Mingyu Tan
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
Papers in
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- Lung Cancer Diagnosis and Treatment 6
- Lung Cancer Treatments and Mutations 3
- Radiation Therapy and Dosimetry 3
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- Radiomics and Machine Learning in Medical Imaging 6
- Effects of Radiation Exposure 3
- Co-authors
- Ming Li (7 shared papers)Weiling Ma (7 shared papers)Yingli Sun (5 shared papers)Liang Jin (5 shared papers)Pan Gao (2 shared papers)Wei Zhao (2 shared papers)Cheng Li (3 shared papers)Kaiming Kuang (3 shared papers)
- Journals
- Frontiers in Oncology (5 papers)Technology in Cancer Research & Treatment (2 papers)BJOG An International Journal of Obstetrics & Gynaecology (1 paper)Scientific Reports (1 paper)Radiation Oncology (1 paper)
- Partner nations
- ChinaGermanyUnited States
In The Last Decade
Mingyu Tan
17 papers receiving 330 citations
Peers
Comparison fields: 5 of 46
- Health Informatics 28
- Radiology, Nuclear Medicine and Imaging 238
- Pulmonary and Respiratory Medicine 175
- Biomedical Engineering 95
- Oral Surgery 13
Countries citing papers authored by Mingyu Tan
This map shows the geographic impact of Mingyu Tan'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 Mingyu Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingyu Tan more than expected).
Fields of papers citing papers by Mingyu Tan
This network shows the impact of papers produced by Mingyu Tan. 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 Mingyu Tan. The network helps show where Mingyu Tan may publish in the future.
Co-authors
The 25 scholars most cited alongside Mingyu Tan, 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 | 2020 | 113 | |
| 2 | 2020 | 98 | |
| 3 | 2020 | 38 | |
| 4 | 2022 | 18 | |
| 5 | 2021 | 15 | |
| 6 | 2022 | 13 | |
| 7 | 2021 | 12 | |
| 8 | 2023 | 6 | |
| 9 | 2021 | 4 | |
| 10 | 2022 | 4 | |
| 11 | 2023 | 4 | |
| 12 | 2024 | 2 | |
| 13 | 2024 | 2 | |
| 14 | 2022 | 2 | |
| 15 | 2024 | 1 | |
| 16 | 2024 | 1 | |
| 17 | 2024 | 1 | |
| 18 | 2025 | 0 |
About Mingyu Tan
Mingyu Tan is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Surgery, Otorhinolaryngology and Biomedical Engineering, having authored 18 papers that have together received 334 indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (6 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Effects of Radiation Exposure (3 papers), Head and Neck Cancer Studies (3 papers), Lung Cancer Treatments and Mutations (3 papers), Radiation Therapy and Dosimetry (3 papers), Endometrial and Cervical Cancer Treatments (2 papers) and Advanced X-ray and CT Imaging (2 papers). The work is most often cited by research in Health Informatics (28 citations), Radiology, Nuclear Medicine and Imaging (238 citations), Pulmonary and Respiratory Medicine (175 citations), Biomedical Engineering (95 citations) and Oral Surgery (13 citations). Mingyu Tan has collaborated with scholars based in China, Germany and United States. Frequent co-authors include Ming Li, Weiling Ma, Yingli Sun, Liang Jin, Pan Gao, Wei Zhao, Cheng Li, Kaiming Kuang, Pan Gao and Shaofeng Duan. Their work appears in journals such as Frontiers in Oncology, Technology in Cancer Research & Treatment, BJOG An International Journal of Obstetrics & Gynaecology, Scientific Reports and Radiation Oncology.
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.