AIMC Topic: United Kingdom

Clear Filters Showing 21 to 30 of 369 articles

Trait mediation explains decadal distributional shifts for a wide range of insect taxa.

Nature communications
Shifts in insect distributions have been reported globally, largely attributed to climate and landscape changes. Communities are being reshaped, with species response traits mediating the effects of changing environments. Using a machine-learning app...

Development and validation of a diagnostic prediction model for pancreatic ductal adenocarcinoma: VAPOR 1, protocol for a prospective multicentre case-control study.

BMJ open
INTRODUCTION: Pancreatic ductal adenocarcinoma (PDAC) continues to have extremely poor patient outcomes, unlike other cancer types which have seen significant improvements in their treatments and survival. A major contributing factor is that PDAC is ...

Evolving Digital Health Technologies: Aligning With and Enhancing the National Institute for Health and Care Excellence Evidence Standards Framework.

JMIR mHealth and uHealth
The rapid advancement of artificial intelligence (AI)-driven diagnostics and wearable health technologies is transforming health care delivery by enabling real-time health monitoring and early disease detection. These innovations are catalyzing a shi...

Artificial Intelligence in Healthcare: Current Regulatory Landscape and Future Directions.

British journal of hospital medicine (London, England : 2005)
The integration of artificial intelligence (AI) in healthcare offers the potential to play a critical role in reshaping clinical practice. However, it also brings regulatory, ethical, implementation, social, and technical challenges that healthcare s...

Generative Artificial Intelligence in Primary Care: Qualitative Study of UK General Practitioners' Views.

Journal of medical Internet research
BACKGROUND: The potential for generative artificial intelligence (GenAI) to assist with clinical tasks is the subject of ongoing debate within biomedical informatics and related fields.

Comprehensive interaction modeling with machine learning improves prediction of disease risk in the UK Biobank.

Nature communications
Understanding how risk factors interact to jointly influence disease risk can provide insights into disease development and improve risk prediction. Here we introduce survivalFM, a machine learning extension to the widely used Cox proportional hazard...

Crisis-line workers' perspectives on AI in suicide prevention: a qualitative exploration of risk and opportunity.

BMC public health
BACKGROUND: Crisis support services offer crucial intervention for individuals in acute distress, providing timely access to trained volunteers whose human connection is key to the effectiveness of these services. However, there are significant dispa...

Proteomic risk scores for predicting common diseases using linear and neural network models in the UK biobank.

Scientific reports
Plasma proteomics provides a unique opportunity to enhance disease prediction by capturing protein expression patterns linked to diverse pathological processes. Leveraging data from 2,923 proteins measured in 53,030 UK Biobank participants, we develo...

Hip surveillance in children with cerebral palsy in the UK : history, challenges, and future directions.

The bone & joint journal
Cerebral palsy (CP) is associated with musculoskeletal complications in children, notably hip migration, which can progress to hip dislocation and joint degeneration. Without regular radiological monitoring, early-stage hip migration can be missed, p...