Yuan‐Hsiang Chang
- Artificial Intelligence top 5%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computer Vision and Pattern Recognition top 10%
- Pulmonary and Respiratory Medicine
- Oncology
- Co-authors
- David GurBin ZhengWalter F. GoodLara A. HardestyThomas ChangWilliam R. PollerXiao Hui WangXiaohui Wang
- Topics
- AI in cancer detection (21 papers)Radiomics and Machine Learning in Medical Imaging (10 papers)Cell Image Analysis Techniques (8 papers)
- Journals
- SHILAP Revista de lepidopterologíaAmerican Journal of RoentgenologyMedical Physics
- Partner nations
- United StatesTaiwanJapan
In The Last Decade
Yuan‐Hsiang Chang
40 papers receiving 426 citations
Peers
Comparison fields: 5 of 62
- Artificial Intelligence 327
- Radiology, Nuclear Medicine and Imaging 157
- Computer Vision and Pattern Recognition 128
- Pulmonary and Respiratory Medicine 104
- Oncology 104
Countries citing papers authored by Yuan‐Hsiang Chang
This map shows the geographic impact of Yuan‐Hsiang 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 Yuan‐Hsiang Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuan‐Hsiang Chang more than expected).
Fields of papers citing papers by Yuan‐Hsiang Chang
This network shows the impact of papers produced by Yuan‐Hsiang 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 Yuan‐Hsiang Chang. The network helps show where Yuan‐Hsiang Chang may publish in the future.
Co-authorship network of co-authors of Yuan‐Hsiang Chang
This figure shows the co-authorship network connecting the top 25 collaborators of Yuan‐Hsiang Chang. A scholar is included among the top collaborators of Yuan‐Hsiang Chang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yuan‐Hsiang Chang. Yuan‐Hsiang Chang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 6 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | Development of Bill-Counterfeit Prevention Technology for Multi-Function Peripherals. | 1 |
| 7 | 5 | |
| 8 | 42 | |
| 9 | 24 | |
| 10 | 30 | |
| 11 | 12 | |
| 12 | 45 | |
| 13 | 16 | |
| 14 | 14 | |
| 15 | 21 | |
| 16 | 8 | |
| 17 | 6 | |
| 18 | 21 | |
| 19 | 1 | |
| 20 | 33 |
About Yuan‐Hsiang Chang
Yuan‐Hsiang Chang is a scholar working on Biophysics, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 41 papers that have together received 439 indexed citations. Recurring topics across this work include AI in cancer detection (21 papers), Radiomics and Machine Learning in Medical Imaging (10 papers) and Cell Image Analysis Techniques (8 papers). The work is most often cited by research in Artificial Intelligence (327 citations), Radiology, Nuclear Medicine and Imaging (157 citations) and Biophysics (38 citations). Yuan‐Hsiang Chang has collaborated with scholars based in United States, Taiwan and Japan. Frequent co-authors include David Gur, Bin Zheng, Walter F. Good, Lara A. Hardesty, Thomas Chang, William R. Poller, Xiao Hui Wang, Xiaohui Wang, Kuniya Abe and Hideo Yokota. Their work appears in journals such as SHILAP Revista de lepidopterología, American Journal of Roentgenology and Medical Physics.
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.