Hang Chang

3.7k total citations
98 papers, 2.4k citations indexed

About

Hang Chang is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition and Biophysics. According to data from OpenAlex, Hang Chang has authored 98 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Molecular Biology, 30 papers in Computer Vision and Pattern Recognition and 29 papers in Biophysics. Recurrent topics in Hang Chang's work include Cell Image Analysis Techniques (28 papers), AI in cancer detection (26 papers) and Medical Image Segmentation Techniques (15 papers). Hang Chang is often cited by papers focused on Cell Image Analysis Techniques (28 papers), AI in cancer detection (26 papers) and Medical Image Segmentation Techniques (15 papers). Hang Chang collaborates with scholars based in United States, China and Australia. Hang Chang's 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 and has published in prestigious journals such as Environmental Science & Technology, Bioinformatics and PLoS ONE.

In The Last Decade

Hang Chang

96 papers receiving 2.4k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hang Chang United States 30 720 661 651 383 340 98 2.4k
Constantino Carlos Reyes‐Aldasoro United Kingdom 24 670 0.9× 514 0.8× 377 0.6× 405 1.1× 632 1.9× 99 2.6k
Maode Lai China 28 904 1.3× 873 1.3× 620 1.0× 882 2.3× 642 1.9× 77 3.2k
Yoshihiko Hamamoto Japan 27 329 0.5× 889 1.3× 400 0.6× 329 0.9× 137 0.4× 126 2.9k
Raghu Machiraju United States 27 286 0.4× 464 0.7× 1.0k 1.5× 116 0.3× 164 0.5× 143 2.4k
Jun Sese Japan 27 518 0.7× 1.9k 2.9× 280 0.4× 200 0.5× 241 0.7× 82 3.6k
Laura E. Boucheron United States 12 1.2k 1.7× 174 0.3× 844 1.3× 208 0.5× 552 1.6× 40 1.8k
Noriaki Hashimoto Japan 23 282 0.4× 575 0.9× 204 0.3× 254 0.7× 167 0.5× 191 2.4k
Xiao Han China 25 738 1.0× 185 0.3× 350 0.5× 251 0.7× 660 1.9× 145 1.9k

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-authorship network of co-authors of Hang Chang

This figure shows the co-authorship network connecting the top 25 collaborators of Hang Chang. A scholar is included among the top collaborators of Hang 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 Hang Chang. Hang Chang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Jiang, Chengfei, Lingyan Chen, Suzaynn F. Schick, et al.. (2024). Thirdhand smoke exposure promotes gastric tumor development in mouse and human. Environment International. 191. 108986–108986. 1 indexed citations
3.
Inman, Jamie L., Liang Chen, Kenneth H. Wan, et al.. (2024). Long-term, non-invasive FTIR detection of low-dose ionizing radiation exposure. Scientific Reports. 14(1). 6119–6119. 4 indexed citations
4.
Wang, Xinzhi, Qianqian Xu, Yuqi Pan, et al.. (2024). NQO1 Triggers Neutrophil Recruitment and NET Formation to Drive Lung Metastasis of Invasive Breast Cancer. Cancer Research. 84(21). 3538–3555. 12 indexed citations
5.
Yang, Hui, Xinzhi Wang, Adrián Blanco‐Gómez, et al.. (2024). A susceptibility gene signature for ERBB2-driven mammary tumour development and metastasis in collaborative cross mice. EBioMedicine. 106. 105260–105260. 2 indexed citations
6.
Liu, Xiaoping, et al.. (2022). Development and validation of chest CT-based imaging biomarkers for early stage COVID-19 screening. Frontiers in Public Health. 10. 1004117–1004117. 1 indexed citations
7.
Mao, Aiqin, et al.. (2021). Identification of a novel cancer microbiome signature for predicting prognosis of human breast cancer patients. Clinical & Translational Oncology. 24(3). 597–604. 14 indexed citations
8.
Jin, Xiaoqing, S Celniker, Yankai Xia, et al.. (2021). Gut microbiome partially mediates and coordinates the effects of genetics on anxiety-like behavior in Collaborative Cross mice. Scientific Reports. 11(1). 270–270. 27 indexed citations
9.
Li, He, Pin Wang, Peyton Jacob, et al.. (2021). Genetic background influences the effect of thirdhand smoke exposure on anxiety and memory in Collaborative Cross mice. Scientific Reports. 11(1). 13285–13285. 7 indexed citations
10.
Chang, Hang, Zhenhua Xu, Baoshu Yin, et al.. (2019). Generation and Propagation of M2 Internal Tides Modulated by the Kuroshio Northeast of Taiwan. Journal of Geophysical Research Oceans. 124(4). 2728–2749. 28 indexed citations
11.
Lohr, James B., Hang Chang, Michelle Sexton, & Barton W. Palmer. (2019). Allostatic load and the cannabinoid system: implications for the treatment of physiological abnormalities in post-traumatic stress disorder (PTSD). CNS Spectrums. 25(6). 743–749. 7 indexed citations
12.
Vatter, Fanny A. Pelissier, Denis Schapiro, Hang Chang, et al.. (2018). High-Dimensional Phenotyping Identifies Age-Emergent Cells in Human Mammary Epithelia. Cell Reports. 23(4). 1205–1219. 32 indexed citations
13.
Tareef, Afaf, Yang Song, Weidong Cai, et al.. (2016). Automatic segmentation of overlapping cervical smear cells based on local distinctive features and guided shape deformation. Neurocomputing. 221. 94–107. 52 indexed citations
14.
Cheng, Qingsu, Gerald Fontenay, Hang Chang, et al.. (2016). Stiffness of the microenvironment upregulates ERBB2 expression in 3D cultures of MCF10A within the range of mammographic density. Scientific Reports. 6(1). 28987–28987. 17 indexed citations
15.
Fontenay, Gerald, et al.. (2016). BioSig3D: High Content Screening of Three-Dimensional Cell Culture Models. PLoS ONE. 11(3). e0148379–e0148379. 17 indexed citations
16.
Han, Ju, Gerald Fontenay, Yunfu Wang, Jian‐Hua Mao, & Hang Chang. (2016). Phenotypic characterization of breast invasive carcinoma via transferable tissue morphometric patterns learned from glioblastoma multiforme. PubMed. 113. 1025–1028.
17.
Zhou, Yin, Hang Chang, Kenneth E. Barner, & Bahram Parvin. (2015). Nuclei segmentation via sparsity constrained convolutional regression. PubMed. 2015. 1284–1287. 18 indexed citations
18.
Chang, Hang, Yin Zhou, Paul T. Spellman, & Bahram Parvin. (2013). Stacked Predictive Sparse Coding for Classification of Distinct Regions in Tumor Histopathology. PubMed. 169–176. 21 indexed citations
19.
DeFilippis, Rosa Anna, Hang Chang, Nancy Dumont, et al.. (2012). CD36 Repression Activates a Multicellular Stromal Program Shared by High Mammographic Density and Tumor Tissues. Cancer Discovery. 2(9). 826–839. 152 indexed citations
20.
Han, Junwei, et al.. (2010). Multiscale iterative voting for differential analysis of stress response for 2D and 3D cell culture models. Journal of Microscopy. 241(3). 315–326. 16 indexed citations

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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