Mark Sak
Impact in
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- Ultrasound Imaging and Elastography
- Medical Imaging Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
- Artificial Intelligence top 10%
- AI in cancer detection
Papers in
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- Digital Radiography and Breast Imaging 17
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- AI in cancer detection 18
- Co-authors
- Peter J. Littrup (22 shared papers)Neb Duric (18 shared papers)Gretchen L. Gierach (11 shared papers)Mark E. Sherman (11 shared papers)Lisa Bey‐Knight (9 shared papers)Cuiping Li (8 shared papers)Haythem Ali (4 shared papers)Nebojsa Duric (7 shared papers)
- Journals
- Journal of Clinical Medicine (4 papers)Medical Physics (2 papers)BioMed Research International (1 paper)Sensors (1 paper)npj Breast Cancer (1 paper)
- Partner nations
- United StatesCanadaChina
In The Last Decade
Mark Sak
26 papers receiving 304 citations
Peers
Comparison fields: 5 of 46
- Radiology, Nuclear Medicine and Imaging 176
- Artificial Intelligence 133
- Pulmonary and Respiratory Medicine 123
- Biomedical Engineering 120
- Oncology 57
Countries citing papers authored by Mark Sak
This map shows the geographic impact of Mark Sak'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 Sak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Sak more than expected).
Fields of papers citing papers by Mark Sak
This network shows the impact of papers produced by Mark Sak. 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 Sak. The network helps show where Mark Sak may publish in the future.
Co-authors
The 25 scholars most cited alongside Mark Sak, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 53 | |
| 2 | 2013 | 52 | |
| 3 | 2015 | 31 | |
| 4 | 2020 | 27 | |
| 5 | 2015 | 22 | |
| 6 | 2017 | 22 | |
| 7 | 2013 | 14 | |
| 8 | 2021 | 13 | |
| 9 | 2020 | 9 | |
| 10 | 2011 | 8 | |
| 11 | 2012 | 7 | |
| 12 | 2017 | 7 | |
| 13 | 2014 | 6 | |
| 14 | 2011 | 6 | |
| 15 | 2021 | 6 | |
| 16 | 2020 | 5 | |
| 17 | 2017 | 5 | |
| 18 | 2011 | 5 | |
| 19 | 2022 | 5 | |
| 20 | The Role Of Tissue Sound Speed As A Surrogate Marker Of Breast Density | 2013 | 3 |
About Mark Sak
Mark Sak is a scholar working on Pulmonary and Respiratory Medicine, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Oncology and Pathology and Forensic Medicine, having authored 27 papers that have together received 318 indexed citations. Recurring topics across this work include AI in cancer detection (18 papers), Digital Radiography and Breast Imaging (17 papers), Ultrasound Imaging and Elastography (10 papers), Global Cancer Incidence and Screening (7 papers), Breast Lesions and Carcinomas (5 papers), Breast Cancer Treatment Studies (3 papers), Medical Imaging Techniques and Applications (3 papers) and Photoacoustic and Ultrasonic Imaging (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (176 citations), Artificial Intelligence (133 citations), Pulmonary and Respiratory Medicine (123 citations), Biomedical Engineering (120 citations) and Oncology (57 citations). Mark Sak has collaborated with scholars based in United States, Canada and China. Frequent co-authors include Peter J. Littrup, Neb Duric, Gretchen L. Gierach, Mark E. Sherman, Lisa Bey‐Knight, Cuiping Li, Haythem Ali, Nebojsa Duric, Rachel F. Brem and Norman F. Boyd. Their work appears in journals such as Journal of Clinical Medicine, Medical Physics, BioMed Research International, Sensors and npj Breast Cancer.
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.