Artificial intelligence-enhanced electrocardiogram (AI-ECG) models have shown outstanding performance in diagnostic and prognostic tasks, yet their black-box nature hampers clinical adoption. Meanwhile, a growing demand for explainable AI in medicine underscores the need for…
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Digital health interventions (DHIs) offer scalable, accessible approaches to promote healthy sleep in adolescents and to prevent or treat poor sleep and insomnia. Given the high prevalence of sleep problems and their bidirectional links…
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Sleep disturbances and mental health issues represent escalating global health challenges, exacerbated by the COVID-19 pandemic and increased digital media consumption. Digital mindfulness-based interventions (DMBIs) have emerged as a scalable and accessible alternative, but…
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Remote photoplethysmography (rPPG) offers a non-invasive means of estimating heart rate in telemedicine settings. Yet its reliability remains uncertain due to the limited diversity and ecological validity of existing benchmark datasets. In this work,…
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Healthcare faces significant challenges, including workforce shortages and increasing demands. Socially assistive robots (SARs) have emerged as potential solutions to augment care, but their implementation in hospital wards remains largely unexplored. We conducted a…
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The preferences and opinions of individuals with depression will likely be fundamental for the success of mood monitoring interventions, or for ambulatory assessment approaches as methods of data collection. Concerns have been raised regarding…
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We evaluated the effectiveness of a low-carbohydrate digitally-supported weight loss programme for glycaemic control for people with type 2 diabetes (T2D) compared with usual primary care in a 12 month RCT. We individually randomised…
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P4 medicine (Predictive, Preventive, Personalized, and Participatory) offers a comprehensive approach to personalized healthcare, emphasizing both the transition from disease to wellness and the importance of preventive care. In this perspective, we propose a…
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Real-time prediction of short-term mortality risk in the intensive care unit (ICU) is often hampered by missing medical data. To address this, we developed RealMIP, an end-to-end framework leveraging generative model for the dynamic…
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Synthetic tabular data generation (SDG) is increasingly important in healthcare research and innovation while preserving patients’ privacy. However, ethical concerns remain, primarily over residual privacy vulnerability and insufficient oversight. This review analyzes the only…
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