Xiaokai Mo
Impact in
- Otorhinolaryngology top 1%
- Head and Neck Cancer Studies
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- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- Medical Imaging Techniques and Applications
Papers in
-
- Radiomics and Machine Learning in Medical Imaging 20
- MRI in cancer diagnosis 8
- Medical Imaging Techniques and Applications 3
- Co-authors
- Shuixing Zhang (35 shared papers)Bin Zhang (30 shared papers)Yuhao Dong (21 shared papers)Lu Zhang (14 shared papers)Wenhui Huang (13 shared papers)Jie Tian (7 shared papers)Fusheng Ouyang (11 shared papers)Shufang Pei (13 shared papers)
In The Last Decade
Xiaokai Mo
33 papers receiving 1.6k citations
Xiaokai Mo's Hit Papers
Peers
Comparison fields: 5 of 85
- Otorhinolaryngology 350
- Radiology, Nuclear Medicine and Imaging 1.2k
- Health Informatics 62
- Pulmonary and Respiratory Medicine 415
- Genetics 130
Countries citing papers authored by Xiaokai Mo
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
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-authors
The 25 scholars most cited alongside Xiaokai Mo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Radiomics Features of Multiparametric MRI as Novel Prognostic Factors in Advanced Nasopharyngeal Carcinoma Hit paper breakdown → | 2017 | 389 |
| 2 | 2017 | 204 | |
| 3 | 2017 | 197 | |
| 4 | 2019 | 105 | |
| 5 | 2019 | 78 | |
| 6 | 2021 | 71 | |
| 7 | 2017 | 57 | |
| 8 | 2020 | 51 | |
| 9 | 2021 | 47 | |
| 10 | 2018 | 42 | |
| 11 | 2019 | 41 | |
| 12 | 2019 | 40 | |
| 13 | 2017 | 37 | |
| 14 | 2020 | 34 | |
| 15 | 2020 | 25 | |
| 16 | 2022 | 20 | |
| 17 | 2019 | 20 | |
| 18 | 2019 | 15 | |
| 19 | 2021 | 15 | |
| 20 | 2018 | 15 |
About Xiaokai Mo
Xiaokai Mo is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Surgery, Otorhinolaryngology and Oncology, having authored 37 papers that have together received 1.6k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (20 papers), Head and Neck Cancer Studies (9 papers), MRI in cancer diagnosis (8 papers), Pancreatic and Hepatic Oncology Research (4 papers), Glioma Diagnosis and Treatment (4 papers), Medical Imaging Techniques and Applications (3 papers), Ocular Oncology and Treatments (3 papers) and Cancer Immunotherapy and Biomarkers (3 papers). The work is most often cited by research in Otorhinolaryngology (350 citations), Radiology, Nuclear Medicine and Imaging (1.2k citations), Health Informatics (62 citations), Pulmonary and Respiratory Medicine (415 citations) and Genetics (130 citations). Xiaokai Mo has collaborated with scholars based in China and Hong Kong. Frequent co-authors include Shuixing Zhang, Bin Zhang, Yuhao Dong, Lu Zhang, Wenhui Huang, Jie Tian, Fusheng Ouyang, Shufang Pei, Zhouyang Lian and Dongsheng Gu. Their work appears in journals such as BMC Cancer, European Radiology, Oncotarget, Journal of Cancer and 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.