Mark Mai

895 total citations
22 papers, 556 citations indexed

About

Mark Mai is a scholar working on Pulmonary and Respiratory Medicine, Epidemiology and Emergency Medicine. According to data from OpenAlex, Mark Mai has authored 22 papers receiving a total of 556 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Pulmonary and Respiratory Medicine, 5 papers in Epidemiology and 5 papers in Emergency Medicine. Recurrent topics in Mark Mai's work include Respiratory Support and Mechanisms (5 papers), Emergency and Acute Care Studies (4 papers) and Neonatal Respiratory Health Research (4 papers). Mark Mai is often cited by papers focused on Respiratory Support and Mechanisms (5 papers), Emergency and Acute Care Studies (4 papers) and Neonatal Respiratory Health Research (4 papers). Mark Mai collaborates with scholars based in United States, Netherlands and India. Mark Mai's co-authors include Nandini Gokulchandran, Karla E. Hirokawa, Ben Martynoga, Ashwin S. Shetty, Lakshmi Subramanian, Lisa A. Flanagan, Shubha Tole, Yuqing Li, Edwin S. Monuki and P. R. V. Satyaki and has published in prestigious journals such as Science, Journal of Clinical Investigation and Philosophical Transactions of the Royal Society B Biological Sciences.

In The Last Decade

Mark Mai

17 papers receiving 543 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark Mai United States 10 215 118 97 64 63 22 556
Andrew E. Fry United Kingdom 18 361 1.7× 315 2.7× 48 0.5× 69 1.1× 70 1.1× 37 956
Carmela Fusco Italy 19 454 2.1× 192 1.6× 168 1.7× 64 1.0× 87 1.4× 53 1.0k
Jenny Ruiz United States 9 360 1.7× 178 1.5× 13 0.1× 33 0.5× 16 0.3× 30 556
Rachel Dickinson United Kingdom 11 236 1.1× 107 0.9× 18 0.2× 113 1.8× 88 1.4× 16 622
Tim Morgan New Zealand 17 323 1.5× 208 1.8× 15 0.2× 23 0.4× 9 0.1× 44 782
Gilles Gasparoni Germany 19 766 3.6× 180 1.5× 28 0.3× 53 0.8× 21 0.3× 46 1.3k
Eberhard Buse Germany 16 223 1.0× 62 0.5× 28 0.3× 116 1.8× 10 0.2× 50 727
Jasmine Plummer United States 14 381 1.8× 99 0.8× 22 0.2× 42 0.7× 4 0.1× 25 918
Rüdiger Lessig Germany 13 316 1.5× 440 3.7× 16 0.2× 24 0.4× 22 0.3× 28 935
Jennifer Yen United States 13 396 1.8× 144 1.2× 15 0.2× 27 0.4× 30 0.5× 34 996

Countries citing papers authored by Mark Mai

Since Specialization
Citations

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

Fields of papers citing papers by Mark Mai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Mai

This figure shows the co-authorship network connecting the top 25 collaborators of Mark Mai. A scholar is included among the top collaborators of Mark Mai 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 Mark Mai. Mark Mai 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.
2.
Orenstein, Evan, Naveen Muthu, Nikolay Braykov, et al.. (2025). Early clinical evaluation of a vendor developed pediatric artificial intelligence sepsis model in the emergency department. Journal of the American Medical Informatics Association. 32(10). 1542–1551.
3.
Dziorny, Adam, Allison B. McCoy, Evan Orenstein, et al.. (2025). Pediatric Predictive Artificial Intelligence Implemented in Clinical Practice from 2010 to 2021: A Systematic Review. Applied Clinical Informatics. 16(3). 477–487. 2 indexed citations
4.
Muthu, Naveen, et al.. (2025). Human performance evaluation of a pediatric artificial intelligence sepsis model. Journal of the American Medical Informatics Association. 32(10). 1552–1561. 1 indexed citations
5.
Yehya, Nadir, Thomas J. Booth, Jill Thompson, et al.. (2024). Inflammatory and tissue injury marker dynamics in pediatric acute respiratory distress syndrome. Journal of Clinical Investigation. 134(10). 11 indexed citations
6.
7.
Grunwell, Jocelyn R., Alireza Rafiei, Prakadeshwari Rajapreyar, et al.. (2023). Development and Validation of a Model for Endotracheal Intubation and Mechanical Ventilation Prediction in PICU Patients*. Pediatric Critical Care Medicine. 25(3). 212–221. 5 indexed citations
8.
Percy, Andrew, Mark Mai, Anoopindar Bhalla, & Nadir Yehya. (2023). Mechanical Power Is Associated With Mortality in Pediatric Acute Respiratory Distress Syndrome. Pediatric Critical Care Medicine. 24(7). e307–e316. 8 indexed citations
9.
Mai, Mark, et al.. (2022). Measuring Training Disruptions Using an Informatics Based Tool. Academic Pediatrics. 23(1). 7–11. 1 indexed citations
10.
Rasooly, Irit R., et al.. (2022). Characteristics of Emergency Room and Hospital Encounters Resulting From Consumer Home Monitors. Hospital Pediatrics. 12(7). e239–e244. 2 indexed citations
11.
Yehya, Nadir, Hossein Fazelinia, Gladys G. Lawrence, et al.. (2021). Plasma Nucleosomes Are Associated With Mortality in Pediatric Acute Respiratory Distress Syndrome. Critical Care Medicine. 49(7). 1149–1158. 13 indexed citations
12.
Morrison, Wynne, et al.. (2020). Apnea Testing Using Continuous Positive Airway Pressure When Determining Death by Neurologic Criteria in Children: Retrospective Analysis of Potential Adverse Events*. Pediatric Critical Care Medicine. 21(12). e1152–e1156. 12 indexed citations
13.
Mai, Mark, et al.. (2020). 102. HACKING OUR WAY TO IMPROVEMENT: LEVERAGING THE HEALTHCARE HACKATHON TO ENGAGE HOUSESTAFF IN QI. Academic Pediatrics. 20(7). e48–e49.
14.
Bonafide, Christopher P., Jeffrey M. Miller, A. Russell Localio, et al.. (2019). Association Between Mobile Telephone Interruptions and Medication Administration Errors in a Pediatric Intensive Care Unit. JAMA Pediatrics. 174(2). 162–162. 17 indexed citations
15.
Mai, Mark, et al.. (2018). A Model for Clinical Informatics Education for Residents: Addressing an Unmet Need. Applied Clinical Informatics. 9(2). 261–267. 11 indexed citations
16.
Orenstein, Evan, Irit R. Rasooly, Mark Mai, et al.. (2018). Influence of simulation on electronic health record use patterns among pediatric residents. Journal of the American Medical Informatics Association. 25(11). 1501–1506. 17 indexed citations
17.
Mai, Mark & Michael Krauthammer. (2016). Controlling testing volume for respiratory viruses using machine learning and text mining.. PubMed. 2016. 1910–1919. 9 indexed citations
18.
Gilbert, Scott F., et al.. (2010). Symbiosis as a source of selectable epigenetic variation: taking the heat for the big guy. Philosophical Transactions of the Royal Society B Biological Sciences. 365(1540). 671–678. 100 indexed citations
19.
Hirokawa, Karla E., P. R. V. Satyaki, Nandini Gokulchandran, et al.. (2008). Lhx2 Selector Activity Specifies Cortical Identity and Suppresses Hippocampal Organizer Fate. Science. 319(5861). 304–309. 239 indexed citations
20.
Bennett, Charles L., Andrew M. Evens, Leslie A. Andritsos, et al.. (2006). Haematological malignancies developing in previously healthy individuals who received haematopoietic growth factors: report from the Research on Adverse Drug Events and Reports (RADAR) project. British Journal of Haematology. 135(5). 642–650. 93 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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