AIMC Topic: England
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Trustworthy artificial intelligence and ethical design: public perceptions of trustworthiness of an AI-based decision-support tool in the context of intrapartum care.
BMC medical ethics
Jun 20, 2023
BACKGROUND: Despite the recognition that developing artificial intelligence (AI) that is trustworthy is necessary for public acceptability and the successful implementation of AI in healthcare contexts, perspectives from key stakeholders are often ab...
Characterising the nationwide burden and predictors of unkept outpatient appointments in the National Health Service in England: A cohort study using a machine learning approach.
PLoS medicine
Oct 12, 2021
BACKGROUND: Unkept outpatient hospital appointments cost the National Health Service £1 billion each year. Given the associated costs and morbidity of unkept appointments, this is an issue requiring urgent attention. We aimed to determine rates of un...
Contrasting factors associated with COVID-19-related ICU admission and death outcomes in hospitalised patients by means of Shapley values.
PLoS computational biology
Jun 23, 2021
Identification of those at greatest risk of death due to the substantial threat of COVID-19 can benefit from novel approaches to epidemiology that leverage large datasets and complex machine-learning models, provide data-driven intelligence, and guid...
Logistic regression and machine learning predicted patient mortality from large sets of diagnosis codes comparably.
Journal of clinical epidemiology
Jan 22, 2021
OBJECTIVE: The objective of the study was to compare the performance of logistic regression and boosted trees for predicting patient mortality from large sets of diagnosis codes in electronic healthcare records.
A comparison of the value of two machine learning predictive models to support bovine tuberculosis disease control in England.
Preventive veterinary medicine
Jan 15, 2021
Nearly a decade into Defra's current eradication strategy, bovine tuberculosis (bTB) remains a serious animal health problem in England, with c.30,000 cattle slaughtered annually in the fight against this insidious disease. There is an urgent need to...
Consistency of variety of machine learning and statistical models in predicting clinical risks of individual patients: longitudinal cohort study using cardiovascular disease as exemplar.
BMJ (Clinical research ed.)
Nov 4, 2020
OBJECTIVE: To assess the consistency of machine learning and statistical techniques in predicting individual level and population level risks of cardiovascular disease and the effects of censoring on risk predictions.
Uptake and accessibility of surgical robotics in England.
The international journal of medical robotics + computer assisted surgery : MRCAS
Oct 7, 2020
BACKGROUND: The distribution, utilisation and accessibility of surgical robotics in England is unknown.
Predicting bovine tuberculosis status of dairy cows from mid-infrared spectral data of milk using deep learning.
Journal of dairy science
Aug 20, 2020
Bovine tuberculosis (bTB) is a zoonotic disease in cattle that is transmissible to humans, distributed worldwide, and considered endemic throughout much of England and Wales. Mid-infrared (MIR) analysis of milk is used routinely to predict fat and pr...
Using de-identified electronic health records to research mental health supported housing services: A feasibility study.
PloS one
Aug 20, 2020
BACKGROUND: Mental health supported housing services are a key component in the rehabilitation of people with severe and complex needs. They are implemented widely in the UK and other deinstitutionalised countries but there have been few empirical st...
Using machine learning to improve our understanding of injury risk and prediction in elite male youth football players.
Journal of science and medicine in sport
May 18, 2020
OBJECTIVES: The purpose of this study was to examine whether the use of machine learning improved the ability of a neuromuscular screen to identify injury risk factors in elite male youth football players.
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