Hee Jung Shin
-
- MRI in cancer diagnosis 58
- Radiomics and Machine Learning in Medical Imaging 38
- Medical Imaging Techniques and Applications 17
- Advanced Neuroimaging Techniques and Applications 13
- Cancer Research top 2%
- Breast Cancer Treatment Studies 44
-
- Breast Lesions and Carcinomas 64
- Oncology top 5%
- Dermatology top 5%
-
- AI in cancer detection 22
-
- Digital Radiography and Breast Imaging 18
- Journals
- SHILAP Revista de lepidopterología (2 papers)PLoS ONE (2 papers)Scientific Reports (2 papers)
- Partner nations
- South KoreaUnited StatesBelarus
In The Last Decade
Hee Jung Shin
146 papers receiving 2.6k citations
Peers
Comparison fields: 5 of 110
- Radiology, Nuclear Medicine and Imaging 1.5k
- Cancer Research 912
- Pathology and Forensic Medicine 929
- Oncology 528
- Dermatology 146
Countries citing papers authored by Hee Jung Shin
This map shows the geographic impact of Hee Jung Shin'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 Hee Jung Shin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hee Jung Shin more than expected).
Fields of papers citing papers by Hee Jung Shin
This network shows the impact of papers produced by Hee Jung Shin. 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 Hee Jung Shin. The network helps show where Hee Jung Shin may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Hee Jung Shin, 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 | 2025 | 2 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 0 | |
| 5 | 2024 | 2 | |
| 6 | 2023 | 3 | |
| 7 | 2023 | 0 | |
| 8 | 2023 | 2 | |
| 9 | 2023 | 3 | |
| 10 | 2021 | 9 | |
| 11 | 2019 | 10 | |
| 12 | 2017 | 16 | |
| 13 | 2017 | 18 | |
| 14 | 2016 | 26 | |
| 15 | 2013 | 49 | |
| 16 | 2012 | 55 | |
| 17 | Automated Breast Ultrasound. | 2011 | 1 |
| 18 | 2007 | 8 | |
| 19 | 2007 | 22 | |
| 20 | The 2,3-Dihydroxybiphenyl 1,2-Dioxygenase Gene (phnQ) of Pseudomonas sp. DJ77: Nucleotide Sequence, Enzyme Assay, and Comparison with Isofunctional Dioxygenases | 1999 | 2 |
About Hee Jung Shin
Hee Jung Shin is a scholar working on Pathology and Forensic Medicine, Radiology, Nuclear Medicine and Imaging and Cancer Research, having authored 153 papers that have together received 2.7k indexed citations. Recurring topics across this work include Breast Lesions and Carcinomas (64 papers), MRI in cancer diagnosis (58 papers), Breast Cancer Treatment Studies (44 papers), Radiomics and Machine Learning in Medical Imaging (38 papers), AI in cancer detection (22 papers), Digital Radiography and Breast Imaging (18 papers), Medical Imaging Techniques and Applications (17 papers) and Advanced Neuroimaging Techniques and Applications (13 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.5k citations), Cancer Research (912 citations) and Pathology and Forensic Medicine (929 citations). Hee Jung Shin has collaborated with scholars based in South Korea, United States and Belarus. Frequent co-authors include Hak Hee Kim, Joo Hee, Eun Young Chae, Woo Jung Choi, Gyungyub Gong, Hyunji Kim, Su Min Ha, Sun Mi Kim, Byung Ho Son and Sei Hyun Ahn. Their work appears in journals such as SHILAP Revista de lepidopterología, 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.