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 […]

The landscape of epidemiological research is experiencing a technological transformation, driven by the rapid expansion of big data and advancements in artificial intelligence (AI) and machine learning (ML). This workshop explored the opportunities and challenges associated with integrating diverse data sources into population-based research at different levels, including electronic health records (EHRs), genomic and omics […]

ObjectivesMental health services are facing unprecedented demand, placing significant pressure on clinicians to conduct timely and effective patient assessments. Rising staff turnover and burnout threatens service quality across many countries. This study examined whether providing clinical information, collected via an artificial intelligence (AI)—enabled decision support tool for mental health assessments in the UK’s National Health […]

BackgroundNurses frequently endure diminished sleep quality, sleeplessness, and psychological distress due to high-intensity shifts and persistent work pressure. Digital health interventions are increasingly utilised to enhance sleep behaviour; however, systematic information about their real benefits on the nursing population remains insufficient.ObjectiveTo assess the efficacy of digital and mobile interventions on sleep and associated psychological consequences […]