Yae Won Park
Impact in
- Genetics top 1%
- Glioma Diagnosis and Treatment
- Health Informatics top 5%
Papers in
- Genetics 48
- Glioma Diagnosis and Treatment 48
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- Radiomics and Machine Learning in Medical Imaging 30
- MRI in cancer diagnosis 7
- Medical Imaging Techniques and Applications 7
- Co-authors
- Sung Soo Ahn (75 shared papers)Seung‐Koo Lee (73 shared papers)Se Hoon Kim (49 shared papers)Jong Hee Chang (51 shared papers)Kyunghwa Han (28 shared papers)Yoon Seong Choi (8 shared papers)Seok‐Gu Kang (23 shared papers)Eui Hyun Kim (22 shared papers)
- Journals
- European Radiology (14 papers)Korean Journal of Radiology (7 papers)Neuroradiology (6 papers)Journal of Neuro-Oncology (6 papers)Scientific Reports (5 papers)
- Partner nations
- South KoreaUnited StatesGermany
In The Last Decade
Yae Won Park
93 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 97
- Genetics 622
- Health Informatics 43
- Radiology, Nuclear Medicine and Imaging 598
- Neurology 161
- Neurology 76
Countries citing papers authored by Yae Won Park
This map shows the geographic impact of Yae Won Park'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 Yae Won Park with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yae Won Park more than expected).
Fields of papers citing papers by Yae Won Park
This network shows the impact of papers produced by Yae Won Park. 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 Yae Won Park. The network helps show where Yae Won Park may publish in the future.
Co-authors
The 25 scholars most cited alongside Yae Won Park, 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 98 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 152 | |
| 2 | 2017 | 121 | |
| 3 | 2019 | 78 | |
| 4 | 2021 | 61 | |
| 5 | 2018 | 59 | |
| 6 | 2007 | 56 | |
| 7 | 2023 | 53 | |
| 8 | 2021 | 52 | |
| 9 | 2019 | 46 | |
| 10 | 2020 | 41 | |
| 11 | 2021 | 40 | |
| 12 | 2020 | 37 | |
| 13 | 2021 | 36 | |
| 14 | 2021 | 36 | |
| 15 | 2018 | 35 | |
| 16 | 2020 | 34 | |
| 17 | 2019 | 34 | |
| 18 | 2020 | 30 | |
| 19 | 2021 | 30 | |
| 20 | 2020 | 29 |
About Yae Won Park
Yae Won Park is a scholar working on Genetics, Radiology, Nuclear Medicine and Imaging, Epidemiology, Pulmonary and Respiratory Medicine and Endocrinology, Diabetes and Metabolism, having authored 98 papers that have together received 1.8k indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (48 papers), Radiomics and Machine Learning in Medical Imaging (30 papers), Meningioma and schwannoma management (13 papers), Pituitary Gland Disorders and Treatments (8 papers), MRI in cancer diagnosis (7 papers), Medical Imaging Techniques and Applications (7 papers), Brain Metastases and Treatment (6 papers) and Cerebrospinal fluid and hydrocephalus (4 papers). The work is most often cited by research in Genetics (622 citations), Health Informatics (43 citations), Radiology, Nuclear Medicine and Imaging (598 citations), Neurology (161 citations) and Neurology (76 citations). Yae Won Park has collaborated with scholars based in South Korea, United States and Germany. Frequent co-authors include Sung Soo Ahn, Seung‐Koo Lee, Se Hoon Kim, Jong Hee Chang, Kyunghwa Han, Yoon Seong Choi, Seok‐Gu Kang, Eui Hyun Kim, Hwiyoung Kim and Chae Jung Park. Their work appears in journals such as European Radiology, Korean Journal of Radiology, Neuroradiology, Journal of Neuro-Oncology 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.