David J. Lowe

4.3k total citations · 2 hit papers
101 papers, 2.5k citations indexed

About

David J. Lowe is a scholar working on Molecular Biology, Emergency Medicine and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, David J. Lowe has authored 101 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 22 papers in Emergency Medicine and 16 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in David J. Lowe's work include Emergency and Acute Care Studies (16 papers), Porphyrin Metabolism and Disorders (11 papers) and Gout, Hyperuricemia, Uric Acid (8 papers). David J. Lowe is often cited by papers focused on Emergency and Acute Care Studies (16 papers), Porphyrin Metabolism and Disorders (11 papers) and Gout, Hyperuricemia, Uric Acid (8 papers). David J. Lowe collaborates with scholars based in United Kingdom, United States and Ireland. David J. Lowe's co-authors include Robert C. Bray, R. N. F. Thorneley, Francisco Garcı́a-Cánovas, Alexander N. P. Hiner, José Neptuno Rodrı́guez-López, Josefa Hernández‐Ruíz, B. E. Smith, E.M. Fielden, Peter Roberts and Michael Barber and has published in prestigious journals such as Journal of the American Chemical Society, Journal of Biological Chemistry and Circulation.

In The Last Decade

David J. Lowe

98 papers receiving 2.4k citations

Hit Papers

Outcomes among confirmed cases and a matched comparison g... 2022 2026 2023 2024 2022 2023 40 80 120

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David J. Lowe United Kingdom 26 847 486 444 236 218 101 2.5k
Yutang Wang China 35 941 1.1× 410 0.8× 63 0.1× 90 0.4× 102 0.5× 189 4.6k
Mohamed Abdel‐Rehim Sweden 45 743 0.9× 84 0.2× 138 0.3× 41 0.2× 47 0.2× 153 6.5k
Massimiliano Peana Italy 38 1.5k 1.8× 97 0.2× 354 0.8× 160 0.7× 231 1.1× 127 6.2k
Elizabeth N. Bess United States 16 1.2k 1.4× 47 0.1× 350 0.8× 163 0.7× 197 0.9× 24 2.5k
Lulu Zhang China 31 1.2k 1.4× 369 0.8× 40 0.1× 32 0.1× 93 0.4× 203 3.4k
Dongyang Liu China 24 690 0.8× 72 0.1× 141 0.3× 555 2.4× 1.5k 6.8× 183 3.9k
W. A. PRYOR United States 23 2.0k 2.3× 91 0.2× 515 1.2× 76 0.3× 42 0.2× 49 6.5k
Yingying Ma China 28 494 0.6× 101 0.2× 135 0.3× 21 0.1× 79 0.4× 92 2.5k
Linda M. Benson United States 33 1.1k 1.3× 60 0.1× 85 0.2× 47 0.2× 110 0.5× 98 2.9k
Hassan A. Alhazmi Saudi Arabia 31 1.1k 1.3× 93 0.2× 43 0.1× 47 0.2× 108 0.5× 176 3.4k

Countries citing papers authored by David J. Lowe

Since Specialization
Citations

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

Fields of papers citing papers by David J. Lowe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David J. Lowe. 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 David J. Lowe. The network helps show where David J. Lowe may publish in the future.

Co-authorship network of co-authors of David J. Lowe

This figure shows the co-authorship network connecting the top 25 collaborators of David J. Lowe. A scholar is included among the top collaborators of David J. Lowe 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 David J. Lowe. David J. Lowe 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.
Thomson, RM, et al.. (2025). Evaluating the environmental sustainability of AI in radiology: a systematic review of current practice. CLOK (University of Central Lancashire). 1(1). e000073–e000073.
2.
Ho, Antonia, Andrew Blunsum, Michael E. Murphy, et al.. (2024). Near real-time severe acute respiratory illness surveillance characterising influenza and COVID-19 epidemiology in hospitalised adults, 2021-22. Journal of Infection. 89(6). 106338–106338.
3.
Vimalesvaran, Kavitha, Mark Harrison, Sarim Ather, et al.. (2024). Assessing the effectiveness of artificial intelligence (AI) in prioritising CT head interpretation: study protocol for a stepped-wedge cluster randomised trial (ACCEPT-AI). BMJ Open. 14(6). e078227–e078227. 1 indexed citations
5.
Lowe, David J., et al.. (2024). Views of emergency care providers in providing healthcare for asylum seekers and refugees. Emergency Medicine Journal. 41(10). 578–584.
6.
Lee, Kuan Ken, David J. Lowe, Rachel O’Brien, et al.. (2023). Troponin in acute chest pain to risk stratify and guide effective use of computed tomography coronary angiography (TARGET-CTCA): a randomised controlled trial. Trials. 24(1). 402–402. 3 indexed citations
7.
Hastie, Claire E., David J. Lowe, Andrew McAuley, et al.. (2023). True prevalence of long-COVID in a nationwide, population cohort study. Nature Communications. 14(1). 7892–7892. 80 indexed citations breakdown →
8.
Anderson, Jacqueline, et al.. (2023). Long-Term Usage and Improved Clinical Outcomes with Adoption of a COPD Digital Support Service: Key Findings from the RECEIVER Trial. International Journal of COPD. Volume 18. 1301–1318. 1 indexed citations
9.
Drozdov, Ignat, et al.. (2023). An Artificial Neural Network for Nasogastric Tube Position Decision Support. Radiology Artificial Intelligence. 5(2). e220165–e220165. 9 indexed citations
10.
Wereski, Ryan, Philip D Adamson, Caelan Taggart, et al.. (2023). High-Sensitivity Cardiac Troponin for Risk Assessment in Patients With Chronic Coronary Artery Disease. Journal of the American College of Cardiology. 82(6). 473–485. 8 indexed citations
11.
Woodfield, Julie, Ellie Edlmann, Polly Black, et al.. (2022). Duration of External Neck Stabilisation (DENS) following odontoid fracture in older or frail adults: protocol for a randomised controlled trial of collar versus no collar. BMJ Open. 12(7). e057753–e057753. 6 indexed citations
12.
Hastie, Claire E., David J. Lowe, Andrew McAuley, et al.. (2022). Outcomes among confirmed cases and a matched comparison group in the Long-COVID in Scotland study. Nature Communications. 13(1). 5663–5663. 126 indexed citations breakdown →
14.
Hornsby, James, et al.. (2021). Assistive technologies for home NIV in patients with COPD: feasibility and positive experience with remote-monitoring and volume-assured auto-EPAP NIV mode. BMJ Open Respiratory Research. 8(1). e000828–e000828. 5 indexed citations
15.
Wereski, Ryan, Dorien M. Kimenai, Anda Bularga, et al.. (2021). Risk factors for type 1 and type 2 myocardial infarction. European Heart Journal. 43(2). 127–135. 50 indexed citations
16.
Drozdov, Ignat, et al.. (2021). Development and prospective validation of COVID-19 chest X-ray screening model for patients attending emergency departments. Scientific Reports. 11(1). 20384–20384. 7 indexed citations
17.
Wereski, Ryan, Stephen W. Smith, Andrew R. Chapman, et al.. (2020). 21 High-sensitivity cardiac troponin concentrations at presentation in patients with st-segment elevation myocardial infarction. A15–A16. 1 indexed citations
18.
Robson, Simon C., et al.. (2020). Identifying opportunities for health promotion and intervention in the ED. Emergency Medicine Journal. 38(12). 927–932. 6 indexed citations
19.
Cameron, Allan, et al.. (2018). Comparison of Glasgow Admission Prediction Score and Amb Score in predicting need for inpatient care. Emergency Medicine Journal. 35(4). 247–251. 13 indexed citations
20.
Lowe, David J., et al.. (2016). Exploring situational awareness in emergency medicine: developing a shared mental model to enhance training and assessment. Postgraduate Medical Journal. 92(1093). 653–658. 38 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

Rankless by CCL
2026