Yehang Chen

579 citations
26 papers · 382 · h-index 10

Impact in

Papers in

Yehang Chen

23 papers receiving 379 citations

Peers

Yehang Chen
Comparison fields: 5 of 49
  • Radiology, Nuclear Medicine and Imaging 318
  • Health Informatics 14
  • Pulmonary and Respiratory Medicine 174
  • Artificial Intelligence 76
  • Biomedical Engineering 81
Replace Bao Feng with:
Bao Feng China
Camilla Scapicchio Italy
Koichiro Kimura Japan
Zhuangsheng Liu China
Juebin Jin China
Yao Ai China
L Hunter United States
Yunfeng Cui United States
Ruimei Chai China
Lifang Pang China
Yehang Chen relative to Bao Feng China Bao Feng's profile →
Citations per field
00.5×1.5×
Bao Feng · 1×
Citations per year

Countries citing papers authored by Yehang Chen

Since Specialization
Citations

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

Fields of papers citing papers by Yehang Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201978
2 202050
3 202048
4 202035
5 202425
6 202223
7 202017
8 202113
9 202011
10 20239
11 20209
12 20238
13 20238
14 20227
15 20217
16 20207
17 20196
18 20226
19 20255
20 20244

About Yehang Chen

Yehang Chen is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Artificial Intelligence, Biomedical Engineering and Oncology, having authored 26 papers that have together received 382 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (21 papers), Lung Cancer Diagnosis and Treatment (8 papers), Advanced X-ray and CT Imaging (4 papers), AI in cancer detection (4 papers), Gastric Cancer Management and Outcomes (4 papers), MRI in cancer diagnosis (3 papers), COVID-19 diagnosis using AI (2 papers) and Medical Imaging Techniques and Applications (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (318 citations), Health Informatics (14 citations), Pulmonary and Respiratory Medicine (174 citations), Artificial Intelligence (76 citations) and Biomedical Engineering (81 citations). Yehang Chen has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Wansheng Long, Bao Feng, Xiangmeng Chen, Zhuangsheng Liu, Ronggang Li, Enming Cui, Kunwei Li, Zhi Li, Kunfeng Liu and Xueguo Liu. Their work appears in journals such as European Radiology, Frontiers in Oncology, Cancer Imaging, Nature Communications and European Journal of 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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