Won Chang
Impact in
-
- Medical Imaging Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
- Radiation Dose and Imaging
- Hepatology top 5%
- Hepatocellular Carcinoma Treatment and Prognosis
Papers in
- Hepatology 11
- Hepatocellular Carcinoma Treatment and Prognosis 11
-
- Radiomics and Machine Learning in Medical Imaging 5
- Radiation Dose and Imaging 3
- Co-authors
- Eun‐Hee Kang (3 shared papers)Jong Chul Ye (3 shared papers)Jeong Min Lee (23 shared papers)Jaejun Yoo (1 shared paper)Jeong Hee Yoon (22 shared papers)Joon Koo Han (13 shared papers)Sang Min Lee (9 shared papers)Young Hoon Kim (13 shared papers)
- Journals
- Korean Journal of Radiology (10 papers)European Radiology (8 papers)PLoS ONE (6 papers)Radiology (5 papers)Gastric Cancer (4 papers)
- Partner nations
- South KoreaEthiopiaPuerto Rico
In The Last Decade
Won Chang
68 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 91
- Radiology, Nuclear Medicine and Imaging 506
- Hepatology 151
- Oncology 204
- Biomedical Engineering 346
- Epidemiology 180
Countries citing papers authored by Won Chang
This map shows the geographic impact of Won Chang'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 Won Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Won Chang more than expected).
Fields of papers citing papers by Won Chang
This network shows the impact of papers produced by Won Chang. 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 Won Chang. The network helps show where Won Chang may publish in the future.
Co-authors
The 25 scholars most cited alongside Won Chang, 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 71 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 271 | |
| 2 | 2013 | 125 | |
| 3 | 2019 | 92 | |
| 4 | 2015 | 70 | |
| 5 | 2020 | 65 | |
| 6 | 2019 | 59 | |
| 7 | 2016 | 59 | |
| 8 | 2017 | 49 | |
| 9 | 2019 | 41 | |
| 10 | 2020 | 39 | |
| 11 | 2017 | 35 | |
| 12 | 2017 | 35 | |
| 13 | 2019 | 29 | |
| 14 | 2018 | 27 | |
| 15 | 2022 | 25 | |
| 16 | 2021 | 25 | |
| 17 | 2019 | 24 | |
| 18 | 2020 | 24 | |
| 19 | 2018 | 24 | |
| 20 | 2021 | 23 |
About Won Chang
Won Chang is a scholar working on Hepatology, Radiology, Nuclear Medicine and Imaging, Oncology, Epidemiology and Pulmonary and Respiratory Medicine, having authored 71 papers that have together received 1.5k indexed citations. Recurring topics across this work include Hepatocellular Carcinoma Treatment and Prognosis (11 papers), Liver Disease Diagnosis and Treatment (7 papers), Pancreatic and Hepatic Oncology Research (6 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Advanced X-ray and CT Imaging (5 papers), Gastric Cancer Management and Outcomes (4 papers), Colorectal Cancer Surgical Treatments (4 papers) and Radiation Dose and Imaging (3 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (506 citations), Hepatology (151 citations), Oncology (204 citations), Biomedical Engineering (346 citations) and Epidemiology (180 citations). Won Chang has collaborated with scholars based in South Korea, Ethiopia and Puerto Rico. Frequent co-authors include Eun‐Hee Kang, Jong Chul Ye, Jeong Min Lee, Jaejun Yoo, Jeong Hee Yoon, Joon Koo Han, Sang Min Lee, Young Hoon Kim, Yoon Jin Lee and Mi Hye Yu. Their work appears in journals such as Korean Journal of Radiology, European Radiology, PLoS ONE, Radiology and Gastric Cancer.
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.