James M. Dolezal
- Molecular Biology
- Artificial Intelligence top 5%
- Cancer Research top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Oncology
- Co-authors
- Edward V. ProchownikAlexander T. PearsonSara KochannyHuabo WangJefree J. SchulteFrederick M. HowardNicole A. CiprianiSucheta Kulkarni
- Topics
- AI in cancer detection (12 papers)Radiomics and Machine Learning in Medical Imaging (7 papers)Cancer Genomics and Diagnostics (5 papers)
- Partner nations
- United StatesItalyUnited Kingdom
In The Last Decade
James M. Dolezal
26 papers receiving 675 citations
Peers
Comparison fields: 5 of 92
- Molecular Biology 271
- Artificial Intelligence 229
- Cancer Research 192
- Radiology, Nuclear Medicine and Imaging 172
- Oncology 112
Countries citing papers authored by James M. Dolezal
This map shows the geographic impact of James M. Dolezal'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 James M. Dolezal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James M. Dolezal more than expected).
Fields of papers citing papers by James M. Dolezal
This network shows the impact of papers produced by James M. Dolezal. 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 James M. Dolezal. The network helps show where James M. Dolezal may publish in the future.
Co-authorship network of co-authors of James M. Dolezal
This figure shows the co-authorship network connecting the top 25 collaborators of James M. Dolezal. A scholar is included among the top collaborators of James M. Dolezal 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 James M. Dolezal. James M. Dolezal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 8 | |
| 4 | 23 | |
| 5 | 20 | |
| 6 | 5 | |
| 7 | 16 | |
| 8 | 6 | |
| 9 | 30 | |
| 10 | 75 | |
| 11 | 4 | |
| 12 | 2 | |
| 13 | 43 | |
| 14 | 20 | |
| 15 | 70 | |
| 16 | 30 | |
| 17 | 28 | |
| 18 | 40 | |
| 19 | 29 | |
| 20 | 43 |
About James M. Dolezal
James M. Dolezal is a scholar working on Biophysics, Cancer Research and Artificial Intelligence, having authored 29 papers that have together received 679 indexed citations. Recurring topics across this work include AI in cancer detection (12 papers), Radiomics and Machine Learning in Medical Imaging (7 papers) and Cancer Genomics and Diagnostics (5 papers). The work is most often cited by research in Health Informatics (50 citations), Cancer Research (192 citations) and Biophysics (43 citations). James M. Dolezal has collaborated with scholars based in United States, Italy and United Kingdom. Frequent co-authors include Edward V. Prochownik, Alexander T. Pearson, Sara Kochanny, Huabo Wang, Jefree J. Schulte, Frederick M. Howard, Nicole A. Cipriani, Sucheta Kulkarni, Jie Lu and Olufunmilayo I. Olopade. Their work appears in journals such as Journal of Biological Chemistry, Nature Communications and Journal of Clinical Oncology.
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.