Won Chang

1.9k citations
61 papers · 1.3k · h-index 19

Impact in

    • Medical Imaging Techniques and Applications
    • Radiation Dose and Imaging
    • Radiomics and Machine Learning in Medical Imaging
    • MRI in cancer diagnosis
  • Hepatology top 5%
    • Hepatocellular Carcinoma Treatment and Prognosis

Papers in

Won Chang

59 papers receiving 1.2k citations

Peers

Won Chang
Comparison fields: 5 of 94
  • Radiology, Nuclear Medicine and Imaging 742
  • Hepatology 225
  • Biomedical Engineering 500
  • Oncology 222
  • Epidemiology 235
Replace Joseph R. Grajo with:
Joseph R. Grajo United States
Nadine Abi‐Jaoudeh United States
Peter Isfort Germany
Frank Fischbach Germany
Jae Seok Bae South Korea
Yoshifumi Noda Japan
Jong Hyo Kim South Korea
Manish Dhyani United States
Helen Kavnoudias Australia
Shintaro Ichikawa Japan
Won Chang relative to Joseph R. Grajo United States Joseph R. Grajo's profile →
Citations per field
00.5×1.5×2.3×
Joseph R. Grajo · 1×
Citations per year

Countries citing papers authored by Won Chang

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Won Chang Line = papers co-authored together Won Chang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 61 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2018235
2 2013123
3 201986
4 201564
5 202059
6 201656
7 201951
8 201938
9 202035
10 201733
11 201731
12 201927
13 201825
14 201822
15 201620
16 201720
17 201920
18 202120
19 201620
20 201718

About Won Chang

Won Chang is a scholar working on Radiology, Nuclear Medicine and Imaging, Hepatology, Epidemiology, Biomedical Engineering and Oncology, having authored 61 papers that have together received 1.3k indexed citations. Recurring topics across this work include Hepatocellular Carcinoma Treatment and Prognosis (18 papers), Liver Disease Diagnosis and Treatment (16 papers), Advanced X-ray and CT Imaging (11 papers), Radiomics and Machine Learning in Medical Imaging (9 papers), MRI in cancer diagnosis (8 papers), Medical Imaging Techniques and Applications (8 papers), Pancreatic and Hepatic Oncology Research (8 papers) and Renal cell carcinoma treatment (7 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (742 citations), Hepatology (225 citations), Biomedical Engineering (500 citations), Oncology (222 citations) and Epidemiology (235 citations). Won Chang has collaborated with scholars based in South Korea, Ethiopia and Puerto Rico. Frequent co-authors include Jeong Min Lee, Eun‐Hee Kang, Jong Chul Ye, 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 Investigative 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.

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