Ling Mao
Impact in
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- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
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- Lung Cancer Diagnosis and Treatment
- Occupational and environmental lung diseases
Papers in
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- Occupational and environmental lung diseases 6
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- Medical Image Segmentation Techniques 3
- Co-authors
- Xiwen Sun (5 shared papers)Pavan Annangi (2 shared papers)Aamir Raja (1 shared paper)Sheshadri Thiruvenkadam (1 shared paper)Hao Xu (1 shared paper)Yonghong Feng (4 shared papers)Yaodong Dai (1 shared paper)Wei Han (1 shared paper)
- Journals
- Frontiers in Medicine (2 papers)Apmis (1 paper)American Journal of Industrial Medicine (1 paper)BMC Pulmonary Medicine (1 paper)Clinical and Vaccine Immunology (1 paper)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Ling Mao
33 papers receiving 384 citations
Peers
Comparison fields: 5 of 87
- Radiology, Nuclear Medicine and Imaging 94
- Pulmonary and Respiratory Medicine 111
- Electrochemistry 17
- Infectious Diseases 38
- General Dentistry 3
Countries citing papers authored by Ling Mao
This map shows the geographic impact of Ling 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 Ling Mao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ling Mao more than expected).
Fields of papers citing papers by Ling Mao
This network shows the impact of papers produced by Ling 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 Ling Mao. The network helps show where Ling Mao may publish in the future.
Co-authors
The 25 scholars most cited alongside Ling 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 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 68 | |
| 2 | 2009 | 43 | |
| 3 | 2014 | 38 | |
| 4 | 2011 | 30 | |
| 5 | 2015 | 25 | |
| 6 | 2016 | 22 | |
| 7 | 2017 | 20 | |
| 8 | 2010 | 18 | |
| 9 | 2022 | 17 | |
| 10 | 2020 | 13 | |
| 11 | 2009 | 12 | |
| 12 | 2009 | 11 | |
| 13 | 2015 | 10 | |
| 14 | 2017 | 10 | |
| 15 | 2016 | 9 | |
| 16 | 2023 | 8 | |
| 17 | 2011 | 6 | |
| 18 | 2017 | 5 | |
| 19 | 2014 | 5 | |
| 20 | 2024 | 5 |
About Ling Mao
Ling Mao is a scholar working on Pulmonary and Respiratory Medicine, Computer Vision and Pattern Recognition, Molecular Biology, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 38 papers that have together received 398 indexed citations. Recurring topics across this work include Occupational and environmental lung diseases (6 papers), Medical Image Segmentation Techniques (3 papers), AI in cancer detection (3 papers), Immune Cell Function and Interaction (2 papers), COVID-19 diagnosis using AI (2 papers), Tuberculosis Research and Epidemiology (2 papers), Glycosylation and Glycoproteins Research (1 paper) and Sesquiterpenes and Asteraceae Studies (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (94 citations), Pulmonary and Respiratory Medicine (111 citations), Electrochemistry (17 citations), Infectious Diseases (38 citations) and General Dentistry (3 citations). Ling Mao has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Xiwen Sun, Pavan Annangi, Aamir Raja, Sheshadri Thiruvenkadam, Hao Xu, Yonghong Feng, Yaodong Dai, Wei Han, Da Chen and Bin Kang. Their work appears in journals such as Frontiers in Medicine, Apmis, American Journal of Industrial Medicine, BMC Pulmonary Medicine and Clinical and Vaccine Immunology.
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.