Xin Zhen

2.0k citations
86 papers · 1.6k · 1 hit paper · h-index 22

Impact in

Papers in

Xin Zhen

77 papers receiving 1.6k citations

Xin Zhen's Hit Papers

Artificial intelligence-based models enabling accurate diagnosis of ovarian cancer using laboratory tests in China: a multicentre, retrospective cohort study 2024 · 53 citations
530+1Years since publication1020304050

Peers

Xin Zhen
Comparison fields: 5 of 113
  • Radiation 375
  • Radiology, Nuclear Medicine and Imaging 519
  • Health Informatics 32
  • Nephrology 84
  • Neurology 75
Replace Lei Ren with:
Lei Ren United States
Yi Luo United States
Yaping Wu China
Hamid Abdollahi Iran
Jiwoong Jeong United States
Wei Fan China
Xing Lv China
Ming Yang China
Ruixia Cui China
Mark J. Gooding United Kingdom
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Countries citing papers authored by Xin Zhen

Since Specialization
Citations

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

Fields of papers citing papers by Xin Zhen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 86 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017236
2 2017154
3 2017138
4 201975
5 201260
6 201954
7
Artificial intelligence-based models enabling accurate diagnosis of ovarian cancer using laboratory tests in China: a multicentre, retrospective cohort study
Hit paper breakdown →
202453
8 201749
9 201947
10 201336
11 201736
12 201835
13 201335
14 201433
15 201731
16 199927
17 202027
18 201726
19 201324
20 202124

About Xin Zhen

Xin Zhen is a scholar working on Radiation, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Artificial Intelligence and Pulmonary and Respiratory Medicine, having authored 86 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Radiotherapy Techniques (28 papers), Medical Imaging Techniques and Applications (20 papers), Radiomics and Machine Learning in Medical Imaging (18 papers), AI in cancer detection (10 papers), Advanced X-ray and CT Imaging (9 papers), Medical Image Segmentation Techniques (9 papers), MRI in cancer diagnosis (5 papers) and Digital Radiography and Breast Imaging (4 papers). The work is most often cited by research in Radiation (375 citations), Radiology, Nuclear Medicine and Imaging (519 citations), Health Informatics (32 citations), Nephrology (84 citations) and Neurology (75 citations). Xin Zhen has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Linghong Zhou, Xuejun Gu, Steve B Jiang, Xun Jia, Jing Nie, Brian A. Hrycushko, Hao Yan, Zichun Zhong, Kevin Albuquerque and Mu-Xuan Chen. Their work appears in journals such as Medical Physics, Physics in Medicine and Biology, Frontiers in Oncology, Expert Systems with Applications 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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