Zhe Jin

907 total citations
37 papers, 525 citations indexed

About

Zhe Jin is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology and Surgery. According to data from OpenAlex, Zhe Jin has authored 37 papers receiving a total of 525 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Radiology, Nuclear Medicine and Imaging, 11 papers in Oncology and 10 papers in Surgery. Recurrent topics in Zhe Jin's work include Radiomics and Machine Learning in Medical Imaging (17 papers), MRI in cancer diagnosis (8 papers) and Colorectal Cancer Surgical Treatments (4 papers). Zhe Jin is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (17 papers), MRI in cancer diagnosis (8 papers) and Colorectal Cancer Surgical Treatments (4 papers). Zhe Jin collaborates with scholars based in China, United States and France. Zhe Jin's co-authors include Shuixing Zhang, Qiuying Chen, Jingjing You, Bin Zhang, Lu Zhang, Shuyi Liu, Xiaokai Mo, Bin Zhang, Luyan Chen and Fang Jin and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Journal of Medicinal Chemistry.

In The Last Decade

Zhe Jin

33 papers receiving 521 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zhe Jin China 14 283 185 161 88 62 37 525
Colton Ladbury United States 11 177 0.6× 164 0.9× 185 1.1× 54 0.6× 40 0.6× 67 461
Seung Yeun Chung South Korea 14 194 0.7× 155 0.8× 159 1.0× 67 0.8× 30 0.5× 31 537
M. Fang China 4 408 1.4× 158 0.9× 363 2.3× 130 1.5× 54 0.9× 7 620
Amir H. Khandani United States 18 305 1.1× 215 1.2× 377 2.3× 82 0.9× 104 1.7× 59 759
Pierpaolo Pastina Italy 17 165 0.6× 319 1.7× 211 1.3× 69 0.8× 93 1.5× 39 599
Qingtao Qiu China 16 495 1.7× 134 0.7× 273 1.7× 97 1.1× 27 0.4× 51 614
Wanhu Li China 12 216 0.8× 137 0.7× 184 1.1× 93 1.1× 83 1.3× 24 474
Nalee Kim South Korea 17 293 1.0× 248 1.3× 242 1.5× 174 2.0× 53 0.9× 76 884
Gokoulakrichenane Loganadane France 10 147 0.5× 126 0.7× 164 1.0× 76 0.9× 17 0.3× 39 374
Anup Vinayan United Kingdom 6 329 1.2× 103 0.6× 247 1.5× 49 0.6× 72 1.2× 10 456

Countries citing papers authored by Zhe Jin

Since Specialization
Citations

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

Fields of papers citing papers by Zhe Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhe Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Zhe Jin. A scholar is included among the top collaborators of Zhe Jin 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 Zhe Jin. Zhe Jin 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.
Wu, Xuewei, Zhe Jin, Jie Sun, et al.. (2025). Generative artificial intelligence in medical imaging: Current landscape, challenges, and future directions. SHILAP Revista de lepidopterología. 3(4).
2.
3.
Huang, Ling, Zhe Jin, Xin Yue, et al.. (2025). Artificial Intelligence Can Predict Personalized Immunotherapy Outcomes in Cancer. Cancer Immunology Research. 13(7). 964–977. 2 indexed citations
4.
Mo, Xiaokai, Fang Jin, Bin Zhang, et al.. (2025). Use of virtual simulation-based training platform on thyroid ultrasonography in medical students: a randomized controlled trial. Computers in Biology and Medicine. 197(Pt A). 110999–110999.
5.
6.
7.
Wu, Xuewei, Shuaitong Zhang, Zhenyu Zhang, et al.. (2024). Biologically interpretable multi-task deep learning pipeline predicts molecular alterations, grade, and prognosis in glioma patients. npj Precision Oncology. 8(1). 181–181. 10 indexed citations
8.
Chen, Qiuying, Jue Yang, Zhe Jin, et al.. (2024). PO‐AKID‐teller: An interpretable machine learning tool for predicting acute kidney injury requiring dialysis after acute type A aortic dissection surgery. SHILAP Revista de lepidopterología. 3(1). 1 indexed citations
9.
Zhang, Bin, Lu Zhang, Qiuying Chen, et al.. (2023). Harnessing artificial intelligence to improve clinical trial design. SHILAP Revista de lepidopterología. 3(1). 191–191. 29 indexed citations
10.
Jin, Zhe, Shufang Pei, Hui Shen, et al.. (2023). Comparative Study of C-TIRADS, ACR-TIRADS, and EU-TIRADS for Diagnosis and Management of Thyroid Nodules. Academic Radiology. 30(10). 2181–2191. 13 indexed citations
11.
Zhang, Bin, Xiao Zhang, Jing Hou, et al.. (2023). Integrative Scoring System for Survival Prediction in Patients With Locally Advanced Nasopharyngeal Carcinoma: A Retrospective Multicenter Study. JCO Clinical Cancer Informatics. 7(7). e2200015–e2200015. 3 indexed citations
12.
Mo, Xiaokai, Wenbo Chen, Simin Chen, et al.. (2023). MRI texture-based machine learning models for the evaluation of renal function on different segmentations: a proof-of-concept study. Insights into Imaging. 14(1). 28–28. 6 indexed citations
13.
Jin, Zhe, Shufang Pei, Lu Zhang, et al.. (2022). Thy‐Wise: An interpretable machine learning model for the evaluation of thyroid nodules. International Journal of Cancer. 151(12). 2229–2243. 11 indexed citations
14.
Wang, Yao, Zhe Jin, Qingcong Kong, et al.. (2022). Evaluation of the Effects of Anti‐PD‐1 Therapy on Triple‐Negative Breast Cancer in Mice by Diffusion Kurtosis Imaging and Dynamic Contrast‐Enhanced Imaging. Journal of Magnetic Resonance Imaging. 56(6). 1912–1923. 6 indexed citations
15.
16.
Li, Minmin, Bin Zhang, Qiuying Chen, et al.. (2021). Concurrent chemoradiotherapy with additional chemotherapy for nasopharyngeal carcinoma: A pooled analysis of propensity score‐matching studies. Head & Neck. 43(6). 1912–1927. 7 indexed citations
17.
Chen, Qiuying, Lu Zhang, Xiaokai Mo, et al.. (2021). Current status and quality of radiomic studies for predicting immunotherapy response and outcome in patients with non-small cell lung cancer: a systematic review and meta-analysis. European Journal of Nuclear Medicine and Molecular Imaging. 49(1). 345–360. 47 indexed citations
18.
Zhang, Lu, Xiangjun Wu, Jing Liu, et al.. (2020). MRI‐Based Deep‐Learning Model for Distant Metastasis‐Free Survival in Locoregionally Advanced Nasopharyngeal Carcinoma. Journal of Magnetic Resonance Imaging. 53(1). 167–178. 34 indexed citations
19.
Jin, Zhe, Bin Zhang, Lu Zhang, et al.. (2020). Immune-checkpoint inhibitor plus chemotherapy versus conventional chemotherapy for treatment of recurrent or metastatic head and neck squamous cell carcinoma: a systematic review and network meta-analysis. Therapeutic Advances in Medical Oncology. 12. 3863598757–3863598757. 10 indexed citations
20.
Guo, Yuan, Wenjie Tang, Qingcong Kong, et al.. (2019). Can whole-tumor apparent diffusion coefficient histogram analysis be helpful to evaluate breast phyllode tumor grades?. European Journal of Radiology. 114. 25–31. 14 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Colton Ladbury Breakdown of academic impact, for papers by Seung Yeun Chung Breakdown of academic impact, for papers by M. Fang Breakdown of academic impact, for papers by Amir H. Khandani Breakdown of academic impact, for papers by Pierpaolo Pastina Breakdown of academic impact, for papers by Qingtao Qiu Breakdown of academic impact, for papers by Wanhu Li Breakdown of academic impact, for papers by Nalee Kim Breakdown of academic impact, for papers by Gokoulakrichenane Loganadane Breakdown of academic impact, for papers by Anup Vinayan
Rankless by CCL
2026