IntroductionDigital solutions and Artificial Intelligence (AI) innovations are often presented as the answer to many challenges faced by healthcare systems around the world. The UK government has made significant investments in this area, yet there have been concerns about the challenges faced when these technologies are implemented in practice. The aim of this study was […]
Digital health literacy and sociodemographic characteristics of patients undergoing total hip or knee arthroplasty—a cross-sectional study
BackgroundDigital solutions may increase sustainability in healthcare for patients undergoing total hip or knee arthroplasty (THA, TKA). Little information exists on these patients’ digital health literacy levels.ObjectiveDescribe digital health literacy in patients following THA or TKA and examine the associations between sociodemographic factors and digital health literacy levels.MethodsIn a cross-sectional survey, a total of 800 […]
Promises and challenges of applying large language models in the healthcare domain
Large language models are rapidly moving from theoretical concepts to active clinical pilots. Current approaches diverge between general-purpose models, which adapt to healthcare via prompt engineering, and domain-specific models, which prioritize deep alignment with medical knowledge graphs to ensure safety. Despite reported benefits in documentation efficiency and diagnostic reasoning, significant challenges remain regarding hallucination, privacy, […]
Artificial intelligence in rehabilitation: a review of clinical effectiveness, real-world performance, safety, and equity across modalities and settings
BackgroundRehabilitation faces a scale problem: millions who could benefit lack timely, effective services. Artificial intelligence (AI) and device-based modalities (e.g., robotics and VR) can extend reach and personalise care when validated, yet decision-makers lack a consolidated view of clinical usefulness, translation to practice, safety, equity, and cost.MethodsWe conducted an umbrella review of reviews using a […]
Planning and delivering co-creation workshops: practical lessons from digital health device design
Co-creation methods are increasingly recognised as essential in digital health and care, yet engineers and physical scientists new to the field often find the literature highly theoretical, fragmented, and difficult to apply in practice. This paper presents a worked example of planning and delivering co-creation workshops through the development of an overactive bladder treatment device. […]
Can ChatGPT-5 educate the public about vasectomy?: a Google Trends–based expert panel assessment
BackgroundChatGPT-5, the latest multimodal large language model (LLM), has gained remarkable public attention for its ability to provide real-time and context-aware health information. However, its effectiveness in addressing sensitive urological topics such as vasectomy has not been systematically evaluated.ObjectiveThis study aimed to evaluate the accuracy, completeness and public suitability of ChatGPT-5’s responses to frequently asked […]
Ontology- and LLM-based data harmonization for federated learning in healthcare
IntroductionSemantic heterogeneity across electronic health records (EHRs) limits scalable and privacy-preserving analytics in healthcare. While federated learning (FL) enables collaborative modeling without sharing raw data, it requires consistent, ontology-aligned representations. We present an ontology- and large language model (LLM)-based data harmonization approach to support secure, interoperable FL workflows.MethodsWe propose a general two-step pipeline for converting […]
Shaping the future of multiple myeloma with artificial intelligence and digital twins: from concept to clinic
Multiple myeloma (MM) is an incurable hematological malignancy with significant clinical and biological heterogeneity. Despite development and refinement of numerous prognostic models for MM, challenges with accurate and reliable risk stratification remain, highlighted by unexpected, early relapse or progression of disease in patients termed functional high-risk (FHR). To improve decision-making and optimise outcome, there is […]
Intelligence without intuition: a mixed-methods pilot study on reasoning models in musculoskeletal physiotherapy for low-back pain
Musculoskeletal pain, especially low-back pain, is highly prevalent and often challenging to manage due to its multifactorial nature. Effective diagnosis and therapy require clinicians to integrate biopsychosocial information within an evidence-based clinical reasoning framework. Large language models that “think” before responding, so-called reasoning models, show promise to support such complex decision-making, yet their validity and […]
Anonymization, accountability, and access: legal dimensions of health data sharing in federated networks. Perspectives from empirical study
This paper explores the perspectives of stakeholders involved in federated networks for health data sharing, focusing on the legal and practical dimensions of data protection and governance under GDPR and EHDS in the development of such infrastructures. Using a qualitative approach centered on perspectives of 19 experts with experience in projects building federated networks, it […]
A pre-treatment comparison of referral pathways to guided ICBT for depression and anxiety disorders – A naturalistic study in routine clinical care
IntroductionSelf-referral to therapist-guided internet-delivered cognitive behavioral therapy (guided ICBT) is increasingly being implemented in specialized mental healthcare settings to reduce barriers to care. Little is known about the characteristics of patients who access treatment through this pathway compared to the traditional referral pathway from general practitioner (GP). This study aims to compare demographic characteristics, socioeconomic […]
Extraction and processing of intensive care chart data from a patient data management system
BackgroundRoutine clinical data captured in Patient Data Management Systems (PDMS) in intensive care and perioperative settings are an invaluable resource for clinical research. However, the proprietary, fragmented, and transaction-oriented architecture of many systems severely limits secondary data use and requires extensive Extract, Transform, and Load (ETL) processing.MethodsWe developed a modular, Python-based ETL framework that enables […]