Hang Chang

3.7k citations
98 papers · 2.4k · h-index 30

Impact in

Papers in

Hang Chang

96 papers receiving 2.4k citations

Peers

Hang Chang
Comparison fields: 5 of 160
  • Biophysics 338
  • Computer Vision and Pattern Recognition 651
  • Artificial Intelligence 720
  • Biological Psychiatry 44
  • Media Technology 147
Replace Yoshihiko Hamamoto with:
Yoshihiko Hamamoto Japan
Terry E. Weymouth United States
Constantino Carlos Reyes‐Aldasoro United Kingdom
Jun Sese Japan
Nektarios A. Valous Germany
Xi Peng China
Lu Fang China
Maode Lai China
Raghu Machiraju United States
Hang Chang relative to Yoshihiko Hamamoto Japan Yoshihiko Hamamoto's profile →
Citations per field
00.5×6.3×
Yoshihiko Hamamoto · 1×
Citations per year

Countries citing papers authored by Hang Chang

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 98 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020173
2 2012152
3 2013151
4 2007123
5 2017123
6 201481
7 202076
8 201273
9 201761
10 201652
11 200950
12 201347
13 201847
14 201446
15 202046
16 201544
17 202144
18 202243
19 201141
20 199440

About Hang Chang

Hang Chang is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Biophysics, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 98 papers that have together received 2.4k 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 (12 papers), Gut microbiota and health (10 papers), Cancer Cells and Metastasis (8 papers), Digital Imaging for Blood Diseases (7 papers) and Epigenetics and DNA Methylation (4 papers). The work is most often cited by research in Biophysics (338 citations), Computer Vision and Pattern Recognition (651 citations), Artificial Intelligence (720 citations), Biological Psychiatry (44 citations) and Media Technology (147 citations). Hang Chang has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Bahram Parvin, Bahram Parvin, Paul T. Spellman, Jian‐Hua Mao, Ju Han, Antoine M. Snijders, Alexander D. Borowsky, Qing Yang, Yin Zhou and Mary Helen Barcellos‐Hoff. Their work appears in journals such as Scientific Reports, Environment International, International Journal of Computer Vision, Journal of Geophysical Research Oceans and Medical Image Analysis.

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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