Cai Chang

2.7k citations
84 papers · 1.4k · h-index 18

Impact in

Papers in

Cai Chang

78 papers receiving 1.4k citations

Peers

Cai Chang
Comparison fields: 5 of 89
  • Radiology, Nuclear Medicine and Imaging 536
  • Endocrinology, Diabetes and Metabolism 352
  • Health Informatics 26
  • Cancer Research 136
  • Artificial Intelligence 180
Replace Yu‐Mee Sohn with:
Yu‐Mee Sohn South Korea
Vivian Youngjean Park South Korea
Bong Joo Kang South Korea
Hye Mi Gweon South Korea
Mirinae Seo South Korea
Shufang Pei China
Xiaokai Mo China
Andrey Bychkov Japan
Olorunsola F. Agbaje United Kingdom
Cai Chang relative to Yu‐Mee Sohn South Korea Yu‐Mee Sohn's profile →
Citations per field
00.5×6.3×
Yu‐Mee Sohn · 1×
Citations per year

Countries citing papers authored by Cai Chang

Since Specialization
Citations

This map shows the geographic impact of Cai 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 Cai Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cai Chang more than expected).

Fields of papers citing papers by Cai Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cai 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 Cai Chang. The network helps show where Cai Chang may publish in the future.

Co-authors

The 25 scholars most cited alongside Cai 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 Cai Chang Line = papers co-authored together Cai Chang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 84 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020215
2 2014143
3 2017122
4 201986
5 202066
6 202057
7 202350
8 201837
9 202135
10 201534
11 201831
12 202229
13 202324
14 201523
15 201822
16 202020
17 201219
18 202218
19 201617
20 202017

About Cai Chang

Cai Chang is a scholar working on Radiology, Nuclear Medicine and Imaging, Endocrinology, Diabetes and Metabolism, Cancer Research, Biomedical Engineering and Artificial Intelligence, having authored 84 papers that have together received 1.4k indexed citations. Recurring topics across this work include Thyroid Cancer Diagnosis and Treatment (14 papers), Radiomics and Machine Learning in Medical Imaging (14 papers), Breast Cancer Treatment Studies (12 papers), AI in cancer detection (9 papers), Ultrasound Imaging and Elastography (8 papers), Breast Lesions and Carcinomas (6 papers), Photoacoustic and Ultrasonic Imaging (4 papers) and Nanoplatforms for cancer theranostics (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (536 citations), Endocrinology, Diabetes and Metabolism (352 citations), Health Informatics (26 citations), Cancer Research (136 citations) and Artificial Intelligence (180 citations). Cai Chang has collaborated with scholars based in China, United States and Finland. Frequent co-authors include Shichong Zhou, Yuanyuan Wang, Jinhua Yu, Jin Zhou, Yi Guo, Tongtong Liu, Jiawei Li, Yunxia Huang, Mengyun Qiao and Yinhui Deng. Their work appears in journals such as Journal of Ultrasound in Medicine, Frontiers in Oncology, Academic Radiology, Cancer Management and Research and European 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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