Tim Churches

2.0k total citations
59 papers, 1.3k citations indexed

About

Tim Churches is a scholar working on Epidemiology, Management Science and Operations Research and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Tim Churches has authored 59 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Epidemiology, 11 papers in Management Science and Operations Research and 9 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Tim Churches's work include Data-Driven Disease Surveillance (12 papers), Data Quality and Management (11 papers) and Influenza Virus Research Studies (7 papers). Tim Churches is often cited by papers focused on Data-Driven Disease Surveillance (12 papers), Data Quality and Management (11 papers) and Influenza Virus Research Studies (7 papers). Tim Churches collaborates with scholars based in Australia, United Kingdom and United States. Tim Churches's co-authors include Peter Christen, Rohan A. Baxter, David Muscatello, Louisa Jorm, Wei Xing Zheng, Kim Lim, Sarah Thackway, Raphael Grzebieta, Jake Olivier and Scott R. Walter and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Tim Churches

55 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tim Churches Australia 18 375 363 300 215 182 59 1.3k
Mohammad S. Jalali United States 24 245 0.7× 160 0.4× 133 0.4× 441 2.1× 347 1.9× 113 1.7k
Douglas B. Fridsma United States 21 175 0.5× 202 0.6× 212 0.7× 282 1.3× 399 2.2× 48 1.9k
Marc Cuggia France 19 392 1.0× 99 0.3× 261 0.9× 210 1.0× 61 0.3× 106 1.4k
Shaun J. Grannis United States 27 927 2.5× 395 1.1× 351 1.2× 413 1.9× 84 0.5× 139 2.4k
Zoie Shui-Yee Wong Japan 19 114 0.3× 115 0.3× 227 0.8× 110 0.5× 76 0.4× 73 1.4k
Brian E. Dixon United States 26 642 1.7× 168 0.5× 157 0.5× 346 1.6× 89 0.5× 202 2.3k
Nicole G. Weiskopf United States 19 401 1.1× 512 1.4× 634 2.1× 434 2.0× 86 0.5× 39 2.6k
Toan C. Ong United States 14 135 0.4× 168 0.5× 172 0.6× 83 0.4× 99 0.5× 38 786
Hamish Fraser United States 30 639 1.7× 171 0.5× 293 1.0× 388 1.8× 389 2.1× 104 3.2k
Peter J. Embí United States 29 314 0.8× 216 0.6× 337 1.1× 708 3.3× 114 0.6× 103 2.8k

Countries citing papers authored by Tim Churches

Since Specialization
Citations

This map shows the geographic impact of Tim Churches'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 Tim Churches with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Churches more than expected).

Fields of papers citing papers by Tim Churches

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tim Churches. 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 Tim Churches. The network helps show where Tim Churches may publish in the future.

Co-authorship network of co-authors of Tim Churches

This figure shows the co-authorship network connecting the top 25 collaborators of Tim Churches. A scholar is included among the top collaborators of Tim Churches 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 Tim Churches. Tim Churches is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Liu, Leibo, Victoria Blake, Tim Churches, et al.. (2025). Using natural language processing to extract information from clinical text in electronic medical records for populating clinical registries: a systematic review. Journal of the American Medical Informatics Association. 33(2). 484–499.
2.
Churches, Tim, et al.. (2024). Applying and Improving a Publicly Available Medication NER Pipeline in a Clinical Cancer EMR. Studies in health technology and informatics. 310. 679–684.
3.
4.
Perez‐Concha, Oscar, Mark Hanly, Juliana de Oliveira Costa, et al.. (2023). Enriching Data Science and Health Care Education: Application and Impact of Synthetic Data Sets Through the Health Gym Project. JMIR Medical Education. 10. e51388–e51388. 5 indexed citations
5.
Churches, Tim, Justine Naylor, Wei Xuan, et al.. (2022). Association between VTE and antibiotic prophylaxis guideline compliance and patient-reported outcomes after total hip and knee arthroplasty: an observational study. Journal of Patient-Reported Outcomes. 6(1). 110–110. 1 indexed citations
6.
Hanly, Mark, Tim Churches, Oisín Fitzgerald, et al.. (2022). Modelling vaccination capacity at mass vaccination hubs and general practice clinics: a simulation study. BMC Health Services Research. 22(1). 1059–1059. 12 indexed citations
7.
Churches, Tim, Justine Naylor, Wei Xuan, et al.. (2021). Non-compliance with clinical guidelines increases the risk of complications after primary total hip and knee joint replacement surgery. PLoS ONE. 16(11). e0260146–e0260146. 13 indexed citations
8.
Hanly, Mark, Tim Churches, Oisín Fitzgerald, C. Raina MacIntyre, & Louisa Jorm. (2021). Vaccinating Australia: How long will it take?. Vaccine. 40(17). 2491–2497. 7 indexed citations
9.
Churches, Tim & Louisa Jorm. (2020). Flexible, Freely Available Stochastic Individual Contact Model for Exploring COVID-19 Intervention and Control Strategies: Development and Simulation. JMIR Public Health and Surveillance. 6(3). e18965–e18965. 11 indexed citations
10.
11.
Sparks, Ross, Chris Carter, Petra L. Graham, et al.. (2010). Understanding sources of variation in syndromic surveillance for early warning of natural or intentional disease outbreaks. IIE Transactions. 42(9). 613–631. 45 indexed citations
12.
Churches, Tim. (2010). Data and Graphing Errors in the Voukelatos and Rissel Paper. Journal of the Australasian College of Road Safety. 21(4). 62–64. 3 indexed citations
13.
Churches, Tim, Stephen Conaty, Robin Gilmour, & David Muscatello. (2010). Reflections on public health surveillance of pandemic (H1N1) 2009 influenza in NSW. New South Wales Public Health Bulletin. 21(2). 19–19. 6 indexed citations
14.
Cretikos, Michelle, David Muscatello, Stephen Conaty, et al.. (2009). Progression and impact of the first winter wave of the 2009 pandemic H1N1 influenza in New South Wales, Australia.. Eurosurveillance. 14(42). 48 indexed citations
15.
Summerhayes, Richard, Paul Holder, John Beard, et al.. (2006). Automated geocoding of routinely collected health data in New South Wales. New South Wales Public Health Bulletin. 17(4). 33–33. 8 indexed citations
16.
Muscatello, David, Michelle Cretikos, Mark J. Bartlett, et al.. (2006). Planning for pandemic influenza surveillance in NSW. New South Wales Public Health Bulletin. 17(10). 146–146. 1 indexed citations
17.
Churches, Tim & Peter Christen. (2004). Some methods for blindfolded record linkage. BMC Medical Informatics and Decision Making. 4(1). 9–9. 92 indexed citations
18.
Christen, Peter, et al.. (2002). Parallel Computing Techniques for High-Performance Probabilistic Record Linkage. 3 indexed citations
19.
Churches, Tim, et al.. (2002). Preparation of name and address data for record linkage using hidden Markov models. BMC Medical Informatics and Decision Making. 2(1). 9–9. 76 indexed citations
20.
McCredie, Margaret, Marylon Coates, Tim Churches, & Richard Taylor. (1991). Cancer incidence in New South Wales, Australia. European Journal of Cancer and Clinical Oncology. 27(7). 928–931. 20 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Mohammad S. Jalali Breakdown of academic impact, for papers by Douglas B. Fridsma Breakdown of academic impact, for papers by Marc Cuggia Breakdown of academic impact, for papers by Shaun J. Grannis Breakdown of academic impact, for papers by Zoie Shui-Yee Wong Breakdown of academic impact, for papers by Brian E. Dixon Breakdown of academic impact, for papers by Nicole G. Weiskopf Breakdown of academic impact, for papers by Toan C. Ong Breakdown of academic impact, for papers by Hamish Fraser Breakdown of academic impact, for papers by Peter J. Embí
Rankless by CCL
2026