Daniel Burns

530 total citations
18 papers, 203 citations indexed

About

Daniel Burns is a scholar working on Artificial Intelligence, Epidemiology and Infectious Diseases. According to data from OpenAlex, Daniel Burns has authored 18 papers receiving a total of 203 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 4 papers in Epidemiology and 3 papers in Infectious Diseases. Recurrent topics in Daniel Burns's work include Machine Learning in Healthcare (4 papers), COVID-19 Clinical Research Studies (3 papers) and Immune Cell Function and Interaction (3 papers). Daniel Burns is often cited by papers focused on Machine Learning in Healthcare (4 papers), COVID-19 Clinical Research Studies (3 papers) and Immune Cell Function and Interaction (3 papers). Daniel Burns collaborates with scholars based in United Kingdom, United States and Australia. Daniel Burns's co-authors include Apostolos Pilaftsis, Michael Boniface, Francis Chmiel, N.M. White, Christopher Duckworth, Zlatko Zlatev, T. Daniels, Salah Mansour, Ivo Tews and Ali Roghanian and has published in prestigious journals such as PLoS ONE, Scientific Reports and Nuclear Physics B.

In The Last Decade

Daniel Burns

15 papers receiving 199 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Burns United Kingdom 8 58 44 37 33 24 18 203
Phillip B. Warner United States 11 38 0.7× 110 2.5× 19 0.5× 19 0.6× 11 0.5× 28 336
Christopher Duckworth United Kingdom 9 50 0.9× 127 2.9× 15 0.4× 35 1.1× 6 0.3× 13 252
B. Mellado South Africa 13 43 0.7× 49 1.1× 382 10.3× 23 0.7× 9 0.4× 74 522
Niki Kilbertus Germany 7 102 1.8× 85 1.9× 6 0.2× 10 0.3× 4 0.2× 14 260
R. Gupta United States 9 45 0.8× 132 3.0× 64 1.7× 53 1.6× 3 0.1× 22 321
Christopher Bishop United Kingdom 7 34 0.6× 8 0.2× 23 0.6× 16 0.5× 3 0.1× 16 433
C. Campagnari United States 8 58 1.0× 8 0.2× 111 3.0× 24 0.7× 3 0.1× 16 295
Sergey Morozov Netherlands 6 79 1.4× 10 0.2× 22 0.6× 186 5.6× 10 0.4× 10 282
Zhusong Mei China 12 35 0.6× 3 0.1× 77 2.1× 2 0.1× 8 0.3× 22 298
George Napolitano Denmark 11 49 0.8× 27 0.6× 4 0.1× 6 0.2× 78 3.3× 43 285

Countries citing papers authored by Daniel Burns

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Burns

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Burns

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

All Works

18 of 18 papers shown
1.
Duckworth, Christopher, et al.. (2025). Predicting onward care needs at admission to reduce discharge delay using explainable machine learning. Scientific Reports. 15(1). 16033–16033. 1 indexed citations
2.
Blunt, Matthew D., Ralf B. Schittenhelm, Sajida Khan, et al.. (2024). The nuclear export protein XPO1 provides a peptide ligand for natural killer cells. Science Advances. 10(34). eado6566–eado6566. 2 indexed citations
3.
4.
Inada-Kim, Matthew, Francis Chmiel, Michael Boniface, et al.. (2024). Validation of oxygen saturations measured in the community by emergency medical services as a marker of clinical deterioration in patients with confirmed COVID-19: a retrospective cohort study. BMJ Open. 14(1). e067378–e067378. 5 indexed citations
5.
Burns, Daniel, et al.. (2023). Towards a better understanding of human iNKT cell subpopulations for improved clinical outcomes. Frontiers in Immunology. 14. 1176724–1176724. 23 indexed citations
6.
Roy, Ashok, et al.. (2023). Pilot study to evaluate hypercoagulation and inflammation using rotational thromboelastometry and calprotectin in COVID-19 patients. PLoS ONE. 18(1). e0269738–e0269738. 2 indexed citations
7.
Birch, J.R., Shirley A. Ellis, Daniel Burns, et al.. (2023). Cattle killer immunoglobulin-like receptor expression on leukocyte subsets suggests functional divergence compared to humans. Veterinary Immunology and Immunopathology. 263. 110646–110646. 1 indexed citations
8.
Ryan, Hannah, et al.. (2023). Antibiotic treatment to reduce the duration and severity of travellers’ diarrhoea. Cochrane Database of Systematic Reviews. 2023(11).
9.
Boniface, Michael, et al.. (2022). COVID-19 Oximetry @home: evaluation of patient outcomes. BMJ Open Quality. 11(1). e001584–e001584. 11 indexed citations
10.
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12.
Duckworth, Christopher, Francis Chmiel, Daniel Burns, et al.. (2021). Using explainable machine learning to characterise data drift and detect emergent health risks for emergency department admissions during COVID-19. Scientific Reports. 11(1). 23017–23017. 59 indexed citations
13.
Chmiel, Francis, Daniel Burns, Florina Borca, et al.. (2021). Using explainable machine learning to identify patients at risk of reattendance at discharge from emergency departments. Scientific Reports. 11(1). 21513–21513. 15 indexed citations
14.
Grace, Paul, et al.. (2019). Pseudonymization risk analysis in distributed systems. Journal of Internet Services and Applications. 10(1). 15 indexed citations
15.
Grace, Paul, et al.. (2018). Identifying Privacy Risks in Distributed Data Services: A Model-Driven Approach. ePrints Soton (University of Southampton). 41. 1513–1518. 2 indexed citations
16.
Burns, Daniel, et al.. (2016). Frame-covariant formulation of inflation in scalar-curvature theories. Nuclear Physics B. 907. 785–819. 36 indexed citations
17.
Burns, Daniel & Apostolos Pilaftsis. (2015). Matter quantum corrections to the graviton self-energy and the Newtonian potential. Physical review. D. Particles, fields, gravitation, and cosmology. 91(6). 12 indexed citations
18.
Burns, Daniel, et al.. (1991). Variable Hold Time in Dynamic Random Access Memories. Defense Technical Information Center (DTIC).

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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