Hang Chang
Impact in
- Biophysics top 0.5%
- Cell Image Analysis Techniques
-
- Digital Imaging for Blood Diseases
- Medical Image Segmentation Techniques
Papers in
-
- Medical Image Segmentation Techniques 15
- Digital Imaging for Blood Diseases 8
-
- Gut microbiota and health 9
- Co-authors
- Bahram Parvin (27 shared papers)Paul T. Spellman (13 shared papers)Bahram Parvin (16 shared papers)Jian‐Hua Mao (33 shared papers)Ju Han (18 shared papers)Antoine M. Snijders (25 shared papers)Alexander D. Borowsky (10 shared papers)Qing Yang (5 shared papers)
- Journals
- Scientific Reports (4 papers)Environment International (3 papers)International Journal of Computer Vision (3 papers)Cancer Research (2 papers)Journal of Geophysical Research Oceans (2 papers)
- Partner nations
- United StatesChinaAustralia
In The Last Decade
Hang Chang
100 papers receiving 2.6k citations
Peers
Comparison fields: 5 of 158
- Biophysics 354
- Computer Vision and Pattern Recognition 719
- Artificial Intelligence 790
- Biological Psychiatry 39
- Media Technology 156
Countries citing papers authored by Hang Chang
This map shows the geographic impact of Hang 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 Hang Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hang Chang more than expected).
Fields of papers citing papers by Hang Chang
This network shows the impact of papers produced by Hang 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 Hang Chang. The network helps show where Hang Chang may publish in the future.
Co-authors
The 25 scholars most cited alongside Hang 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 104 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 183 | |
| 2 | 2013 | 160 | |
| 3 | 2012 | 158 | |
| 4 | 2007 | 136 | |
| 5 | 2017 | 132 | |
| 6 | 2014 | 91 | |
| 7 | 2012 | 82 | |
| 8 | 2020 | 80 | |
| 9 | 2017 | 70 | |
| 10 | 2016 | 58 | |
| 11 | 2009 | 54 | |
| 12 | 2013 | 53 | |
| 13 | 2014 | 49 | |
| 14 | 2018 | 48 | |
| 15 | 2020 | 47 | |
| 16 | 2021 | 47 | |
| 17 | 2022 | 46 | |
| 18 | 2015 | 46 | |
| 19 | 2011 | 45 | |
| 20 | 2022 | 42 |
About Hang Chang
Hang Chang is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology, Artificial Intelligence, Biophysics and Radiology, Nuclear Medicine and Imaging, having authored 104 papers that have together received 2.7k indexed citations. Recurring topics across this work include Cell Image Analysis Techniques (28 papers), AI in cancer detection (26 papers), Medical Image Segmentation Techniques (15 papers), Radiomics and Machine Learning in Medical Imaging (10 papers), Gut microbiota and health (9 papers), Digital Imaging for Blood Diseases (8 papers), Cancer Cells and Metastasis (7 papers) and Image Processing Techniques and Applications (4 papers). The work is most often cited by research in Biophysics (354 citations), Computer Vision and Pattern Recognition (719 citations), Artificial Intelligence (790 citations), Biological Psychiatry (39 citations) and Media Technology (156 citations). Hang Chang has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Bahram Parvin, Paul T. Spellman, Bahram Parvin, Jian‐Hua Mao, Ju Han, Antoine M. Snijders, Alexander D. Borowsky, Qing Yang, Weidong Cai and Yin Zhou. Their work appears in journals such as Scientific Reports, Environment International, International Journal of Computer Vision, Cancer Research and Journal of Geophysical Research Oceans.
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.