IntroductionThe rapid ageing of the population presents significant public health challenges, particularly in countries with high life expectancy such as Italy. Although nutrition and physical activity are key determinants of healthy ageing, many older adults do not meet recommended guidelines. Mobile health (mHealth) technologies may support healthy behaviors; however, evidence on older adults’ perspectives remains […]
Trustworthy intelligent rooms: integrating blockchain, federated learning, and data-centric AI for healthcare 4.0
IntroductionIntelligent room systems are experiencing a surge in demand within the Healthcare 4.0 ecosystem. The integration of Federated Learning (FL) and Data-Centric AI has led to substantial enhancements in the predictive capabilities of machine learning models while maintaining data privacy. However, centralized aggregation in FL remains a single point of failure and is vulnerable to […]
Construction of patient trajectories to model clinical trial outcomes: application to myasthenia gravis
IntroductionAccurate prediction of patient outcomes in clinical trials is crucial for the timely assessment of treatment efficacy. This study proposes a novel approach to predict patient response using longitudinal clinical data.MethodsWe construct temporal trajectories from longitudinal data and extrapolate these trajectories to forecast individual patient outcomes. Additionally, we assess when new patients align with established […]
Effectiveness of the mobile application Holidaily in reducing work-related rumination when returning to work after vacation: a randomized controlled trial
BackgroundVacations reliably improve indicators of mental health, largely by providing relief from work-related stress. Low levels of work-related rumination, a key transdiagnostic factor linked to burnout and depression, are considered prerequisites for successful recovery both during vacations and in daily working life. However, such benefits are typically short-lived, with a rapid “fade-out” upon return to […]
Behavior change beyond intervention: an activity-theoretical perspective on human-centered design of personal health technology
IntroductionModern personal technologies, such as smartphone apps with artificial intelligence (AI) capabilities, have a significant potential for helping people make necessary changes in their behavior (e.g., adopt healthier lifestyles). Current research highlights that realizing this potential through the design and use of personal technologies calls for a critical reappraisal of the role of healthcare interventions […]
A data-centric perspective on designing AI foundation models for healthcare
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NICE approves life-extending drug for rare bile duct cancer
A new targeted treatment for a rare and aggressive bile duct cancer has been approved by NICE, offering patients the chance of longer survival and improved quality of life The targeted drug is designed for patients with advanced cholangiocarcinoma, an aggressive bile duct cancer that is often diagnosed at a late stage and has limited […]
Co-designing animated videos to explain large language models and their use in healthcare and research
IntroductionThe increasing development of large language models (LLM) in healthcare research is taking place without patient and public involvement and engagement (PPIE). Part of the challenge is the lack of accessible educational resources to promote literacy around LLMs.MethodsWe employed a co-design approach with 6 PPIE contributors from Tower Hamlets, London to develop educational animations about […]
Exploring plausible futures for artificial intelligence in rural healthcare: insights from participatory foresight methods
BackgroundArtificial intelligence (AI) has the potential to transform rural healthcare delivery through automated monitoring, personalised care, and virtual support. Yet the future pathways for AI in rural contexts remain underexplored. Most AI applications are developed in urban-centric environments with limited consideration for infrastructure constraints, workforce realities, and sociocultural dynamics that shape rural healthcare delivery.MethodsThis study […]
Navigating ethical, regulatory, and implementation barriers to AI in healthcare: pathways toward inclusive digital health in low-resource settings—a scoping review
BackgroundArtificial intelligence (AI) has the potential to revolutionize healthcare delivery in low- and middle-income countries (LMICs), yet its rapid adoption raises complex ethical, regulatory, and implementation challenges. This review investigates these barriers and identifies emerging strategies that support equitable and inclusive AI deployment in resource-limited settings.MethodsFollowing the PRISMA Extension for Scoping Reviews (PRISMA-ScR) guidelines, a […]
A framework for generative AI-driven extraction of clinical user needs in pediatric device development
IntroductionGenerative artificial intelligence (GenAI) is becoming an important tool in medical product development. A main component of this development includes annotating, summarizing, and extracting key insights from expert interviews to identify clinical pain points and curate device requirements. These tasks are time- and labor-intensive, resulting in increased administrative burden and reduced efficiency. As a result, […]
Artificial intelligence approaches to predicting treatment non-adherence in chronic diseases: a narrative review
Medication non-adherence affects 40%–50% of chronic disease patients globally, causing preventable morbidity and substantial healthcare costs. Traditional adherence monitoring approaches are retrospective and reactive, limiting timely intervention. Artificial intelligence and machine learning offer novel approaches for prospective adherence risk prediction, enabling anticipatory, resource-efficient interventions. This narrative review synthesizes current evidence on AI-based non-adherence prediction across […]