AIMC Topic: United Kingdom

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Deep Learning-based Segmentation of Computed Tomography Scans Predicts Disease Progression and Mortality in Idiopathic Pulmonary Fibrosis.

American journal of respiratory and critical care medicine
Despite evidence demonstrating a prognostic role for computed tomography (CT) scans in idiopathic pulmonary fibrosis (IPF), image-based biomarkers are not routinely used in clinical practice or trials. To develop automated imaging biomarkers using ...

Artificial intelligence software for analysing chest X-ray images to identify suspected lung cancer: an evidence synthesis early value assessment.

Health technology assessment (Winchester, England)
BACKGROUND: Lung cancer is one of the most common types of cancer in the United Kingdom. It is often diagnosed late. The 5-year survival rate for lung cancer is below 10%. Early diagnosis may improve survival. Software that has an artificial intellig...

Scaling up a Clinical AI Fellowship.

Studies in health technology and informatics
Insights derived from successfully scaling a Clinical AI NHS Fellowship, addressing the scarcity of professionals proficient in clinical and Artificial Intelligence (AI) domains. Approach focus on operationalising a novel educational route critical f...

Deep Learning for Breast Cancer Risk Prediction: Application to a Large Representative UK Screening Cohort.

Radiology. Artificial intelligence
Purpose To develop an artificial intelligence (AI) deep learning tool capable of predicting future breast cancer risk from a current negative screening mammographic examination and to evaluate the model on data from the UK National Health Service Bre...

Artificial intelligence-generated patient information leaflets: a comparison of contents according to British Association of Dermatologists standards.

Clinical and experimental dermatology
BACKGROUND: Patient information leaflets (PILs) can supplement a clinical consultation and provide additional information for a patient to read in their own time. A wide range of PILs are available for distribution by the British Association of Derma...

Predicting type 1 diabetes in children using electronic health records in primary care in the UK: development and validation of a machine-learning algorithm.

The Lancet. Digital health
BACKGROUND: Children presenting to primary care with suspected type 1 diabetes should be referred immediately to secondary care to avoid life-threatening diabetic ketoacidosis. However, early recognition of children with type 1 diabetes is challengin...

An Interpretable Population Graph Network to Identify Rapid Progression of Alzheimer's Disease Using UK Biobank.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Alzheimer's disease (AD) manifests with varying progression rates across individuals, necessitating the understanding of their intricate patterns of cognition decline that could contribute to effective strategies for risk monitoring. In this study, w...

Association between Resting Heart Rate and Machine Learning-Based Brain Age in Middle- and Older-Age.

The journal of prevention of Alzheimer's disease
BACKGROUND: Resting heart rate (RHR), has been related to increased risk of dementia, but the relationship between RHR and brain age is unclear.