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Usman Farooqui

Observed names: Farooqui, Usman, U Farooqui, U. Farooqui
ORCID: 0000-0002-3443-1912
Observed ORCID: 0000-0002-3443-1912
OpenAlex ID: A5089282114
Predicting Atrial Fibrillation in Primary Care Using Machine Learning
2018 · Nathan R. Hill, Daniel Ayoubkhani, et al. · PLoS ONE · 141
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Peritoneal Dialysis and In-Centre Haemodialysis: A Cost-Utility Analysis from a UK Payer Perspective
2014 · Catrin Treharne, Frank Xiaoqing Liu, et al. · Applied Health Economics and Health Policy · 71
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Detecting undiagnosed atrial fibrillation in UK primary care: Validation of a machine learning prediction algorithm in a retrospective cohort study
2020 · Sara Sekelj, Belinda Sandler, et al. · European Journal of Preventive Cardiology · 52
Meta-Analysis Comparing Apixaban Versus Rivaroxaban for Management of Patients With Nonvalvular Atrial Fibrillation
2021 · Mamas A. Mamas, Sarah Batson, et al. · The American Journal of Cardiology · 44
Identification of undiagnosed atrial fibrillation using a machine learning risk-prediction algorithm and diagnostic testing (PULsE-AI) in primary care: a multi-centre randomized controlled trial in England
2022 · Nathan R Hill, Lara Groves, et al. · European Heart Journal - Digital Health · 43
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Cost-effectiveness of targeted screening for the identification of patients with atrial fibrillation: evaluation of a machine learning risk prediction algorithm
2019 · Nathan R. Hill, Belinda Sandler, et al. · Journal of Medical Economics · 41
A Systematic Review of Network Meta-Analyses and Real-World Evidence Comparing Apixaban and Rivaroxaban in Nonvalvular Atrial Fibrillation
2020 · Nathan R. Hill, Belinda Sandler, et al. · Clinical and Applied Thrombosis/Hemostasis · 30
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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
2022 · Nathan R. Hill, Lara Groves, et al. · Journal of Medical Economics · 29
Budget impact analysis of a machine learning algorithm to predict high risk of atrial fibrillation among primary care patients
2022 · Tomasz Szymanski, Rachel Ashton, et al. · EP Europace · 26
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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
2020 · Nathan R. Hill, Chris Arden, et al. · Contemporary Clinical Trials · 25
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Using machine learning to predict anticoagulation control in atrial fibrillation: A UK Clinical Practice Research Datalink study
2021 · Jason Gordon, Max Norman, et al. · Informatics in Medicine Unlocked · 14
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Application of a machine learning algorithm for detection of atrial fibrillation in secondary care
2020 · Kevin G. Pollock, Sara Sekelj, et al. · IJC Heart & Vasculature · 11
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Machine Learning to Detect and Diagnose Atrial Fibrillation and Atrial Flutter (AF/F) Using Routine Clinical Data
2018 · NR Hill, D Ayoubkhani, et al. · Value in Health · 2
Undertaking multi-centre randomised controlled trials in primary care: learnings and recommendations from the PULsE-AI trial researchers
2024 · Kevin G. Pollock, Carissa Dickerson, et al. · BMC Family Practice · 1
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Budget impact analysis of peritoneal dialysis vs. conventional in-center hemodialysis in the United Kingdom
2013 · Frank Xiaoqing Liu, Robert J. Leipold, et al. · F1000Research · 1
Peritoneal dialysis - A
2013 · M. Ito, A. Emami-Naini, et al. · Nephrology Dialysis Transplantation · 1
POSC125 Identification of Undiagnosed Atrial Fibrillation Using a Machine Learning Risk Prediction Algorithm and Diagnostic Testing (PULSE-AI) in Primary Care: Health Economic Impact Assessment of a UK Randomised Controlled Trial
2022 · NR Hill, L Groves, et al. · Value in Health
PCV93 Using Machine Learning to Predict Anticoagulation Control in Atrial Fibrillation: A UK Retrospective Database Study
2020 · J. Gordon, M. Norman, et al. · Value in Health
Pcv50 Cost-effectiveness of Targeted Screening Using a Machine Learning Risk Prediction Tool for the Identification of Patients With Atrial Fibrillation
2019 · N. Hill, S. Lister, et al. · Value in Health
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Validation and Evaluation of Memorial Symptom Assessment Scale Short-Form (Msas-Sf)In a Romanian Cohort of Hemodialysis Patients
2015 · Tatsuyoshi Ikenoue, M. Wang, et al. · The Medical-Surgical Journal
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Dialysis. Epidemiology, Outcome Research, Health Services 1
2014 · T. Ikenoue, K. Koike, et al. · Nephrology Dialysis Transplantation
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Works count: 30
Citation count: 532
H-index: 11
I10-index: 12
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