Xiaoming Zhou

568 total citations
24 papers, 323 citations indexed

About

Xiaoming Zhou is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Surgery. According to data from OpenAlex, Xiaoming Zhou has authored 24 papers receiving a total of 323 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Radiology, Nuclear Medicine and Imaging, 9 papers in Pulmonary and Respiratory Medicine and 5 papers in Surgery. Recurrent topics in Xiaoming Zhou's work include Radiomics and Machine Learning in Medical Imaging (16 papers), Gastric Cancer Management and Outcomes (6 papers) and MRI in cancer diagnosis (5 papers). Xiaoming Zhou is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (16 papers), Gastric Cancer Management and Outcomes (6 papers) and MRI in cancer diagnosis (5 papers). Xiaoming Zhou collaborates with scholars based in China, Canada and Spain. Xiaoming Zhou's co-authors include Yuanxiang Gao, Zhiming Li, Haiyang Yu, Ming Ni, Xuejun Liu, Yande Ren, Xuexi Zhang, Xin Wang, Jihua Liu and Fang Liu and has published in prestigious journals such as Journal of Clinical Oncology, Medical Physics and BioMed Research International.

In The Last Decade

Xiaoming Zhou

22 papers receiving 317 citations

Peers

Xiaoming Zhou
Stefan P. Haider United States
Giuseppe Corrias Italy
Khashayar Namdar Canada
Su Yeon Ko South Korea
Camilla Scapicchio Italy
Su Yeon Ahn South Korea
Zhiyong Xu China
Mohab M. Elmohr United States
Anselm Schulz Norway
Pavel Ryška Czechia
Stefan P. Haider United States
Xiaoming Zhou
Citations per year, relative to Xiaoming Zhou Xiaoming Zhou (= 1×) peers Stefan P. Haider

Countries citing papers authored by Xiaoming Zhou

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoming Zhou

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaoming Zhou

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoming Zhou. A scholar is included among the top collaborators of Xiaoming Zhou 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 Xiaoming Zhou. Xiaoming Zhou 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.
Gao, Song, et al.. (2025). MRI-based deep transfer learning models for predicting progesterone receptor expression in meningioma. Frontiers in Oncology. 15. 1517205–1517205.
2.
Jiang, Sheng, Wentao Xie, Wenjun Pan, et al.. (2024). CT-based radiomics model for predicting perineural invasion status in gastric cancer. Abdominal Radiology. 50(5). 1916–1926. 1 indexed citations
3.
Xie, Yuxin, Xiaoming Zhou, Xin Wang, et al.. (2024). Different radiomics models in predicting the malignant potential of small intestinal stromal tumors. European Journal of Radiology Open. 13. 100615–100615. 2 indexed citations
4.
Xiang, Le, et al.. (2024). SCADA Anomaly Detection Scheme Based on OCSVM-PSO. 1335–1340.
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Xie, Wentao, et al.. (2023). A virtual biopsy study of microsatellite instability in gastric cancer based on deep learning radiomics. Insights into Imaging. 14(1). 104–104. 8 indexed citations
8.
Zhang, Shuai, et al.. (2022). Radiomics nomogram for prediction of microvascular invasion in hepatocellular carcinoma based on MR imaging with Gd-EOB-DTPA. Frontiers in Oncology. 12. 1034519–1034519. 5 indexed citations
9.
Xie, Wentao, Xiaoming Zhou, Xianxiang Zhang, et al.. (2022). Quantitative Radiological Features and Deep Learning for the Non-Invasive Evaluation of Programmed Death Ligand 1 Expression Levels in Gastric Cancer Patients: A Digital Biopsy Study. Academic Radiology. 30(7). 1317–1328. 5 indexed citations
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Liu, Fang, Song Gao, Nan Li, et al.. (2021). Comparison of Radiomic Models Based on Different Machine Learning Methods for Predicting Intracerebral Hemorrhage Expansion. Clinical Neuroradiology. 32(1). 215–223. 13 indexed citations
12.
Li, Nan, et al.. (2020). CT texture analysis for the differentiation of papillary renal cell carcinoma subtypes. Abdominal Radiology. 45(11). 3860–3868. 7 indexed citations
13.
Wang, Jiachen, Tong Zhou, Jihua Liu, et al.. (2020). Application of 1H-MRS in end-stage renal disease with depression. BMC Nephrology. 21(1). 225–225. 8 indexed citations
14.
Ni, Ming, Xiaoming Zhou, Jingwei Liu, et al.. (2020). Prediction of the clinicopathological subtypes of breast cancer using a fisher discriminant analysis model based on radiomic features of diffusion-weighted MRI. BMC Cancer. 20(1). 1073–1073. 19 indexed citations
15.
Zheng, Longbo, Jilin Hu, Yuan Gao, et al.. (2020). Establishment and Applicability of a Diagnostic System for Advanced Gastric Cancer T Staging Based on a Faster Region-Based Convolutional Neural Network. Frontiers in Oncology. 10. 1238–1238. 13 indexed citations
16.
Ni, Ming, Xiaoming Zhou, Qian Lv, et al.. (2019). Radiomics models for diagnosing microvascular invasion in hepatocellular carcinoma: which model is the best model?. Cancer Imaging. 19(1). 60–60. 63 indexed citations
17.
Song, Shuangshuang, et al.. (2019). Hypervascular hepatic focal lesions on dynamic contrast-enhanced CT: preliminary data from arterial phase scans texture analysis for classification. Clinical Radiology. 74(8). 653.e11–653.e18. 14 indexed citations
18.
Zhou, Xiaoming, et al.. (2019). Differentiation Researches on the Meningioma Subtypes by Radiomics from Contrast-Enhanced Magnetic Resonance Imaging: A Preliminary Study. World Neurosurgery. 126. e646–e652. 38 indexed citations
19.
Wang, Gang, et al.. (2017). Multi-slice spiral computed tomography perfusion imaging technology differentiates benign and malignant solitary pulmonary nodules. Biomedical Research-tokyo. 28(10). 4605–4609. 4 indexed citations
20.
Li, Zhiming, Xin Wang, Haiyang Yu, et al.. (2017). Diagnostic Performance of Mammographic Texture Analysis in the Differential Diagnosis of Benign and Malignant Breast Tumors. Clinical Breast Cancer. 18(4). e621–e627. 49 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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