D. Schött
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- COVID-19 diagnosis using AI
- Health Informatics top 10%
Papers in
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- Radiomics and Machine Learning in Medical Imaging 10
- MRI in cancer diagnosis 3
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- Advanced X-ray and CT Imaging 8
- Co-authors
- X. Allen Li (8 shared papers)William A. Hall (9 shared papers)Haidy Nasief (3 shared papers)Cheng Zheng (2 shared papers)Beth Erickson (2 shared papers)Susan Tsai (2 shared papers)Bradley A. Erickson (7 shared papers)Paul Knechtges (6 shared papers)
- Journals
- International Journal of Radiation Oncology*Biology*Physics (4 papers)Medical Physics (4 papers)PLoS ONE (1 paper)Radiotherapy and Oncology (1 paper)European Journal of Neurology (1 paper)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
D. Schött
15 papers receiving 376 citations
Peers
Comparison fields: 5 of 37
- Radiology, Nuclear Medicine and Imaging 227
- Health Informatics 14
- Oncology 149
- Radiation 26
- Artificial Intelligence 77
Countries citing papers authored by D. Schött
This map shows the geographic impact of D. Schött'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 D. Schött with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D. Schött more than expected).
Fields of papers citing papers by D. Schött
This network shows the impact of papers produced by D. Schött. 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 D. Schött. The network helps show where D. Schött may publish in the future.
Co-authors
The 25 scholars most cited alongside D. Schött, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 134 | |
| 2 | 2020 | 74 | |
| 3 | 2017 | 72 | |
| 4 | 2018 | 37 | |
| 5 | 2020 | 15 | |
| 6 | 2018 | 12 | |
| 7 | 2000 | 11 | |
| 8 | 2021 | 11 | |
| 9 | 2019 | 7 | |
| 10 | 2016 | 3 | |
| 11 | 2019 | 2 | |
| 12 | 2016 | 1 | |
| 13 | 2019 | 1 | |
| 14 | 2019 | 1 | |
| 15 | 2019 | 1 | |
| 16 | 2020 | 0 | |
| 17 | 2019 | 0 |
About D. Schött
D. Schött is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering, Oncology, Radiation and Pulmonary and Respiratory Medicine, having authored 17 papers that have together received 382 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (10 papers), Advanced X-ray and CT Imaging (8 papers), Pancreatic and Hepatic Oncology Research (4 papers), Advanced Radiotherapy Techniques (3 papers), MRI in cancer diagnosis (3 papers), Hepatocellular Carcinoma Treatment and Prognosis (2 papers), Endometrial and Cervical Cancer Treatments (1 paper) and Cardiovascular Health and Disease Prevention (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (227 citations), Health Informatics (14 citations), Oncology (149 citations), Radiation (26 citations) and Artificial Intelligence (77 citations). D. Schött has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include X. Allen Li, William A. Hall, Haidy Nasief, Cheng Zheng, Beth Erickson, Susan Tsai, Bradley A. Erickson, Paul Knechtges, E.S. Paulson and Kiyoko Oshima. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, Medical Physics, PLoS ONE, Radiotherapy and Oncology and European Journal of Neurology.
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.