Beomhee Park
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- COVID-19 diagnosis using AI 9
- Radiomics and Machine Learning in Medical Imaging 7
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- Lung Cancer Diagnosis and Treatment 8
- Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis 1
- Co-authors
- Namkug Kim (14 shared papers)Joon Beom Seo (11 shared papers)Sang Min Lee (5 shared papers)Yongwon Cho (5 shared papers)Jihye Yun (2 shared papers)Hyun‐Jin Bae (2 shared papers)Jongha Park (1 shared paper)Hee-Jun Park (1 shared paper)
- Journals
- Scientific Reports (6 papers)Journal of Digital Imaging (4 papers)Computers in Biology and Medicine (1 paper)Journal of Clinical Medicine (1 paper)Radiology (1 paper)
- Partner nations
- South Korea
In The Last Decade
Beomhee Park
16 papers receiving 531 citations
Peers
Comparison fields: 5 of 98
- Health Informatics 34
- Radiology, Nuclear Medicine and Imaging 299
- Pulmonary and Respiratory Medicine 218
- Artificial Intelligence 124
- Computer Vision and Pattern Recognition 76
Countries citing papers authored by Beomhee Park
This map shows the geographic impact of Beomhee 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 Beomhee Park with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Beomhee Park more than expected).
Fields of papers citing papers by Beomhee Park
This network shows the impact of papers produced by Beomhee 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 Beomhee Park. The network helps show where Beomhee Park may publish in the future.
Co-authors
The 25 scholars most cited alongside Beomhee 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
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 90 | |
| 2 | 2019 | 82 | |
| 3 | 2020 | 78 | |
| 4 | 2021 | 53 | |
| 5 | 2018 | 52 | |
| 6 | 2020 | 39 | |
| 7 | 2020 | 32 | |
| 8 | 2020 | 24 | |
| 9 | 2019 | 21 | |
| 10 | 2019 | 19 | |
| 11 | 2017 | 14 | |
| 12 | 2020 | 13 | |
| 13 | 2021 | 8 | |
| 14 | 2022 | 6 | |
| 15 | 2020 | 6 | |
| 16 | 2020 | 6 |
About Beomhee Park
Beomhee Park is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Computer Vision and Pattern Recognition, Radiation and Epidemiology, having authored 16 papers that have together received 543 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (9 papers), Lung Cancer Diagnosis and Treatment (8 papers), Radiomics and Machine Learning in Medical Imaging (7 papers), AI in cancer detection (2 papers), Advanced Neural Network Applications (2 papers), Hepatocellular Carcinoma Treatment and Prognosis (1 paper), Advanced X-ray Imaging Techniques (1 paper) and Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (1 paper). The work is most often cited by research in Health Informatics (34 citations), Radiology, Nuclear Medicine and Imaging (299 citations), Pulmonary and Respiratory Medicine (218 citations), Artificial Intelligence (124 citations) and Computer Vision and Pattern Recognition (76 citations). Beomhee Park has collaborated with scholars based in South Korea. Frequent co-authors include Namkug Kim, Joon Beom Seo, Sang Min Lee, Yongwon Cho, Jihye Yun, Hyun‐Jin Bae, Jongha Park, Hee-Jun Park, Minho Lee and Sang Min Lee. Their work appears in journals such as Scientific Reports, Journal of Digital Imaging, Computers in Biology and Medicine, Journal of Clinical Medicine and Radiology.
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.