Song‐Ee Baek
Impact in
- Hepatology top 5%
- Hepatocellular Carcinoma Treatment and Prognosis
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- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
Papers in
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- MRI in cancer diagnosis 3
- Cardiac Imaging and Diagnostics 3
- Radiomics and Machine Learning in Medical Imaging 2
- Foreign Body Medical Cases 1
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- Hepatocellular Carcinoma Treatment and Prognosis 5
- Co-authors
- Joon Seok Lim (9 shared papers)Myeong‐Jin Kim (13 shared papers)Nam Kyu Kim (3 shared papers)Mi‐Suk Park (10 shared papers)Sung‐Won Kim (2 shared papers)Nak‐Hoon Son (2 shared papers)Nieun Seo (2 shared papers)Jaeseung Shin (2 shared papers)
- Journals
- European Radiology (3 papers)American Journal of Roentgenology (3 papers)Korean Journal of Radiology (3 papers)Oncotarget (2 papers)PLoS ONE (2 papers)
- Partner nations
- South KoreaUnited StatesChina
In The Last Decade
Song‐Ee Baek
29 papers receiving 928 citations
Song‐Ee Baek's Hit Papers
Peers
Comparison fields: 5 of 35
- Hepatology 144
- Radiology, Nuclear Medicine and Imaging 246
- Oncology 120
- Health Informatics 11
- Pulmonary and Respiratory Medicine 94
Countries citing papers authored by Song‐Ee Baek
This map shows the geographic impact of Song‐Ee Baek'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 Song‐Ee Baek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Song‐Ee Baek more than expected).
Fields of papers citing papers by Song‐Ee Baek
This network shows the impact of papers produced by Song‐Ee Baek. 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 Song‐Ee Baek. The network helps show where Song‐Ee Baek may publish in the future.
Co-authors
The 25 scholars most cited alongside Song‐Ee Baek, 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 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | MRI Radiomics Model Predicts Pathologic Complete Response of Rectal Cancer Following Chemoradiotherapy Hit paper breakdown → | 2022 | 182 |
| 2 | 2020 | 101 | |
| 3 | 2018 | 84 | |
| 4 | 2012 | 77 | |
| 5 | 2011 | 76 | |
| 6 | 2012 | 69 | |
| 7 | 2018 | 54 | |
| 8 | 2020 | 36 | |
| 9 | 2012 | 30 | |
| 10 | 2014 | 26 | |
| 11 | 2021 | 26 | |
| 12 | 2012 | 21 | |
| 13 | 2015 | 21 | |
| 14 | 2015 | 21 | |
| 15 | 2018 | 17 | |
| 16 | 2009 | 16 | |
| 17 | 2010 | 11 | |
| 18 | 2019 | 11 | |
| 19 | 2016 | 10 | |
| 20 | 2011 | 9 |
About Song‐Ee Baek
Song‐Ee Baek is a scholar working on Radiology, Nuclear Medicine and Imaging, Hepatology, Oncology, Health Informatics and Pulmonary and Respiratory Medicine, having authored 31 papers that have together received 941 indexed citations. Recurring topics across this work include Hepatocellular Carcinoma Treatment and Prognosis (5 papers), MRI in cancer diagnosis (3 papers), Cardiac Imaging and Diagnostics (3 papers), Gastric Cancer Management and Outcomes (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Foreign Body Medical Cases (1 paper), Artificial Intelligence in Healthcare and Education (1 paper) and Cancer Immunotherapy and Biomarkers (1 paper). The work is most often cited by research in Hepatology (144 citations), Radiology, Nuclear Medicine and Imaging (246 citations), Oncology (120 citations), Health Informatics (11 citations) and Pulmonary and Respiratory Medicine (94 citations). Song‐Ee Baek has collaborated with scholars based in South Korea, United States and China. Frequent co-authors include Joon Seok Lim, Myeong‐Jin Kim, Nam Kyu Kim, Mi‐Suk Park, Sung‐Won Kim, Nak‐Hoon Son, Nieun Seo, Jaeseung Shin, Woong Sub Koom and Jin‐Young Choi. Their work appears in journals such as European Radiology, American Journal of Roentgenology, Korean Journal of Radiology, Oncotarget and PLoS ONE.
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.