David Lyell

740 total citations
21 papers, 444 citations indexed

About

David Lyell is a scholar working on Health Information Management, Health Informatics and Surgery. According to data from OpenAlex, David Lyell has authored 21 papers receiving a total of 444 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Health Information Management, 9 papers in Health Informatics and 5 papers in Surgery. Recurrent topics in David Lyell's work include Electronic Health Records Systems (10 papers), Artificial Intelligence in Healthcare and Education (9 papers) and Healthcare Technology and Patient Monitoring (5 papers). David Lyell is often cited by papers focused on Electronic Health Records Systems (10 papers), Artificial Intelligence in Healthcare and Education (9 papers) and Healthcare Technology and Patient Monitoring (5 papers). David Lyell collaborates with scholars based in Australia, Indonesia and Sri Lanka. David Lyell's co-authors include Enrico Coiera, Farah Magrabi, Parina Shah, Jessica Chen, Lisa Pont, Magdalena Z. Raban, Ying Wang, Melissa Baysari, Richard O. Day and Shlomo Berkovsky and has published in prestigious journals such as Journal of Medical Internet Research, Journal of the American Medical Informatics Association and Human Factors The Journal of the Human Factors and Ergonomics Society.

In The Last Decade

David Lyell

16 papers receiving 436 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Lyell Australia 8 196 108 84 63 63 21 444
Arun Vijay Subbarayalu Saudi Arabia 10 197 1.0× 83 0.8× 58 0.7× 72 1.1× 96 1.5× 63 611
Raffaele Rasoini Italy 5 249 1.3× 221 2.0× 96 1.1× 89 1.4× 162 2.6× 8 715
Tom Lawton United Kingdom 10 148 0.8× 142 1.3× 33 0.4× 59 0.9× 56 0.9× 39 486
Jenny Krutzinna Norway 8 125 0.6× 126 1.2× 32 0.4× 60 1.0× 59 0.9× 22 461
Fred Hersch Australia 10 132 0.7× 143 1.3× 54 0.6× 81 1.3× 158 2.5× 16 562
Andrew E. Krumm United States 10 207 1.1× 197 1.8× 59 0.7× 140 2.2× 88 1.4× 55 787
Laura Vardoulakis United States 7 157 0.8× 211 2.0× 53 0.6× 36 0.6× 122 1.9× 10 515
Piyush Mathur United States 8 254 1.3× 129 1.2× 59 0.7× 77 1.2× 78 1.2× 32 533
Ahmed Al Kuwaiti Saudi Arabia 10 197 1.0× 86 0.8× 60 0.7× 74 1.2× 92 1.5× 31 562
Jesutofunmi A. Omiye United States 10 226 1.2× 185 1.7× 57 0.7× 70 1.1× 118 1.9× 17 598

Countries citing papers authored by David Lyell

Since Specialization
Citations

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

Fields of papers citing papers by David Lyell

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Lyell

This figure shows the co-authorship network connecting the top 25 collaborators of David Lyell. A scholar is included among the top collaborators of David Lyell 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 Lyell. David Lyell 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.
Lyell, David, Michael Dinh, Mark Gillett, et al.. (2025). Evaluating the impact of AI assistance on decision-making in emergency doctors interpreting chest X-rays: a multi-reader multi-case study. Emergency Medicine Journal. 42(12). 774–782.
2.
Lyell, David, et al.. (2025). Role of AI in Clinical Decision-Making: An Analysis of FDA Medical Device Approvals. Studies in health technology and informatics. 329. 1019–1023.
3.
Lyell, David, et al.. (2024). Using Clinical Simulation to Evaluate AI-Enabled Decision Support. Studies in health technology and informatics. 310. 299–303. 1 indexed citations
4.
Lyell, David, et al.. (2024). How Well Do AI-Enabled Decision Support Systems Perform in Clinical Settings?. Studies in health technology and informatics. 310. 279–283. 1 indexed citations
5.
Wang, Ying, David Lyell, Enrico Coiera, & Farah Magrabi. (2024). Automating the Identification of Safety Events Involving Machine Learning-Enabled Medical Devices. Studies in health technology and informatics. 310. 604–608.
6.
Lyell, David & Farah Magrabi. (2023). Artificial intelligence in medicine: has the time come to hang up the stethoscope?. Internal Medicine Journal. 53(9). 1533–1539.
7.
Magrabi, Farah, David Lyell, & Enrico Coiera. (2023). Automation in Contemporary Clinical Information Systems: a Survey of AI in Healthcare Settings. Yearbook of Medical Informatics. 32(1). 115–126. 7 indexed citations
8.
Lyell, David, et al.. (2023). Effects of machine learning-based clinical decision support systems on decision-making, care delivery, and patient outcomes: a scoping review. Journal of the American Medical Informatics Association. 30(12). 2050–2063. 20 indexed citations
9.
Lyell, David, et al.. (2022). Emergency department and urgent care clinician perspectives on digital access to past medical histories. BMJ Health & Care Informatics. 29(1). e100567–e100567. 2 indexed citations
10.
Lyell, David, et al.. (2021). How Well Do Computerised Decision Support Systems Cover Nursing Standards of Practice? A Literature Review. Studies in health technology and informatics. 284. 269–274.
11.
Lyell, David, et al.. (2021). Automation in nursing decision support systems: A systematic review of effects on decision making, care delivery, and patient outcomes. Journal of the American Medical Informatics Association. 28(11). 2502–2513. 29 indexed citations
12.
Lyell, David, Enrico Coiera, Jessica Chen, Parina Shah, & Farah Magrabi. (2021). How machine learning is embedded to support clinician decision making: an analysis of FDA-approved medical devices. BMJ Health & Care Informatics. 28(1). e100301–e100301. 51 indexed citations
13.
Lyell, David, et al.. (2020). Effect of Speech Recognition on Problem Solving and Recall in Consumer Digital Health Tasks: Controlled Laboratory Experiment. Journal of Medical Internet Research. 22(6). e14827–e14827. 7 indexed citations
14.
Lyell, David, et al.. (2020). Emergency care access to primary care records: an observational study. BMJ Health & Care Informatics. 27(3). e100153–e100153. 3 indexed citations
15.
Lyell, David, Farah Magrabi, & Enrico Coiera. (2019). Reduced Verification of Medication Alerts Increases Prescribing Errors. Applied Clinical Informatics. 10(1). 66–76. 14 indexed citations
16.
Lyell, David, Farah Magrabi, & Enrico Coiera. (2018). The Effect of Cognitive Load and Task Complexity on Automation Bias in Electronic Prescribing. Human Factors The Journal of the Human Factors and Ergonomics Society. 60(7). 1008–1021. 44 indexed citations
17.
Lyell, David, Farah Magrabi, Magdalena Z. Raban, et al.. (2017). Automation bias in electronic prescribing. BMC Medical Informatics and Decision Making. 17(1). 28–28. 54 indexed citations
18.
Lyell, David & Enrico Coiera. (2016). Automation bias and verification complexity: a systematic review. Journal of the American Medical Informatics Association. 24(2). 423–431. 171 indexed citations
19.
Lyell, David & Geoff McDonnell. (2007). A dynamic balanced scorecard for managing health systems performance. 5 indexed citations
20.
Lyell, David, et al.. (2006). Defence capability management: introduction into service of multi-role helicopters. 5 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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