Mayun Chen
- Health Informatics top 10%
- Pharmacology top 10%
- Neurology top 10%
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- Pulmonary Hypertension Research and Treatments 8
- Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis 3
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- Medicinal Plants and Bioactive Compounds 5
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- COVID-19 diagnosis using AI 4
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- Cardiovascular, Neuropeptides, and Oxidative Stress Research 3
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- Antifungal resistance and susceptibility 3
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- Diet, Metabolism, and Disease 3
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- Immune Response and Inflammation 3
Mayun Chen
34 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 141
- Health Informatics 15
- Complementary and alternative medicine 67
- Pharmacology 71
- Neurology 66
- Pulmonary and Respiratory Medicine 247
Countries citing papers authored by Mayun Chen
This map shows the geographic impact of Mayun Chen'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 Mayun Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mayun Chen more than expected).
Fields of papers citing papers by Mayun Chen
This network shows the impact of papers produced by Mayun Chen. 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 Mayun Chen. The network helps show where Mayun Chen may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mayun Chen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 46 | |
| 2 | 2023 | 2 | |
| 3 | 2023 | 30 | |
| 4 | Directional mutation and crossover boosted ant colony optimization with application to COVID-19 X-ray image segmentationbreakdown → | 2022 | 162 |
| 5 | Multilevel threshold image segmentation for COVID-19 chest radiography: A framework using horizontal and vertical multiverse optimizationbreakdown → | 2022 | 137 |
| 6 | 2021 | 41 | |
| 7 | 2021 | 23 | |
| 8 | 2020 | 15 | |
| 9 | 2020 | 9 | |
| 10 | 2019 | 7 | |
| 11 | 2018 | 5 | |
| 12 | 2017 | 62 | |
| 13 | 2017 | 81 | |
| 14 | Disseminated non-tuberculous mycobacterial infection induced by localized acupuncture and infection: a report of four cases | 2017 | 2 |
| 15 | 2017 | 70 | |
| 16 | 2016 | 66 | |
| 17 | 2015 | 81 | |
| 18 | Clinical analysis of pulmonary cryptococcosis in non-HIV patients in south China. | 2015 | 31 |
| 19 | 2015 | 42 | |
| 20 | 2015 | 27 |
About Mayun Chen
Mayun Chen is a scholar working on Physiology, Pulmonary and Respiratory Medicine and Neurology, having authored 34 papers that have together received 1.3k indexed citations. Recurring topics across this work include Pulmonary Hypertension Research and Treatments (8 papers), Medicinal Plants and Bioactive Compounds (5 papers), COVID-19 diagnosis using AI (4 papers), Cardiovascular, Neuropeptides, and Oxidative Stress Research (3 papers), Interstitial Lung Diseases and Idiopathic Pulmonary Fibrosis (3 papers), Antifungal resistance and susceptibility (3 papers), Diet, Metabolism, and Disease (3 papers) and Immune Response and Inflammation (3 papers). The work is most often cited by research in Health Informatics (15 citations), Complementary and alternative medicine (67 citations) and Pharmacology (71 citations). Mayun Chen has collaborated with scholars based in China, Singapore and Iran. Frequent co-authors include Liangxing Wang, Ali Asghar Heidari, Zhennao Cai, Xiaoying Huang, Huiling Chen, Dong Zhao, Zongda Wu, Peiliang Wu, Yanfan Chen and Xiaoying Huang. Their work appears in journals such as Computers in Biology and Medicine, Aging, BMC Pulmonary Medicine, IEEE Access and BMC Infectious Diseases.
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.