AIMC Topic: United Kingdom

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Mammography Breast Cancer Screening Triage Using Deep Learning: A UK Retrospective Study.

Radiology
Background Breast screening enables early detection of cancers; however, most women have normal mammograms, resulting in repetitive and resource-intensive reading tasks. Purpose To investigate if deep learning (DL) algorithms can be used to triage ma...

Development and validation of artificial intelligence-based prescreening of large-bowel biopsies taken in the UK and Portugal: a retrospective cohort study.

The Lancet. Digital health
BACKGROUND: Histopathological examination is a crucial step in the diagnosis and treatment of many major diseases. Aiming to facilitate diagnostic decision making and improve the workload of pathologists, we developed an artificial intelligence (AI)-...

The time is now: making the case for a UK registry of deployment of radiology artificial intelligence applications.

Clinical radiology
Artificial intelligence (AI)-based healthcare applications (apps) are rapidly evolving, and radiology is a target specialty for their implementation. In this paper, we put the case for a national deployment registry to track the spread of AI apps int...

Pressing issues in healthcare digital technologies and AI.

British journal of nursing (Mark Allen Publishing)
Lecturer in Law, Birmingham Law School, University of Birmingham, discusses several reports addressing patient safety, ethical and legal issues in healthcare digital technologies and artificial intelligence.

POPDx: an automated framework for patient phenotyping across 392 246 individuals in the UK Biobank study.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: For the UK Biobank, standardized phenotype codes are associated with patients who have been hospitalized but are missing for many patients who have been treated exclusively in an outpatient setting. We describe a method for phenotype recog...

Neural network-based integration of polygenic and clinical information: development and validation of a prediction model for 10-year risk of major adverse cardiac events in the UK Biobank cohort.

The Lancet. Digital health
BACKGROUND: In primary cardiovascular disease prevention, early identification of high-risk individuals is crucial. Genetic information allows for the stratification of genetic predispositions and lifetime risk of cardiovascular disease. However, tow...

Hazards for the Implementation and Use of Artificial Intelligence Enabled Digital Health Interventions, a UK Perspective.

Studies in health technology and informatics
BACKGROUND: Artificial Intelligence (AI) has seen an increased application within digital healthcare interventions (DHIs). DHIs use entails challenges about their safety assurance. Exacerbated by regulatory requirements, in the UK, this places the on...

The computer says no: AI, health law, ethics and patient safety.

British journal of nursing (Mark Allen Publishing)
, Lecturer in Law, Birmingham Law School, University of Birmingham, discusses some recent reports on artificial intelligence (AI) and machine learning in the context of law, ethics and patient safety.