Mi Young Kim
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- Medical Imaging Techniques and Applications 7
- MRI in cancer diagnosis 5
- Radiomics and Machine Learning in Medical Imaging 3
- Ultrasound Imaging and Elastography 2
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- Breast Cancer Treatment Studies 6
- Pathology and Forensic Medicine top 10%
- Breast Lesions and Carcinomas 10
- Artificial Intelligence top 10%
- AI in cancer detection 2
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- Digital Radiography and Breast Imaging 5
Mi Young Kim
27 papers receiving 583 citations
Peers
Comparison fields: 5 of 87
- Radiology, Nuclear Medicine and Imaging 269
- Cancer Research 147
- Pathology and Forensic Medicine 118
- Artificial Intelligence 132
- Oncology 111
Countries citing papers authored by Mi Young Kim
This map shows the geographic impact of Mi Young Kim'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 Mi Young Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mi Young Kim more than expected).
Fields of papers citing papers by Mi Young Kim
This network shows the impact of papers produced by Mi Young Kim. 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 Mi Young Kim. The network helps show where Mi Young Kim may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mi Young Kim, 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 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2021 | 2 | |
| 4 | 2021 | 10 | |
| 5 | 2020 | 19 | |
| 6 | 2018 | 16 | |
| 7 | 2018 | 0 | |
| 8 | 2017 | 8 | |
| 9 | 2017 | 39 | |
| 10 | 2015 | 13 | |
| 11 | 2015 | 5 | |
| 12 | 2014 | 7 | |
| 13 | 2014 | 22 | |
| 14 | T1-T2 breast cancer with nodal metastasis: characteristics of pN2 or higher disease compared to pN1 disease. | 2014 | 1 |
| 15 | 2013 | 127 | |
| 16 | 2013 | 23 | |
| 17 | 2013 | 22 | |
| 18 | 2013 | 12 | |
| 19 | 2013 | 37 | |
| 20 | 2006 | 43 |
About Mi Young Kim
Mi Young Kim is a scholar working on Radiology, Nuclear Medicine and Imaging, Pathology and Forensic Medicine, Cancer Research, Otorhinolaryngology and Genetics, having authored 28 papers that have together received 593 indexed citations. Recurring topics across this work include Breast Lesions and Carcinomas (10 papers), Medical Imaging Techniques and Applications (7 papers), Breast Cancer Treatment Studies (6 papers), MRI in cancer diagnosis (5 papers), Digital Radiography and Breast Imaging (5 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), AI in cancer detection (2 papers) and Ultrasound Imaging and Elastography (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (269 citations), Cancer Research (147 citations), Pathology and Forensic Medicine (118 citations), Artificial Intelligence (132 citations) and Oncology (111 citations). Mi Young Kim has collaborated with scholars based in South Korea, Ethiopia and Puerto Rico. Frequent co-authors include Nami Choi, Nariya Cho, Hye Ryoung Koo, Woo Kyung Moon, Min Sun Bae, Won Hwa Kim, Jung Min Chang, Mirinae Seo, Bo La Yun and Ann Yi. Their work appears in journals such as Acta Radiologica, Korean Journal of Radiology, Breast Cancer Research and Treatment, Medicine and Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease.
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.