Xiaokai Mo

2.2k total citations · 1 hit paper
37 papers, 1.6k citations indexed

About

Xiaokai Mo is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Surgery. According to data from OpenAlex, Xiaokai Mo has authored 37 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Radiology, Nuclear Medicine and Imaging, 11 papers in Pulmonary and Respiratory Medicine and 10 papers in Surgery. Recurrent topics in Xiaokai Mo's work include Radiomics and Machine Learning in Medical Imaging (20 papers), Head and Neck Cancer Studies (9 papers) and MRI in cancer diagnosis (8 papers). Xiaokai Mo is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (20 papers), Head and Neck Cancer Studies (9 papers) and MRI in cancer diagnosis (8 papers). Xiaokai Mo collaborates with scholars based in China and Hong Kong. Xiaokai Mo's co-authors include Shuixing Zhang, Bin Zhang, Yuhao Dong, Lu Zhang, Wenhui Huang, Jie Tian, Fusheng Ouyang, Shufang Pei, Dongsheng Gu and Zhouyang Lian and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Radiology.

In The Last Decade

Xiaokai Mo

33 papers receiving 1.6k citations

Hit Papers

Radiomics Features of Multiparametric MRI as Novel Progno... 2017 2026 2020 2023 2017 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Radiomics Features of Multiparametric MRI as Novel Prognostic Factors in Advanced Nasopharyngeal Carcinoma
    2017 389 citations Bin Zhang, Jie Tian et al. Clinical Cancer Research profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiaokai Mo China 17 1.2k 415 350 254 243 37 1.6k
Fusheng Ouyang China 13 836 0.7× 281 0.7× 268 0.8× 186 0.7× 125 0.5× 30 1.1k
Shufang Pei China 12 833 0.7× 212 0.5× 193 0.6× 134 0.5× 229 0.9× 23 1.0k
Hesham Elhalawani United States 21 627 0.5× 433 1.0× 251 0.7× 532 2.1× 130 0.5× 93 1.5k
Xiaoning Luo China 17 720 0.6× 304 0.7× 306 0.9× 243 1.0× 140 0.6× 53 1.3k
Zhouyang Lian China 14 780 0.6× 242 0.6× 233 0.7× 148 0.6× 149 0.6× 37 1.1k
Seung Hyup Hyun South Korea 26 1.3k 1.1× 903 2.2× 183 0.5× 496 2.0× 84 0.3× 79 2.2k
Connie Yip United Kingdom 13 1.4k 1.1× 654 1.6× 221 0.6× 576 2.3× 125 0.5× 33 2.2k
Sylvain Reuzé France 12 1.7k 1.4× 565 1.4× 55 0.2× 372 1.5× 232 1.0× 18 2.0k
Te‐Chun Hsieh Taiwan 20 628 0.5× 331 0.8× 149 0.4× 253 1.0× 77 0.3× 110 1.1k

Countries citing papers authored by Xiaokai Mo

Since Specialization
Citations

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

Fields of papers citing papers by Xiaokai Mo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaokai Mo

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaokai Mo. A scholar is included among the top collaborators of Xiaokai Mo 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 Xiaokai Mo. Xiaokai Mo 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.
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.
2.
Mo, Xiaokai, et al.. (2024). Multifocal Gorham-Stout disease in a thirteen-year-old boy with horseshoe kidney: A case report. SHILAP Revista de lepidopterología. 19(11). 5066–5070.
3.
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
4.
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
5.
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
6.
Yan, Jing, Bin Zhang, Shuaitong Zhang, et al.. (2021). Quantitative MRI-based radiomics for noninvasively predicting molecular subtypes and survival in glioma patients. npj Precision Oncology. 5(1). 71 indexed citations
7.
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
8.
Chen, Qiuying, Bin Zhang, Yuhao Dong, et al.. (2020). Evaluating primary intra-arterial chemotherapy versus intravenous plus intra-arterial chemotherapy for advanced intraocular retinoblastoma. Cancer Chemotherapy and Pharmacology. 85(4). 723–730. 7 indexed citations
9.
Zhang, Bin, Zhouyang Lian, Liming Zhong, et al.. (2020). Machine-learning based MRI radiomics models for early detection of radiation-induced brain injury in nasopharyngeal carcinoma. BMC Cancer. 20(1). 502–502. 51 indexed citations
10.
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
11.
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
12.
Chen, Qiuying, Bin Zhang, Yuhao Dong, et al.. (2019). Intra-arterial chemotherapy as primary or secondary treatment for infants diagnosed with advanced retinoblastoma before 3 months of age. BMC Cancer. 19(1). 693–693. 15 indexed citations
13.
Mo, Xiaokai, Xiangjun Wu, Di Dong, et al.. (2019). Prognostic value of the radiomics-based model in progression-free survival of hypopharyngeal cancer treated with chemoradiation. European Radiology. 30(2). 833–843. 40 indexed citations
14.
15.
Zhang, Bin, Jie Tian, Shufang Pei, et al.. (2019). Machine Learning–Assisted System for Thyroid Nodule Diagnosis. Thyroid. 29(6). 858–867. 105 indexed citations
16.
Chen, Qiuying, Bin Zhang, Yuhao Dong, et al.. (2018). Comparison between intravenous chemotherapy and intra-arterial chemotherapy for retinoblastoma: a meta-analysis. BMC Cancer. 18(1). 486–486. 42 indexed citations
17.
Zhang, Bin, Jie Tian, Di Dong, et al.. (2017). Radiomics Features of Multiparametric MRI as Novel Prognostic Factors in Advanced Nasopharyngeal Carcinoma. Clinical Cancer Research. 23(15). 4259–4269. 389 indexed citations breakdown →
18.
Zhang, Bin, Xin He, Fusheng Ouyang, et al.. (2017). Radiomic machine-learning classifiers for prognostic biomarkers of advanced nasopharyngeal carcinoma. Cancer Letters. 403. 21–27. 204 indexed citations
19.
Dong, Yuhao, Qianjin Feng, Wei Yang, et al.. (2017). Preoperative prediction of sentinel lymph node metastasis in breast cancer based on radiomics of T2-weighted fat-suppression and diffusion-weighted MRI. European Radiology. 28(2). 582–591. 197 indexed citations
20.

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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