Matthew A. Levin

7.6k total citations · 1 hit paper
98 papers, 3.0k citations indexed

About

Matthew A. Levin is a scholar working on Cardiology and Cardiovascular Medicine, Surgery and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Matthew A. Levin has authored 98 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Cardiology and Cardiovascular Medicine, 27 papers in Surgery and 18 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Matthew A. Levin's work include Cardiac, Anesthesia and Surgical Outcomes (22 papers), COVID-19 Clinical Research Studies (16 papers) and Hemodynamic Monitoring and Therapy (13 papers). Matthew A. Levin is often cited by papers focused on Cardiac, Anesthesia and Surgical Outcomes (22 papers), COVID-19 Clinical Research Studies (16 papers) and Hemodynamic Monitoring and Therapy (13 papers). Matthew A. Levin collaborates with scholars based in United States, Israel and Germany. Matthew A. Levin's co-authors include David L. Reich, Hung‐Mo Lin, Benjamin S. Glicksberg, Robert Freeman, Girish N. Nadkarni, Patrick J. McCormick, Zahi A. Fayad, Anuradha Lala, Valentı́n Fuster and Alexander W. Charney and has published in prestigious journals such as Circulation, Annals of Internal Medicine and Journal of the American College of Cardiology.

In The Last Decade

Matthew A. Levin

92 papers receiving 2.9k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Association of Treatment Dose Anticoagulation With In-Hospital Survival Among Hospitalized Patients With COVID-19

2020 622 citations Ishan Paranjpe, Valentı́n Fuster et al. Journal of the American College of Cardiology profile →

Author Peers

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

Author						Papers	Cites
Matthew A. Levin	996	696	673	652	590	98	3.0k
Anuradha Lala	1.1k 1.1×	1.9k 2.8×	886 1.3×	580 0.9×	838 1.4×	131	4.0k
David Berlin	1.9k 1.9×	298 0.4×	630 0.9×	682 1.0×	929 1.6×	54	4.0k
Amer Harky	1.5k 1.5×	1.3k 1.9×	947 1.4×	1.2k 1.9×	968 1.6×	299	4.7k
Jennifer Haythe	915 0.9×	1.0k 1.5×	717 1.1×	182 0.3×	535 0.9×	38	2.4k
LeRoy E. Rabbani	2.0k 2.1×	558 0.8×	363 0.5×	479 0.7×	1.3k 2.2×	12	3.3k
Mahesh V. Madhavan	1.1k 1.1×	1.8k 2.5×	1.6k 2.3×	687 1.1×	603 1.0×	85	4.0k
Lise J Estcourt	880 0.9×	206 0.3×	461 0.7×	286 0.4×	374 0.6×	164	4.3k
Ankur Kalra	632 0.6×	1.8k 2.6×	1.1k 1.6×	508 0.8×	392 0.7×	254	3.6k
Gabriel Sayer	1.3k 1.3×	991 1.4×	969 1.4×	238 0.4×	738 1.3×	197	3.3k
Steffen Christensen	337 0.3×	766 1.1×	1.0k 1.5×	699 1.1×	284 0.5×	123	4.2k

Countries citing papers authored by Matthew A. Levin

Since Specialization

Citations

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

Fields of papers citing papers by Matthew A. Levin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew A. Levin. 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 Matthew A. Levin. The network helps show where Matthew A. Levin may publish in the future.

Co-authorship network of co-authors of Matthew A. Levin

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

All Works

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20 of 20 papers shown

Tandon, Pranai, Gary Oldenburg, Neha Dangayach, et al.. (2025). Impact of a Real-Time Ventilator Management Dashboard With Alerts. 3(4). 100167–100167.

Wang, Cindy, et al.. (2025). The Association Between Surgeon–Anesthesiologist Dyad Familiarity and Operative Mortality: A Retrospective Study at a Large Academic Cardiac Surgery Program. Anesthesia & Analgesia. 142(3). 561–569.

Patel, Dhavalkumar D., Benjamin S. Glicksberg, Matthew A. Levin, et al.. (2025). AI Agents in Modern Healthcare: From Foundation to Pioneer -- A Comprehensive Review and Implementation Roadmap for Impact and Integration in Clinical Settings. Preprints.org. 3 indexed citations

Patel, Dhavalkumar D., Prem Timsina, Benjamin S. Glicksberg, et al.. (2024). Traditional Machine Learning, Deep Learning, and BERT (Large Language Model) Approaches for Predicting Hospitalizations From Nurse Triage Notes: Comparative Evaluation of Resource Management. PubMed. 3. e52190–e52190. 5 indexed citations

Tandon, Pranai, David L. Reich, Robert Freeman, et al.. (2024). Development and Validation of a Deep Learning Classifier Using Chest Radiographs to Predict Extubation Success in Patients Undergoing Invasive Mechanical Ventilation. Bioengineering. 11(6). 626–626. 1 indexed citations

Scott, Erick R., Natalia Egorova, Robert Freeman, et al.. (2024). Assessing calibration and bias of a deployed machine learning malnutrition prediction model within a large healthcare system. npj Digital Medicine. 7(1). 149–149. 5 indexed citations

Vaid, Akhil, Mayte Suárez‐Fariñas, Sanjeev Kaul, et al.. (2023). Implications of the Use of Artificial Intelligence Predictive Models in Health Care Settings. Annals of Internal Medicine. 176(10). 1358–1369. 23 indexed citations

Tandon, Pranai, Prem Timsina, Robert Freeman, et al.. (2023). A Hybrid Decision Tree and Deep Learning Approach Combining Medical Imaging and Electronic Medical Records to Predict Intubation Among Hospitalized Patients With COVID-19: Algorithm Development and Validation. JMIR Formative Research. 7. e46905–e46905. 6 indexed citations

Alkalai, L., et al.. (2022). How businesses are working together to deliver NASA/JPL-designed ventilators to the world in the fight against COVID-19. Acta Astronautica. 201. 576–579. 1 indexed citations

10.

Paranjpe, Ishan, Kumardeep Chaudhary, Kipp W. Johnson, et al.. (2021). Association of SARS-CoV-2 viral load at admission with in-hospital acute kidney injury: A retrospective cohort study. PLoS ONE. 16(2). e0247366–e0247366. 6 indexed citations

11.

Klang, Eyal, Shelly Soffer, Eyal Zimlichman, et al.. (2021). Synergistic effect of hypoalbuminaemia and hypotension in predicting in-hospital mortality and intensive care admission: a retrospective cohort study. BMJ Open. 11(10). e050216–e050216. 3 indexed citations

12.

Levin, Matthew A., et al.. (2020). Differential Ventilation Using Flow Control Valves as a Potential Bridge to Full Ventilatory Support during the COVID-19 Crisis. Anesthesiology. 133(4). 892–904. 17 indexed citations

13.

Wenric, Stéphane, Janina M. Jeff, Thomas T. Joseph, et al.. (2020). Rapid response to the alpha-1 adrenergic agent phenylephrine in the perioperative period is impacted by genomics and ancestry. The Pharmacogenomics Journal. 21(2). 174–189. 1 indexed citations

14.

Cao, Davide, Rishi Chandiramani, Davide Capodanno, et al.. (2020). Non-cardiac surgery in patients with coronary artery disease: risk evaluation and periprocedural management. Nature Reviews Cardiology. 18(1). 37–57. 44 indexed citations

15.

Klang, Eyal, Gassan Kassim, Shelly Soffer, et al.. (2020). Severe Obesity as an Independent Risk Factor for COVID‐19 Mortality in Hospitalized Patients Younger than 50. Obesity. 28(9). 1595–1599. 218 indexed citations

16.

Paranjpe, Ishan, Valentı́n Fuster, Anuradha Lala, et al.. (2020). Association of Treatment Dose Anticoagulation With In-Hospital Survival Among Hospitalized Patients With COVID-19. Journal of the American College of Cardiology. 76(1). 122–124. 622 indexed citations breakdown →

17.

Levin, Matthew A., et al.. (2019). Association of Preoperative Frailty With Intraoperative Hemodynamic Instability and Postoperative Mortality. Anesthesia & Analgesia. 128(6). 1279–1285. 38 indexed citations

18.

Maheshwari, Ankit, Patrick J. McCormick, Daniel I. Sessler, et al.. (2017). Prolonged concurrent hypotension and low bispectral index (‘double low’) are associated with mortality, serious complications, and prolonged hospitalization after cardiac surgery. British Journal of Anaesthesia. 119(1). 40–49. 38 indexed citations

19.

Levin, Matthew A., Thomas T. Joseph, Janina M. Jeff, et al.. (2017). iGAS: A framework for using electronic intraoperative medical records for genomic discovery. Journal of Biomedical Informatics. 67. 80–89. 6 indexed citations

20.

McCormick, Patrick J., Matthew A. Levin, Hung-Mo Lin, Daniel I. Sessler, & David L. Reich. (2016). Effectiveness of an Electronic Alert for Hypotension and Low Bispectral Index on 90-day Postoperative Mortality. Anesthesiology. 125(6). 1113–1120. 22 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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