that integrate traditional drug delivery systems with digital connectivity features represent an opportunity to improve treatment outcomes and disease management. This online survey study was conducted to explore the evolving landscape of digitally connected subcutaneous (SC) drug delivery devices, including the perspectives of pharmaceutical stakeholders regarding the […]

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