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BMJ Open
|
October 6, 2023
Can we collect health-related quality of life information from anticoagulated atrial fibrillation participants who have recently experienced a bleed? An observational feasibility study in primary and secondary care in Wales and through a UK online forum
Hayley Anne Hutchings, Kirsty J Lanyon, Gail Holland, et al.
Plos One
|
November 2, 2019
Predicting atrial fibrillation in primary care using machine learning
Nathan R Hill, Daniel Ayoubkhani, Phil McEwan, et al.
Pilot and Feasibility Studies
|
August 12, 2022
Investigating the feasibility of recruitment to an observational, quality-of-life study of patients diagnosed with atrial fibrillation (AF) who have experienced a bleed while anticoagulated: EQUAL-AF feasibility study protocol
Hayley A Hutchings, Kirsty Lanyon, Steven Lister, et al.
Journal of the American Heart Association
|
March 3, 2023
Sex Differences in Oral Anticoagulation Therapy in Patients Hospitalized With Atrial Fibrillation: A Nationwide Cohort Study
Kuan Ken Lee, Dimitrios Doudesis, Rong Bing, et al.
Journal of Medical Economics
|
July 14, 2022
Identification of undiagnosed atrial fibrillation using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI) in primary care: cost-effectiveness of a screening strategy evaluated in a randomized controlled trial in England
Nathan R Hill, Lara Groves, Carissa Dickerson, et al.
Contemporary Clinical Trials
|
October 22, 2020
Identification of undiagnosed atrial fibrillation patients using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI): Study protocol for a randomised controlled trial
Nathan R Hill, Chris Arden, Lee Beresford-Hulme, et al.
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Showing results (11-20 of 16) with videos related to
Sort By:
Page
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You have reached the last page of results.
This site can display upto 16 results.
BMJ Open
|
October 6, 2023
Can we collect health-related quality of life information from anticoagulated atrial fibrillation participants who have recently experienced a bleed? An observational feasibility study in primary and secondary care in Wales and through a UK online forum
Hayley Anne Hutchings, Kirsty J Lanyon, Gail Holland, et al.
Plos One
|
November 2, 2019
Predicting atrial fibrillation in primary care using machine learning
Nathan R Hill, Daniel Ayoubkhani, Phil McEwan, et al.
Pilot and Feasibility Studies
|
August 12, 2022
Investigating the feasibility of recruitment to an observational, quality-of-life study of patients diagnosed with atrial fibrillation (AF) who have experienced a bleed while anticoagulated: EQUAL-AF feasibility study protocol
Hayley A Hutchings, Kirsty Lanyon, Steven Lister, et al.
Journal of the American Heart Association
|
March 3, 2023
Sex Differences in Oral Anticoagulation Therapy in Patients Hospitalized With Atrial Fibrillation: A Nationwide Cohort Study
Kuan Ken Lee, Dimitrios Doudesis, Rong Bing, et al.
Journal of Medical Economics
|
July 14, 2022
Identification of undiagnosed atrial fibrillation using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI) in primary care: cost-effectiveness of a screening strategy evaluated in a randomized controlled trial in England
Nathan R Hill, Lara Groves, Carissa Dickerson, et al.
Contemporary Clinical Trials
|
October 22, 2020
Identification of undiagnosed atrial fibrillation patients using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI): Study protocol for a randomised controlled trial
Nathan R Hill, Chris Arden, Lee Beresford-Hulme, et al.
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