Author Page for Dexter Canoy

Using National Electronic Health Records for Pandemic Preparedness: Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19

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Using National Electronic Health Records for Pandemic Preparedness: Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19

Number of pages: 19 Posted: 08 Mar 2022

University College London - Institute of Health Informatics, University College London - Institute of Health Informatics, University College London - Institute of Health Informatics, University College London - Institute of Health Informatics, University College London - Institute of Health Informatics, University College London - Institute of Health Informatics, University College London - Institute of Health Informatics, BioPharmaceuticals Medical, AstraZeneca - Medical and Scientific Affairs, BioPharmaceuticals Medical, AstraZeneca - Medical and Scientific Affairs, University of Oxford - Rheumatology and Musculoskeletal Sciences, University of Leicester - Leicester Diabetes Centre, University of Aberdeen - Medical Sciences and Nutrition, Swansea University - Population Data Science, University of Oxford - Nuffield Department of Women’s and Reproductive Health, Swansea University - Population Data Science, University of Glasgow - Institute of Cardiovascular and Medical Sciences, Health Data Research UK - BHF Data Science Centre, Health Data Research UK - BHF Data Science Centre, University of Leicester - Leicester Diabetes Centre, University College London - Institute of Health Informatics, University College London - Institute of Health Informatics, Health Data Research UK - BHF Data Science Centre, University College London - Institute of Health Informatics and affiliation not provided to SSRN

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Using National Electronic Health Records for Pandemic Preparedness: Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19

Number of pages: 20 Posted: 25 Mar 2022

University College London - Institute of Health Informatics, University College London - Institute of Health Informatics, University College London - Institute of Health Informatics, University College London - Institute of Health Informatics, University College London - Institute of Health Informatics, University College London - Institute of Health Informatics, University College London - Institute of Health Informatics, BioPharmaceuticals Medical, AstraZeneca - Medical and Scientific Affairs, BioPharmaceuticals Medical, AstraZeneca - Medical and Scientific Affairs, University of Oxford - Rheumatology and Musculoskeletal Sciences, University of Leicester - Leicester Diabetes Centre, University of Aberdeen - Medical Sciences and Nutrition, Swansea University - Population Data Science, University of Oxford - Nuffield Department of Women’s and Reproductive Health, Swansea University - Population Data Science, University of Glasgow - Institute of Cardiovascular and Medical Sciences, Health Data Research UK - BHF Data Science Centre, Health Data Research UK - BHF Data Science Centre, University of Leicester - Leicester Diabetes Centre, University College London - Institute of Health Informatics, University College London - Institute of Health Informatics, Health Data Research UK - BHF Data Science Centre, University College London - Institute of Health Informatics and Independent

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2.

Assessment of Risk Prediction Models Applied to Longitudinal Electronic Health Record Data for the Prediction of Major Cardiovascular Events in the Presence of Data Shifts

Number of pages: 22 Posted: 03 Feb 2022

Yikuan Li, Gholamreza Salimi-Khorshidi, Shishir Rao, Dexter Canoy, Abdelaali Hassaine, Thomas Lukasiewicz, Kazem Rahimi and Mohammad Mamouei

University of Oxford - Deep Medicine, University of Oxford - Deep Medicine, University of Oxford - Deep Medicine, University of Oxford - Nuffield Department of Women’s and Reproductive Health, University of Oxford - Deep Medicine, University of Oxford - Computing Laboratory, Deep Medicine, NDWRH, University of Oxford and University of Oxford - Deep Medicine

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Elevated Blood Pressure, Antihypertensive Medications and Bone Health in the Population: Revisiting Old Hypotheses and Exploring Future Research Directions

Posted: 14 May 2021

Dexter Canoy, Nicholas Harvey, Daniel Prieto-Alhambra, Cyrus Cooper, Haakon E. Meyer, Bjørn Olav Åsvold, Milad Nazarzadeh and Kazem Rahimi

University of Oxford - Nuffield Department of Women’s and Reproductive Health, University of Southampton - Medical Research Council Life Course Epidemiology Unit, University of Oxford - Rheumatology and Musculoskeletal Sciences, University of Southampton - Medical Research Council Life Course Epidemiology Unit, Norwegian Institute of Public Health, K.G. Jebsen Center for Genetic Epidemiology, Norwegian University of Science and Technology, Deep Medicine, NDWRH, University of Oxford and Deep Medicine, NDWRH, University of Oxford

Dexter Canoy

University of Oxford - Nuffield Department of Women’s and Reproductive Health

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Scholarly Papers (3)

Using National Electronic Health Records for Pandemic Preparedness: Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19

Using National Electronic Health Records for Pandemic Preparedness: Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19

Abstract:

Using National Electronic Health Records for Pandemic Preparedness: Validation of a Parsimonious Model for Predicting Excess Deaths Among Those With COVID-19

Abstract:

Assessment of Risk Prediction Models Applied to Longitudinal Electronic Health Record Data for the Prediction of Major Cardiovascular Events in the Presence of Data Shifts

Abstract:

Elevated Blood Pressure, Antihypertensive Medications and Bone Health in the Population: Revisiting Old Hypotheses and Exploring Future Research Directions

Abstract: