David M. Greer

17.1k total citations · 4 hit papers
242 papers, 7.9k citations indexed

About

David M. Greer is a scholar working on Neurology, Epidemiology and Emergency Medicine. According to data from OpenAlex, David M. Greer has authored 242 papers receiving a total of 7.9k indexed citations (citations by other indexed papers that have themselves been cited), including 96 papers in Neurology, 79 papers in Epidemiology and 64 papers in Emergency Medicine. Recurrent topics in David M. Greer's work include Traumatic Brain Injury and Neurovascular Disturbances (68 papers), Cardiac Arrest and Resuscitation (64 papers) and Organ Donation and Transplantation (58 papers). David M. Greer is often cited by papers focused on Traumatic Brain Injury and Neurovascular Disturbances (68 papers), Cardiac Arrest and Resuscitation (64 papers) and Organ Donation and Transplantation (58 papers). David M. Greer collaborates with scholars based in United States, Canada and Brazil. David M. Greer's co-authors include Brian L. Edlow, Karen L. Furie, Katharina M. Busl, Ona Wu, Ariane Lewis, Aneesh B. Singhal, Nicholas D. Schiff, Jan Claassen, Eelco F. M. Wijdicks and Walter J. Koroshetz and has published in prestigious journals such as New England Journal of Medicine, Circulation and Journal of Clinical Investigation.

In The Last Decade

David M. Greer

225 papers receiving 7.6k citations

Hit Papers

Recovery from disorders o... 2014 2026 2018 2022 2020 2014 2019 2023 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
David M. Greer 3.0k 2.9k 2.3k 1.4k 1.1k 242 7.9k
Jeffrey V. Rosenfeld 3.9k 1.3× 4.5k 1.5× 3.1k 1.4× 785 0.6× 471 0.4× 242 10.7k
Stephen Ashwal 4.0k 1.3× 4.1k 1.4× 2.2k 1.0× 1.2k 0.9× 1.3k 1.2× 235 13.1k
Michael J. Bell 3.0k 1.0× 5.0k 1.7× 3.0k 1.3× 356 0.3× 782 0.7× 237 9.3k
Rebekah Mannix 4.3k 1.4× 2.8k 0.9× 3.1k 1.4× 1.2k 0.9× 444 0.4× 218 7.6k
Jay Mandrekar 1.4k 0.5× 3.8k 1.3× 899 0.4× 457 0.3× 1.2k 1.1× 229 9.5k
Derek A. Bruce 2.1k 0.7× 3.3k 1.1× 1.5k 0.7× 703 0.5× 757 0.7× 148 7.9k
Steven Galetta 3.0k 1.0× 6.4k 2.2× 672 0.3× 934 0.7× 566 0.5× 451 14.1k
B. Jennett 5.8k 2.0× 9.4k 3.2× 5.2k 2.3× 888 0.7× 950 0.9× 103 13.4k
Louis Puybasset 1.5k 0.5× 1.8k 0.6× 1.5k 0.6× 260 0.2× 2.5k 2.4× 179 6.4k
Fenella J. Kirkham 2.6k 0.9× 2.8k 0.9× 365 0.2× 802 0.6× 1.4k 1.3× 324 12.7k

Countries citing papers authored by David M. Greer

Since Specialization
Citations

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

Fields of papers citing papers by David M. Greer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David M. Greer

This figure shows the co-authorship network connecting the top 25 collaborators of David M. Greer. A scholar is included among the top collaborators of David M. Greer 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 M. Greer. David M. Greer 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.
Cervantes‐Arslanian, Anna M., Emelia J. Benjamin, Emily J. Gilmore, et al.. (2025). Quantitative Pupillometry Predicts Neurologic Deterioration in Patients with Large Middle Cerebral Artery Stroke. Annals of Neurology. 97(5). 930–941.
2.
Lewis, Ariane, James A. Russell, Richard J. Bonnie, et al.. (2025). Brain Death/Death by Neurologic Criteria Guidance on Communication, Objections, Pregnancy, and Public Trust. Neurology. 105(10). e214334–e214334.
3.
Lau, Helena, Anna M. Cervantes‐Arslanian, Thanh N. Nguyen, et al.. (2025). Illicit drug use and cerebral microbleeds in patients with acute ischemic stroke and transient ischemic attack. International Journal of Stroke. 20(7). 874–882.
4.
Ong, Charlene, Yihan Zhang, Emelia J. Benjamin, et al.. (2024). Association of Dynamic Trajectories of Time-Series Data and Life-Threatening Mass Effect in Large Middle Cerebral Artery Stroke. Neurocritical Care. 42(1). 77–89. 2 indexed citations
5.
Sarhadi, Kasra, Natalie Smith, Michael J. Souter, et al.. (2024). Verification of Death by Neurologic Criteria: A Survey of 12 Organ Procurement Organizations Across the United States. Neurocritical Care. 41(3). 847–854. 4 indexed citations
7.
Zhang, Yihan, Asim Mian, Mohamad Abdalkader, et al.. (2023). Follow-up ASPECTS improves prediction of potentially lethal malignant edema in patients with large middle cerebral artery stroke. Journal of NeuroInterventional Surgery. 17(e1). e83–e86. 7 indexed citations
8.
Silva, Ivan Da, William Roth, Terry Selfe, et al.. (2023). Do Neuroprognostic Studies Account for Self-Fulfilling Prophecy Bias in Their Methodology? The SPIN Protocol for a Systematic Review. Critical Care Explorations. 5(7). e0943–e0943. 5 indexed citations
9.
Greer, David M., Matthew P. Kirschen, Ariane Lewis, et al.. (2023). Pediatric and Adult Brain Death/Death by Neurologic Criteria Consensus Guideline. Neurology. 101(24). 1112–1132. 59 indexed citations breakdown →
10.
Francoeur, Conall, Matthew J. Weiss, Jennifer MacDonald, et al.. (2021). Variability in Pediatric Brain Death Determination Protocols in the United States. Neurology. 97(3). e310–e319. 14 indexed citations
11.
Kirschen, Matthew P., Conall Francoeur, Matthew J. Weiss, et al.. (2021). Variability in Pediatric Brain Death Protocols in the United States (1173). Neurology. 96(15_supplement). 1 indexed citations
12.
Anand, Pria, Lan Zhou, Nahid Bhadelia, et al.. (2021). Neurologic Findings Among Inpatients with COVID-19 at a Safety-Net U.S. Hospital (1149). Neurology. 96(15_supplement). 1 indexed citations
13.
Shulman, Julie, Hernán Jara, Muhammad M. Qureshi, et al.. (2020). Perihematomal edema surrounding spontaneous intracerebral hemorrhage by CT. Medicine. 99(28). e20951–e20951. 6 indexed citations
14.
Hutch, Meghan R., et al.. (2020). Quantitative Pupillometry and Intracranial Pressure in Neuro ICU Patients (3967). Neurology. 94(15_supplement). 1 indexed citations
15.
Gaieski, David F., Tetsuya Sakamoto, David M. Greer, & David F. Gaieski. (2014). Perspectives on Temperature Management. Therapeutic Hypothermia and Temperature Management. 4(4). 150–153. 1 indexed citations
16.
Greer, David M., Jingyun Yang, Patricia D. Scripko, et al.. (2011). Clinical examination for outcome prediction in nontraumatic coma*. Critical Care Medicine. 40(4). 1150–1156. 26 indexed citations
17.
Maas, Matthew B., Karen L. Furie, Michael H. Lev, et al.. (2009). National Institutes of Health Stroke Scale Score Is Poorly Predictive of Proximal Occlusion in Acute Cerebral Ischemia. Stroke. 40(9). 2988–2993. 113 indexed citations
18.
Greer, David M., et al.. (2008). Impact of Fever on Outcome in Patients With Stroke and Neurologic Injury. Stroke. 39(11). 3029–3035. 274 indexed citations
19.
Greer, David M.. (2007). Acute ischemic stroke : an evidence-based approach.

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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