Ken Fullerton

1.2k total citations
27 papers, 801 citations indexed

About

Ken Fullerton is a scholar working on Emergency Medical Services, Epidemiology and Artificial Intelligence. According to data from OpenAlex, Ken Fullerton has authored 27 papers receiving a total of 801 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Emergency Medical Services, 7 papers in Epidemiology and 5 papers in Artificial Intelligence. Recurrent topics in Ken Fullerton's work include Healthcare Operations and Scheduling Optimization (11 papers), Clinical practice guidelines implementation (5 papers) and Acute Ischemic Stroke Management (5 papers). Ken Fullerton is often cited by papers focused on Healthcare Operations and Scheduling Optimization (11 papers), Clinical practice guidelines implementation (5 papers) and Acute Ischemic Stroke Management (5 papers). Ken Fullerton collaborates with scholars based in United Kingdom, Malta and Canada. Ken Fullerton's co-authors include R. W. Stout, David McSherry, I. Davies, P A O'Neill, Derrick Bennett, Sally McClean, Lalit Garg, Maria Barton, Gilbert MacKenzie and Mick Power and has published in prestigious journals such as The Lancet, Stroke and Journal of the Operational Research Society.

In The Last Decade

Ken Fullerton

26 papers receiving 753 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ken Fullerton United Kingdom 13 283 173 156 118 111 27 801
John Gommans New Zealand 17 478 1.7× 315 1.8× 22 0.1× 23 0.2× 30 0.3× 60 974
Karin Ernström United States 19 540 1.9× 239 1.4× 39 0.3× 41 0.3× 11 0.1× 57 1.3k
Megan K. Yee United States 17 134 0.5× 53 0.3× 39 0.3× 26 0.2× 109 1.0× 49 1.1k
William R. Lewis United States 29 161 0.6× 36 0.2× 76 0.5× 14 0.1× 32 0.3× 87 2.5k
Boon Yeow Tan Singapore 19 111 0.4× 88 0.5× 154 1.0× 11 0.1× 17 0.2× 59 1.4k
Mukul Sharma Canada 25 785 2.8× 93 0.5× 42 0.3× 15 0.1× 55 0.5× 103 1.6k
Sy‐Jou Chen Taiwan 20 90 0.3× 39 0.2× 19 0.1× 23 0.2× 69 0.6× 77 877
Paul Gerrard United States 14 278 1.0× 109 0.6× 70 0.4× 22 0.2× 5 0.0× 31 653
Mohammed Yousufuddin United States 13 112 0.4× 33 0.2× 25 0.2× 19 0.2× 44 0.4× 50 874
Javaid Nauman Norway 25 101 0.4× 33 0.2× 21 0.1× 18 0.2× 90 0.8× 68 1.7k

Countries citing papers authored by Ken Fullerton

Since Specialization
Citations

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

Fields of papers citing papers by Ken Fullerton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ken Fullerton

This figure shows the co-authorship network connecting the top 25 collaborators of Ken Fullerton. A scholar is included among the top collaborators of Ken Fullerton 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 Ken Fullerton. Ken Fullerton 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.
Garg, Lalit, Sally McClean, Maria Barton, et al.. (2021). Evaluating Different Selection Criteria for Phase Type Survival Tree Construction. Big Data Research. 25. 100250–100250. 3 indexed citations
2.
Gillespie, Jennifer Z., Sally McClean, Lalit Garg, et al.. (2016). A multi-phase DES modelling framework for patient-centred care. Journal of the Operational Research Society. 67(10). 1239–1249. 17 indexed citations
3.
McClean, Sally, et al.. (2015). STOPGAP: Stroke patient management and capacity planning. Operations Research for Health Care. 6. 78–86. 3 indexed citations
4.
McClean, Sally, Lalit Garg, & Ken Fullerton. (2014). Costing Mixed Coxian Phase-type Systems with Poisson Arrivals. Communication in Statistics- Theory and Methods. 43(7). 1437–1452. 4 indexed citations
5.
Garg, Lalit, Sally McClean, Maria Barton, Brian J. Meenan, & Ken Fullerton. (2013). An Extended Mixture Distribution Survival Tree for Patient Pathway Prognostication. Communication in Statistics- Theory and Methods. 42(16). 2912–2934. 3 indexed citations
6.
Barton, Maria, Sally McClean, Jennifer Z. Gillespie, et al.. (2012). Is it beneficial to increase the provision of thrombolysis?-- a discrete-event simulation model. QJM. 105(7). 665–673. 19 indexed citations
7.
Gillespie, Jennifer Z., Sally McClean, Bryan Scotney, et al.. (2011). Costing hospital resources for stroke patients using phase-type models. Health Care Management Science. 14(3). 279–291. 14 indexed citations
8.
McClean, Sally, Maria Barton, Lalit Garg, & Ken Fullerton. (2011). A modeling framework that combines markov models and discrete-event simulation for stroke patient care. ACM Transactions on Modeling and Computer Simulation. 21(4). 1–26. 46 indexed citations
9.
Barton, Maria, Sally McClean, Lalit Garg, & Ken Fullerton. (2010). Modelling costs of bed occupancy and delayed discharge of post-stroke patients. 1–6. 10 indexed citations
10.
McClean, Sally, Lalit Garg, Maria Barton, & Ken Fullerton. (2010). Using mixed phase-type distributions to model patient pathways. 23. 172–177. 8 indexed citations
11.
Lennon, Sheila, et al.. (2009). Gait specific training within Bobath therapy: a randomized controlled trial in acute stroke: a randomized controlled trial.. Cerebrovascular Diseases. 27. 240–241. 2 indexed citations
12.
Craig, David, Anthony Peter Passmore, Ken Fullerton, et al.. (2003). Factors influencing prescription of CNS medications in different elderly populations. Pharmacoepidemiology and Drug Safety. 12(5). 383–387. 26 indexed citations
13.
Donnelly, Michael, Mick Power, Mary E. Russell, & Ken Fullerton. (2003). Randomized Controlled Trial of an Early Discharge Rehabilitation Service. Stroke. 35(1). 127–133. 63 indexed citations
14.
Fullerton, Ken. (1999). The winter bed crisisquantifying seasonal effects on hospital bed usage. QJM. 92(4). 199–206. 45 indexed citations
15.
O’Neill, Paul, et al.. (1992). Fluid Balance in Elderly Patients following Acute Stroke. Age and Ageing. 21(4). 280–285. 23 indexed citations
16.
O'Neill, P A, I. Davies, Ken Fullerton, & Derrick Bennett. (1991). Stress hormone and blood glucose response following acute stroke in the elderly.. Stroke. 22(7). 842–847. 176 indexed citations
17.
Power, Martha, Ken Fullerton, & R. W. Stout. (1988). BLOOD GLUCOSE AND PROGNOSIS OF ACUTE STROKE. Age and Ageing. 17(3). 164–170. 28 indexed citations
18.
Fullerton, Ken, Gilbert MacKenzie, & R. W. Stout. (1988). Prognostic Indices in Stroke. QJM. 66(250). 147–62. 106 indexed citations
19.
Fullerton, Ken, David McSherry, & R. W. Stout. (1986). ALBERT'S TEST: A NEGLECTED TEST OF PERCEPTUAL NEGLECT. The Lancet. 327(8478). 430–432. 133 indexed citations
20.
McSherry, David & Ken Fullerton. (1985). Preceptor: a shell for medical expert systems and its application in a study of prognostic indices in stroke. Expert Systems. 2(3). 140–159. 4 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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