Mark Finkelstein

1.4k total citations
49 papers, 835 citations indexed

About

Mark Finkelstein is a scholar working on Radiology, Nuclear Medicine and Imaging, Mathematical Physics and Surgery. According to data from OpenAlex, Mark Finkelstein has authored 49 papers receiving a total of 835 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Radiology, Nuclear Medicine and Imaging, 8 papers in Mathematical Physics and 7 papers in Surgery. Recurrent topics in Mark Finkelstein's work include Probability and Risk Models (5 papers), advanced mathematical theories (4 papers) and COVID-19 diagnosis using AI (4 papers). Mark Finkelstein is often cited by papers focused on Probability and Risk Models (5 papers), advanced mathematical theories (4 papers) and COVID-19 diagnosis using AI (4 papers). Mark Finkelstein collaborates with scholars based in United States, Russia and Israel. Mark Finkelstein's co-authors include Howard G. Tucker, Mario A. Cedillo, Adam Jacobi, Danielle Toussie, Michael Chung, Samuel Z. Maron, Adam Bernheim, Nicholas Voutsinas, Sayan Manna and Corey Eber and has published in prestigious journals such as Nature, Journal of the American Statistical Association and Radiology.

In The Last Decade

Mark Finkelstein

47 papers receiving 775 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 Finkelstein United States 15 251 171 168 104 103 49 835
Mohsin Ali United States 15 327 1.3× 104 0.6× 390 2.3× 134 1.3× 177 1.7× 49 1.6k
Davide Luciani Italy 12 236 0.9× 46 0.3× 122 0.7× 33 0.3× 218 2.1× 21 1.5k
Rafal Kustra Canada 17 137 0.5× 67 0.4× 85 0.5× 74 0.7× 82 0.8× 33 909
Amir Reza Radmard Iran 19 265 1.1× 295 1.7× 189 1.1× 329 3.2× 253 2.5× 76 1.5k
Amir H. Davarpanah United States 19 488 1.9× 169 1.0× 312 1.9× 109 1.0× 342 3.3× 53 1.1k
Achuta Kumar Guddati United States 18 87 0.3× 106 0.6× 206 1.2× 308 3.0× 194 1.9× 101 1.2k
Michael Nagler Switzerland 21 229 0.9× 162 0.9× 110 0.7× 71 0.7× 446 4.3× 102 1.6k
Jeremiah S. Hinson United States 20 213 0.8× 90 0.5× 105 0.6× 86 0.8× 154 1.5× 62 1.8k
Jamie S. Hirsch United States 20 94 0.4× 510 3.0× 107 0.6× 215 2.1× 144 1.4× 61 1.3k
Alexander Meyer Germany 22 136 0.5× 42 0.2× 229 1.4× 69 0.7× 406 3.9× 107 1.7k

Countries citing papers authored by Mark Finkelstein

Since Specialization
Citations

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

Fields of papers citing papers by Mark Finkelstein

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Finkelstein

This figure shows the co-authorship network connecting the top 25 collaborators of Mark Finkelstein. A scholar is included among the top collaborators of Mark Finkelstein 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 Finkelstein. Mark Finkelstein 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.
Yang, Anthony, et al.. (2024). Impact of Deep Learning Image Reconstruction Methods on MRI Throughput. Radiology Artificial Intelligence. 6(3). e230181–e230181. 10 indexed citations
2.
Finkelstein, Mark, et al.. (2024). The Impact of an Artificial Intelligence Certificate Program on Radiology Resident Education. Academic Radiology. 31(11). 4709–4714. 2 indexed citations
3.
Belani, Puneet, et al.. (2024). Radiological Diagnosis and Advances in Imaging of Vertebral Compression Fractures. Journal of Imaging. 10(10). 244–244. 2 indexed citations
4.
Gupta, Yogesh Sean, Mark Finkelstein, Sayan Manna, et al.. (2021). Coronary artery calcification in COVID-19 patients: an imaging biomarker for adverse clinical outcomes. Clinical Imaging. 77. 1–8. 18 indexed citations
5.
Pagano, Andrew, Mark Finkelstein, Jessica Overbey, et al.. (2021). Portable Chest Radiography as an Exclusionary Test for Adverse Clinical Outcomes During the COVID-19 Pandemic. CHEST Journal. 160(1). 238–248. 2 indexed citations
6.
Finkelstein, Mark, Samuel Z. Maron, Shingo Kihira, et al.. (2021). Sources of Revenue Loss and Recovery in Radiology Practices During the Coronavirus Disease 2019 (COVID-19) Pandemic. Academic Radiology. 28(4). 447–456. 2 indexed citations
7.
Doshi, Amish, Shingo Kihira, Keon Mahmoudi, et al.. (2021). Impact of COVID-19 social distancing regulations on outpatient diagnostic imaging volumes and no-show rates. Clinical Imaging. 76. 65–69. 11 indexed citations
8.
Kwon, Young Joon, Danielle Toussie, Mark Finkelstein, et al.. (2020). Combining Initial Radiographs and Clinical Variables Improves Deep Learning Prognostication in Patients with COVID-19 from the Emergency Department. Radiology Artificial Intelligence. 3(2). e200098–e200098. 41 indexed citations
9.
Toussie, Danielle, Nicholas Voutsinas, Mark Finkelstein, et al.. (2020). Clinical and Chest Radiography Features Determine Patient Outcomes in Young and Middle-aged Adults with COVID-19. Radiology. 297(1). E197–E206. 230 indexed citations
10.
Manna, Sayan, Samuel Z. Maron, Danielle Toussie, et al.. (2020). COVID-19: A Multimodality Review of Radiologic Techniques, Clinical Utility, and Imaging Features. Radiology Cardiothoracic Imaging. 2(3). e200210–e200210. 52 indexed citations
11.
Sharma, Himanshu, Mark Finkelstein, Brett Marinelli, et al.. (2020). The Role of Telemedicine in the Maintenance of IR Outpatient Evaluation and Management Volume During the COVID-19 Global Pandemic. Journal of Vascular and Interventional Radiology. 32(3). 479–481. 7 indexed citations
12.
Finkelstein, Mark, et al.. (2020). The Use of FDG PET Parametric Imaging in the Diagnosis of Olivopontocerebellar Atrophy. Clinical Nuclear Medicine. 45(9). e419–e421. 4 indexed citations
13.
Finkelstein, Mark, et al.. (1994). Convergence of Nonrandomly Centered Random Sums. Advances in Applied Mathematics. 15(3). 371–378. 1 indexed citations
14.
Nadkarni, Vinay, et al.. (1994). Inspiratory‐cycle Instillation of Endotracheal Epinephrine in Porcine Arrest. Academic Emergency Medicine. 1(4). 340–345. 5 indexed citations
15.
Nadkarni, Vinay, et al.. (1994). Effects of different techniques of endotracheal epinephrine administration in pediatric porcine hypoxic-hypercarbic cardiopulmonary arrest. Critical Care Medicine. 22(7). 1174–1180. 61 indexed citations
16.
Finkelstein, Mark & Howard G. Tucker. (1989). A necessary and sufficient condition for convergence in law of random sums of random variables under nonrandom centering. Proceedings of the American Mathematical Society. 107(4). 1061–1070. 10 indexed citations
17.
Finkelstein, Mark & Stephen Scheinberg. (1975). Kernels for solving problems of dirichlet type in a half-plane. Advances in Mathematics. 18(1). 108–113. 21 indexed citations
18.
Finkelstein, Mark. (1968). On the relation between measures and convex analytic functions. Illinois Journal of Mathematics. 12(2). 1 indexed citations
19.
Finkelstein, Mark. (1968). A compiler optimization technique. The Computer Journal. 11(1). 22–25. 2 indexed citations
20.
Finkelstein, Mark. (1967). Growth Estimates of Convex Functions. Proceedings of the American Mathematical Society. 18(3). 412–412. 14 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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