Sanja Antic
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Medical Imaging Techniques and Applications
- Health Informatics top 10%
Papers in
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- Lung Cancer Diagnosis and Treatment 20
- Lung Cancer Treatments and Mutations 6
- Ferroptosis and cancer prognosis 1
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- Radiomics and Machine Learning in Medical Imaging 18
- Medical Imaging Techniques and Applications 4
- COVID-19 diagnosis using AI 4
- Co-authors
- Pierre P. Massion (22 shared papers)Bennett A. Landman (18 shared papers)Gary T. Smith (3 shared papers)Yuankai Huo (10 shared papers)Riqiang Gao (12 shared papers)Kim L. Sandler (14 shared papers)Ronald C. Walker (6 shared papers)Yucheng Tang (8 shared papers)
- Journals
- Cancer Biomarkers (2 papers)BMC Cancer (2 papers)Cancer Research (2 papers)PLoS ONE (2 papers)Scientific Reports (2 papers)
- Partner nations
- United StatesChinaJapan
In The Last Decade
Sanja Antic
27 papers receiving 454 citations
Peers
Comparison fields: 5 of 62
- Radiology, Nuclear Medicine and Imaging 242
- Health Informatics 14
- Pulmonary and Respiratory Medicine 252
- Artificial Intelligence 68
- Cancer Research 22
Countries citing papers authored by Sanja Antic
This map shows the geographic impact of Sanja Antic'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 Sanja Antic with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sanja Antic more than expected).
Fields of papers citing papers by Sanja Antic
This network shows the impact of papers produced by Sanja Antic. 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 Sanja Antic. The network helps show where Sanja Antic may publish in the future.
Co-authors
The 25 scholars most cited alongside Sanja Antic, 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 29 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 120 | |
| 2 | 2016 | 85 | |
| 3 | 2019 | 39 | |
| 4 | 2020 | 30 | |
| 5 | 2020 | 22 | |
| 6 | 2018 | 19 | |
| 7 | 2019 | 15 | |
| 8 | 2023 | 14 | |
| 9 | 2022 | 13 | |
| 10 | 2023 | 11 | |
| 11 | 2023 | 10 | |
| 12 | 2022 | 10 | |
| 13 | 2020 | 10 | |
| 14 | 2018 | 10 | |
| 15 | 2023 | 8 | |
| 16 | 2021 | 8 | |
| 17 | 2022 | 7 | |
| 18 | 2020 | 7 | |
| 19 | 2023 | 5 | |
| 20 | 2020 | 5 |
About Sanja Antic
Sanja Antic is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Oncology, Artificial Intelligence and Genetics, having authored 29 papers that have together received 459 indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (20 papers), Radiomics and Machine Learning in Medical Imaging (18 papers), Lung Cancer Treatments and Mutations (6 papers), Medical Imaging Techniques and Applications (4 papers), COVID-19 diagnosis using AI (4 papers), AI in cancer detection (2 papers), Body Composition Measurement Techniques (1 paper) and Ferroptosis and cancer prognosis (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (242 citations), Health Informatics (14 citations), Pulmonary and Respiratory Medicine (252 citations), Artificial Intelligence (68 citations) and Cancer Research (22 citations). Sanja Antic has collaborated with scholars based in United States, China and Japan. Frequent co-authors include Pierre P. Massion, Bennett A. Landman, Gary T. Smith, Yuankai Huo, Riqiang Gao, Kim L. Sandler, Ronald C. Walker, Yucheng Tang, Robert J. Gillies and Thomas Atwater. Their work appears in journals such as Cancer Biomarkers, BMC Cancer, Cancer Research, PLoS ONE and Scientific Reports.
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.