AIMC Topic: United Kingdom

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Breaking down costs: rehabilitation robotics vs. usual care therapy in diverse healthcare models.

Scientific reports
One of the significant barriers to the adoption of rehabilitation robotics into clinical care over the last 30 years has been the high investment costs of the technology. There have been limited efforts to understand the healthcare economics of imple...

Estimating 10-Year Cardiovascular Disease Risk in Primary Prevention Using UK Electronic Health Records and a Hybrid Multitask BERT Model: Retrospective Cohort Study.

JMIR medical informatics
BACKGROUND: Cardiovascular disease (CVD) remains a leading cause of preventable morbidity and mortality, highlighting the need for early risk stratification in primary prevention. Traditional Cox models assume proportional hazards and linear effects,...

Comparative study of coronary artery disease prediction: conventional QRISK3 versus enhanced machine learning models combined with particle swarm optimisation algorithm.

Open heart
BACKGROUND: Coronary artery disease (CAD) is one of the biggest causes of mortality worldwide. Risk stratification for early detection is essential for the primary prevention of CAD. QRISK3 is known to overestimate future CAD risk in some populations...

Carbon Reporting Practices in the NHS: Emissions and Omissions Relating to Artificial Intelligence.

Journal of medical Internet research
Artificial intelligence (AI) is being rolled out across the UK National Health Service (NHS) to improve efficiency; yet, its carbon footprint is largely invisible within mandatory Green Plan reporting. This work shows where NHS carbon reporting omits...

Reducing annotation burden in physical activity research using vision language models.

Scientific reports
Data from wearable devices collected in free-living settings, and labelled with physical activity behaviours compatible with health research, are essential for both validating existing wearable-based measurement approaches and developing novel machin...

A novel potential biomarker panel to diagnose depression derived from big proteomic data.

Journal of affective disorders
BACKGROUND: There is still no clinical biomarker to diagnose depression. Given the complexity of a multifactorial disease like depression, a single biomarker is unlikely to capture the full heterogeneity of the disease and be applicable in clinical p...

Study protocol for an open-label, single-arm, mixed methods feasibility study of the MWIQ AI-powered decision support tool for diabetes management in GP practices.

BMJ open
INTRODUCTION: Diabetes affects ~10% of the world's population and is rising. Treatment costs in the UK are ~15% of the NHS budget. Diabetes-related complications can be lowered through better evidence-based clinician management and patient self-manag...

The Development and Growth of the English National Real-Time Syndromic Surveillance Program: Key Developments and Lessons Learned From the First Two Decades.

Journal of medical Internet research
Syndromic surveillance now forms an integral part of the surveillance for a wide range of hazards in many countries. Establishing syndromic surveillance systems can be difficult due to the many different sources of data that can be used, cost pressur...

Predicting the future risk and outcomes of severe heart failure and coronary artery disease with machine learning in the UK Biobank Cohort.

PloS one
BACKGROUND: In order to seriously impact the global burden of heart failure (HF) and coronary artery disease (CAD), identifying at-risk individuals as early as possible is vital. Risk calculator tools in wide clinical use today are informed by tradit...