Ning Mao
Impact in
-
- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- Health Informatics top 5%
Papers in
-
- Functional Brain Connectivity Studies 28
- EEG and Brain-Computer Interfaces 9
-
- Radiomics and Machine Learning in Medical Imaging 20
- Co-authors
- Haizhu Xie (34 shared papers)Heng Ma (25 shared papers)Chao Sun (5 shared papers)Shaofeng Duan (15 shared papers)Ping Yin (5 shared papers)Meijie Liu (10 shared papers)Ping Yin (6 shared papers)Jiangfen Wu (3 shared papers)
- Journals
- Journal of Magnetic Resonance Imaging (9 papers)Frontiers in Oncology (9 papers)European Radiology (6 papers)Academic Radiology (6 papers)Journal of X-Ray Science and Technology (5 papers)
- Partner nations
- ChinaUnited StatesSouth Korea
In The Last Decade
Ning Mao
131 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 130
- Radiology, Nuclear Medicine and Imaging 596
- Health Informatics 34
- Cognitive Neuroscience 194
- Health, Toxicology and Mutagenesis 120
- Artificial Intelligence 259
Countries citing papers authored by Ning Mao
This map shows the geographic impact of Ning Mao'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 Ning Mao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ning Mao more than expected).
Fields of papers citing papers by Ning Mao
This network shows the impact of papers produced by Ning Mao. 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 Ning Mao. The network helps show where Ning Mao may publish in the future.
Co-authors
The 25 scholars most cited alongside Ning Mao, 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 139 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 175 | |
| 2 | 2018 | 102 | |
| 3 | 2022 | 74 | |
| 4 | 2018 | 68 | |
| 5 | 2018 | 57 | |
| 6 | 2020 | 51 | |
| 7 | 2020 | 39 | |
| 8 | 2019 | 37 | |
| 9 | 2020 | 36 | |
| 10 | 2018 | 32 | |
| 11 | 2022 | 31 | |
| 12 | 2020 | 31 | |
| 13 | 2020 | 31 | |
| 14 | 2021 | 30 | |
| 15 | 2020 | 30 | |
| 16 | 2021 | 29 | |
| 17 | 2021 | 29 | |
| 18 | 2020 | 28 | |
| 19 | 2019 | 26 | |
| 20 | 2023 | 25 |
About Ning Mao
Ning Mao is a scholar working on Cognitive Neuroscience, Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Endocrinology, Diabetes and Metabolism and Artificial Intelligence, having authored 139 papers that have together received 1.9k indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (28 papers), Radiomics and Machine Learning in Medical Imaging (20 papers), Thyroid Cancer Diagnosis and Treatment (10 papers), EEG and Brain-Computer Interfaces (9 papers), Lung Cancer Diagnosis and Treatment (7 papers), AI in cancer detection (6 papers), Breast Cancer Treatment Studies (5 papers) and Digital Radiography and Breast Imaging (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (596 citations), Health Informatics (34 citations), Cognitive Neuroscience (194 citations), Health, Toxicology and Mutagenesis (120 citations) and Artificial Intelligence (259 citations). Ning Mao has collaborated with scholars based in China, United States and South Korea. Frequent co-authors include Haizhu Xie, Heng Ma, Chao Sun, Shaofeng Duan, Ping Yin, Meijie Liu, Ping Yin, Jiangfen Wu, Ying–Hong Shi and Haicheng Zhang. Their work appears in journals such as Journal of Magnetic Resonance Imaging, Frontiers in Oncology, European Radiology, Academic Radiology and Journal of X-Ray Science and Technology.
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.