Dexter Canoy

8.1k total citations · 1 hit paper
82 papers, 4.2k citations indexed

About

Dexter Canoy is a scholar working on Cardiology and Cardiovascular Medicine, Public Health, Environmental and Occupational Health and Epidemiology. According to data from OpenAlex, Dexter Canoy has authored 82 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Cardiology and Cardiovascular Medicine, 26 papers in Public Health, Environmental and Occupational Health and 16 papers in Epidemiology. Recurrent topics in Dexter Canoy's work include Obesity, Physical Activity, Diet (15 papers), Blood Pressure and Hypertension Studies (13 papers) and Chronic Disease Management Strategies (9 papers). Dexter Canoy is often cited by papers focused on Obesity, Physical Activity, Diet (15 papers), Blood Pressure and Hypertension Studies (13 papers) and Chronic Disease Management Strategies (9 papers). Dexter Canoy collaborates with scholars based in United Kingdom, Australia and United States. Dexter Canoy's co-authors include Kazem Rahimi, Sheila Bingham, Robert Luben, Nicholas J. Wareham, Nicholas Day, Kay‐Tee Khaw, Gholamreza Salimi‐Khorshidi, Ailsa Welch, Iain Buchan and Milad Nazarzadeh and has published in prestigious journals such as The Lancet, Circulation and PLoS ONE.

In The Last Decade

Dexter Canoy

80 papers receiving 4.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

BEHRT: Transformer for Electronic Health Records

2020 292 citations Yikuan Li, Shishir Rao et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Dexter Canoy United Kingdom	37	1.1k	934	862	688	517	82	4.2k
Randi E. Foraker United States	31	2.2k 1.9×	1.1k 1.1×	518 0.6×	641 0.9×	169 0.3×	174	4.8k
Giok Ong United Kingdom	9	895 0.8×	1.0k 1.1×	1.2k 1.4×	941 1.4×	243 0.5×	9	7.2k
Michele Freeman United States	35	1.3k 1.1×	766 0.8×	323 0.4×	1.6k 2.4×	216 0.4×	94	6.2k
Martin Landray United Kingdom	37	2.1k 1.8×	1.3k 1.4×	1.4k 1.6×	1.3k 1.9×	276 0.5×	124	11.4k
David C. Kaelber United States	34	1.6k 1.4×	1.5k 1.6×	539 0.6×	877 1.3×	91 0.2×	218	6.9k
Ian Douglas United Kingdom	37	963 0.8×	852 0.9×	1.3k 1.5×	1.0k 1.5×	91 0.2×	155	7.0k
Davood Khalili Iran	34	879 0.8×	1.0k 1.1×	488 0.6×	801 1.2×	134 0.3×	226	4.1k
Peter Brindle United Kingdom	19	2.0k 1.7×	1.1k 1.2×	281 0.3×	864 1.3×	230 0.4×	24	5.3k
Mark R. Cobain United Kingdom	7	2.5k 2.1×	877 0.9×	582 0.7×	671 1.0×	124 0.2×	7	5.5k
Jørgen Hilden Denmark	36	610 0.5×	429 0.5×	401 0.5×	581 0.8×	250 0.5×	148	5.6k

Countries citing papers authored by Dexter Canoy

Since Specialization

Citations

This map shows the geographic impact of Dexter Canoy's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Dexter Canoy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dexter Canoy more than expected).

Fields of papers citing papers by Dexter Canoy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dexter Canoy. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Dexter Canoy. The network helps show where Dexter Canoy may publish in the future.

Co-authorship network of co-authors of Dexter Canoy

This figure shows the co-authorship network connecting the top 25 collaborators of Dexter Canoy. A scholar is included among the top collaborators of Dexter Canoy based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Dexter Canoy. Dexter Canoy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Bidel, Zeinab, Milad Nazarzadeh, Dexter Canoy, et al.. (2023). Sex-Specific Effects of Blood Pressure Lowering Pharmacotherapy for the Prevention of Cardiovascular Disease: An Individual Participant-Level Data Meta-Analysis. Hypertension. 80(11). 2293–2302. 11 indexed citations

Nazarzadeh, Milad, Zeinab Bidel, H. Mohseni, et al.. (2022). Blood pressure and risk of venous thromboembolism: a cohort analysis of 5.5 million UK adults and Mendelian randomization studies. Cardiovascular Research. 119(3). 835–842. 15 indexed citations

Tran, Jenny, Robyn Norton, Dexter Canoy, et al.. (2021). Multi-morbidity and blood pressure trajectories in hypertensive patients: A multiple landmark cohort study. PLoS Medicine. 18(6). e1003674–e1003674. 9 indexed citations

Canoy, Dexter, Nicholas C. Harvey, Daniel Prieto‐Alhambra, et al.. (2021). Elevated blood pressure, antihypertensive medications and bone health in the population: revisiting old hypotheses and exploring future research directions. Osteoporosis International. 33(2). 315–326. 17 indexed citations

Canoy, Dexter, Jenny Tran, Mariagrazia Zottoli, et al.. (2021). Association between cardiometabolic disease multimorbidity and all-cause mortality in 2 million women and men registered in UK general practices. BMC Medicine. 19(1). 258–258. 39 indexed citations

Nazarzadeh, Milad, Ana‐Catarina Pinho‐Gomes, Zeinab Bidel, et al.. (2020). Plasma lipids and risk of aortic valve stenosis: a Mendelian randomization study. European Heart Journal. 41(40). 3913–3920. 95 indexed citations

Solares, José Roberto Ayala, Francesca Raimondi, Yajie Zhu, et al.. (2020). Deep learning for electronic health records: A comparative review of multiple deep neural architectures. Journal of Biomedical Informatics. 101. 103337–103337. 146 indexed citations

Rahimi, Kazem, Dexter Canoy, Milad Nazarzadeh, et al.. (2019). Investigating the stratified efficacy and safety of pharmacological blood pressure-lowering: an overall protocol for individual patient-level data meta-analyses of over 300 000 randomised participants in the new phase of the Blood Pressure Lowering Treatment Trialists’ Collaboration (BPLTTC). BMJ Open. 9(5). e028698–e028698. 18 indexed citations

Rahimian, Fatemeh, Gholamreza Salimi‐Khorshidi, Amir H. Payberah, et al.. (2018). Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records. PLoS Medicine. 15(11). e1002695–e1002695. 90 indexed citations

10.

Tran, Jenny, Robyn Norton, Nathalie Conrad, et al.. (2018). Patterns and temporal trends of comorbidity among adult patients with incident cardiovascular disease in the UK between 2000 and 2014: A population-based cohort study. PLoS Medicine. 15(3). e1002513–e1002513. 96 indexed citations

11.

Canoy, Dexter, Benjamin J. Cairns, Angela Balkwill, et al.. (2016). Hypertension in pregnancy and risk of coronary heart disease and stroke: A prospective study in a large UK cohort. International Journal of Cardiology. 222. 1012–1018. 36 indexed citations

12.

Canoy, Dexter, Thomas M. Barber, Anneli Pouta, et al.. (2014). Serum sex hormone-binding globulin and testosterone in relation to cardiovascular disease risk factors in young men: a population-based study. European Journal of Endocrinology. 170(6). 863–872. 31 indexed citations

13.

Canoy, Dexter, Benjamin J. Cairns, Angela Balkwill, et al.. (2013). Body mass index and incident coronary heart disease in women: a population-based prospective study. BMC Medicine. 11(1). 87–87. 39 indexed citations

14.

Patel, Swatee, Alina Rodriguez, Mark P. Little, et al.. (2011). Associations between pre-pregnancy obesity and asthma symptoms in adolescents. Journal of Epidemiology & Community Health. 66(9). 809–814. 57 indexed citations

15.

Andersen, Lise Geisler, Lars Ängquist, Michael Gamborg, et al.. (2009). Birth Weight in Relation to Leisure Time Physical Activity in Adolescence and Adulthood: Meta-Analysis of Results from 13 Nordic Cohorts. PLoS ONE. 4(12). e8192–e8192. 67 indexed citations

16.

Tzoulaki, Ioanna, Marjo‐Riitta Järvelin, Anna-Liisa Hartikainen, et al.. (2008). Size at birth, weight gain over the life course, and low-grade inflammation in young adulthood: northern Finland 1966 birth cohort study. European Heart Journal. 29(8). 1049–1056. 88 indexed citations

17.

Canoy, Dexter & Iain Buchan. (2007). Challenges in obesity epidemiology. Obesity Reviews. 8(s1). 1–11. 69 indexed citations

18.

Gamborg, Michael, Liisa Byberg, Finn Rasmussen, et al.. (2007). Birth Weight and Systolic Blood Pressure in Adolescence and Adulthood: Meta-Regression Analysis of Sex- and Age-specific Results from 20 Nordic Studies. American Journal of Epidemiology. 166(6). 634–645. 130 indexed citations

19.

Canoy, Dexter, Juha Pekkanen, Paul Elliott, et al.. (2006). Early growth and adult respiratory function in men and women followed from the fetal period to adulthood. Thorax. 62(5). 396–402. 113 indexed citations

20.

Canoy, Dexter, Nicholas J. Wareham, Ailsa Welch, et al.. (2005). Plasma ascorbic acid concentrations and fat distribution in 19 068 British men and women in the European Prospective Investigation into Cancer and Nutrition Norfolk cohort study. American Journal of Clinical Nutrition. 82(6). 1203–1209. 108 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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