Michael G. Risbano

854 total citations
35 papers, 498 citations indexed

About

Michael G. Risbano is a scholar working on Pulmonary and Respiratory Medicine, Cardiology and Cardiovascular Medicine and Molecular Biology. According to data from OpenAlex, Michael G. Risbano has authored 35 papers receiving a total of 498 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Pulmonary and Respiratory Medicine, 15 papers in Cardiology and Cardiovascular Medicine and 6 papers in Molecular Biology. Recurrent topics in Michael G. Risbano's work include Pulmonary Hypertension Research and Treatments (14 papers), Cardiovascular and exercise physiology (5 papers) and Cardiovascular Effects of Exercise (4 papers). Michael G. Risbano is often cited by papers focused on Pulmonary Hypertension Research and Treatments (14 papers), Cardiovascular and exercise physiology (5 papers) and Cardiovascular Effects of Exercise (4 papers). Michael G. Risbano collaborates with scholars based in United States, France and Germany. Michael G. Risbano's co-authors include Mark T. Gladwin, Belinda Rivera‐Lebron, Stephen Y. Chan, Todd M. Bull, David H. Collier, Christina A. Meadows, Mark W. Geraci, Michael A. Mathier, Mehdi Nouraie and Jason Stamm and has published in prestigious journals such as Circulation, Circulation Research and American Journal of Respiratory and Critical Care Medicine.

In The Last Decade

Michael G. Risbano

35 papers receiving 485 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael G. Risbano United States 14 250 128 107 102 59 35 498
Ori Shokek United States 9 161 0.6× 101 0.8× 95 0.9× 49 0.5× 73 1.2× 15 475
Thomas F. Lüscher Switzerland 11 210 0.8× 187 1.5× 155 1.4× 97 1.0× 24 0.4× 22 863
Antonio Moscardó Spain 14 113 0.5× 198 1.5× 164 1.5× 89 0.9× 17 0.3× 34 688
Kieko Hara Japan 12 217 0.9× 83 0.6× 130 1.2× 83 0.8× 37 0.6× 30 600
Han Wu China 14 109 0.4× 176 1.4× 179 1.7× 44 0.4× 24 0.4× 49 624
Rita Paltriccia Italy 11 88 0.4× 145 1.1× 203 1.9× 62 0.6× 27 0.5× 24 525
Elvan Akin Germany 7 103 0.4× 206 1.6× 105 1.0× 114 1.1× 27 0.5× 9 504
Mark Lipphardt Germany 14 66 0.3× 48 0.4× 158 1.5× 49 0.5× 72 1.2× 18 532
Maysoon Elkhawad United Kingdom 8 125 0.5× 126 1.0× 128 1.2× 58 0.6× 18 0.3× 13 436
Atsuko Tahara Japan 13 289 1.2× 272 2.1× 172 1.6× 195 1.9× 34 0.6× 43 864

Countries citing papers authored by Michael G. Risbano

Since Specialization
Citations

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

Fields of papers citing papers by Michael G. Risbano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael G. Risbano. 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 Michael G. Risbano. The network helps show where Michael G. Risbano may publish in the future.

Co-authorship network of co-authors of Michael G. Risbano

This figure shows the co-authorship network connecting the top 25 collaborators of Michael G. Risbano. A scholar is included among the top collaborators of Michael G. Risbano 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 Michael G. Risbano. Michael G. Risbano 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.
Risbano, Michael G.. (2025). From fatigue to physiology: Submaximal 2‐day cardiopulmonary exercise test and emerging standards in long COVID. Experimental Physiology. 111(2). 344–345. 1 indexed citations
2.
Risbano, Michael G., et al.. (2024). Hemodynamic responses at anaerobic threshold during exercise in preload insufficiency. European Journal of Clinical Investigation. 55(2). e14343–e14343. 2 indexed citations
3.
4.
Risbano, Michael G., Corrine R. Kliment, D.G. Dunlap, et al.. (2023). Invasive Cardiopulmonary Exercise Testing Identifies Distinct Physiologic Endotypes in Postacute Sequelae of SARS-CoV-2 Infection. 1(3). 100010–100010. 7 indexed citations
5.
Pu, Jiantao, Naciye Sinem Gezer, Aylin Özgen Alpaydın, et al.. (2023). Automated detection and segmentation of pulmonary embolisms on computed tomography pulmonary angiography (CTPA) using deep learning but without manual outlining. Medical Image Analysis. 89. 102882–102882. 15 indexed citations
6.
Nouraie, Mehdi, et al.. (2023). Stressed Blood Volume Changes in a Cohort of Patients With Preload Insufficiency. A1190–A1190. 1 indexed citations
7.
Risbano, Michael G., Corrine R. Kliment, D.G. Dunlap, et al.. (2023). Post-acute Sequelae of SARS-CoV-2 Infection Patients Have Metabolic Reprogramming and Reduced Mitochondrial Function at Peak Exercise. A4231–A4231. 1 indexed citations
8.
9.
Pu, Jiantao, et al.. (2022). Automated identification of pulmonary arteries and veins depicted in non-contrast chest CT scans. Medical Image Analysis. 77. 102367–102367. 27 indexed citations
10.
Handen, Adam, Marc A. Simon, Michael G. Risbano, et al.. (2020). Outcomes of Pulmonary Arterial Hypertension Are Improved in a Specialty Care Center. CHEST Journal. 158(1). 330–340. 19 indexed citations
11.
Hansmann, Georg, Laurent Calvier, Michael G. Risbano, & Stephen Y. Chan. (2019). Activation of the Metabolic Master Regulator PPARγ: A Potential PIOneering Therapy for Pulmonary Arterial Hypertension. American Journal of Respiratory Cell and Molecular Biology. 62(2). 143–156. 32 indexed citations
12.
Risbano, Michael G., Tamir Kanias, Chenell Donadee, et al.. (2015). Effects of Aged Stored Autologous Red Blood Cells on Human Endothelial Function. American Journal of Respiratory and Critical Care Medicine. 192(10). 1223–1233. 54 indexed citations
13.
Hunt, James M., Michael G. Risbano, John C. Messenger, et al.. (2014). Timed Response to Inhaled Nitric Oxide in Pulmonary Hypertension. Pulmonary Circulation. 4(1). 103–109. 3 indexed citations
14.
Kapnadak, Siddhartha G., D. L. Abt, & Michael G. Risbano. (2013). Acute Respiratory Failure Mimicking Acute Respiratory Distress Syndrome Due to Parenchymal Infiltration by Metastatic Melanoma. Pulmonary Circulation. 3(4). 959–962. 1 indexed citations
15.
Risbano, Michael G. & Mark T. Gladwin. (2013). Therapeutics Targeting of Dysregulated Redox Equilibrium and Endothelial Dysfunction. Handbook of experimental pharmacology. 218. 315–349. 23 indexed citations
16.
Meadows, Christina A., Michael G. Risbano, Li Zhang, et al.. (2010). Increased Expression of Growth Differentiation Factor-15 in Systemic Sclerosis-Associated Pulmonary Arterial Hypertension. CHEST Journal. 139(5). 994–1002. 58 indexed citations
17.
Kendrick, Jessica, Michael G. Risbano, Steve D. Groshong, & Stanley Frankel. (2007). A Rare Presentation of Ischemic Pseudomembranous Colitis Due to Escherichia coli. Clinical Infectious Diseases. 45(2). 217–219. 14 indexed citations
18.
Risbano, Michael G., Steve D. Groshong, & Marvin I. Schwarz. (2007). Lung Nodules in a Woman With a History of Breast Cancer. CHEST Journal. 132(5). 1697–1701. 8 indexed citations
19.
Feldman, James A., et al.. (2002). Evaluating Acceptance and Understanding of Risk in the Emergency Department:Are All Risk Statements Created Equally?. Academic Emergency Medicine. 9(4). 309–316. 1 indexed citations
20.
Feldman, James A., et al.. (2002). Evaluating Acceptance and Understanding of Risk in the Emergency Department:Are All Risk Statements Created Equally?. Academic Emergency Medicine. 9(4). 309–316. 1 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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