Mark Finkelstein
Impact in
- Health Informatics top 5%
Papers in
-
- COVID-19 diagnosis using AI 4
- Radiology practices and education 4
- Radiomics and Machine Learning in Medical Imaging 4
-
- advanced mathematical theories 4
- Stochastic processes and statistical mechanics 3
- Co-authors
- Howard G. Tucker (10 shared papers)Mario A. Cedillo (7 shared papers)Corey Eber (7 shared papers)Samuel Z. Maron (6 shared papers)Adam Jacobi (7 shared papers)Adam Bernheim (7 shared papers)Sayan Manna (7 shared papers)Danielle Toussie (7 shared papers)
- Journals
- Proceedings of the American Mathematical Society (6 papers)Radiology Artificial Intelligence (2 papers)Academic Radiology (2 papers)Urology (2 papers)Advances in Applied Probability (2 papers)
- Partner nations
- United StatesRussiaIsrael
In The Last Decade
Mark Finkelstein
47 papers receiving 775 citations
Peers
Comparison fields: 5 of 121
- Health Informatics 35
- Critical Care and Intensive Care Medicine 65
- Radiology, Nuclear Medicine and Imaging 251
- Infectious Diseases 171
- Emergency Medicine 75
Countries citing papers authored by Mark Finkelstein
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
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-authors
The 25 scholars most cited alongside Mark Finkelstein, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 49 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 230 | |
| 2 | 1994 | 61 | |
| 3 | 2020 | 52 | |
| 4 | 2020 | 43 | |
| 5 | 1981 | 43 | |
| 6 | 2020 | 41 | |
| 7 | 1971 | 38 | |
| 8 | 1986 | 27 | |
| 9 | 2006 | 25 | |
| 10 | 2017 | 22 | |
| 11 | 1975 | 21 | |
| 12 | 2021 | 18 | |
| 13 | 1967 | 16 | |
| 14 | 1998 | 16 | |
| 15 | 2017 | 15 | |
| 16 | 1967 | 14 | |
| 17 | 2021 | 11 | |
| 18 | 1989 | 10 | |
| 19 | 2024 | 10 | |
| 20 | 2012 | 10 |
About Mark Finkelstein
Mark Finkelstein is a scholar working on Radiology, Nuclear Medicine and Imaging, Mathematical Physics, Surgery, Management Science and Operations Research and Oncology, having authored 49 papers that have together received 835 indexed citations. Recurring topics across this work include Probability and Risk Models (5 papers), COVID-19 diagnosis using AI (4 papers), Radiology practices and education (4 papers), advanced mathematical theories (4 papers), COVID-19 and healthcare impacts (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Stochastic processes and statistical mechanics (3 papers) and Functional Equations Stability Results (2 papers). The work is most often cited by research in Health Informatics (35 citations), Critical Care and Intensive Care Medicine (65 citations), Radiology, Nuclear Medicine and Imaging (251 citations), Infectious Diseases (171 citations) and Emergency Medicine (75 citations). Mark Finkelstein has collaborated with scholars based in United States, Russia and Israel. Frequent co-authors include Howard G. Tucker, Mario A. Cedillo, Corey Eber, Samuel Z. Maron, Adam Jacobi, Adam Bernheim, Sayan Manna, Danielle Toussie, Michael Chung and Nicholas Voutsinas. Their work appears in journals such as Proceedings of the American Mathematical Society, Radiology Artificial Intelligence, Academic Radiology, Urology and Advances in Applied Probability.
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.