Yanlin Tan
Impact in
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- Artificial Intelligence in Healthcare
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- Spine and Intervertebral Disc Pathology 12
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- Radiomics and Machine Learning in Medical Imaging 10
- Medical Imaging Techniques and Applications 2
- Co-authors
- Jia Wu (13 shared papers)Zhigang Chen (6 shared papers)Fangfang Gou (3 shared papers)Genghua Yu (3 shared papers)Ming Zhao (2 shared papers)Bayan Aghdasi (10 shared papers)Hirokazu Inoue (8 shared papers)Scott R. Montgomery (8 shared papers)
- Journals
- The Spine Journal (3 papers)Medicine (2 papers)Spine (2 papers)IEEE Journal of Biomedical and Health Informatics (2 papers)IEEE Access (2 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Yanlin Tan
34 papers receiving 638 citations
Peers
Comparison fields: 5 of 95
- Health Information Management 47
- Radiology, Nuclear Medicine and Imaging 210
- Health Informatics 13
- Computer Vision and Pattern Recognition 131
- Pathology and Forensic Medicine 102
Countries citing papers authored by Yanlin Tan
This map shows the geographic impact of Yanlin 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 Yanlin Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yanlin Tan more than expected).
Fields of papers citing papers by Yanlin Tan
This network shows the impact of papers produced by Yanlin 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 Yanlin Tan. The network helps show where Yanlin Tan may publish in the future.
Co-authors
The 25 scholars most cited alongside Yanlin 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
Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 56 | |
| 2 | 2018 | 46 | |
| 3 | 2019 | 45 | |
| 4 | 2018 | 40 | |
| 5 | 2021 | 35 | |
| 6 | 2021 | 34 | |
| 7 | 2012 | 34 | |
| 8 | 2020 | 31 | |
| 9 | 2023 | 28 | |
| 10 | 2022 | 27 | |
| 11 | 2012 | 25 | |
| 12 | 2018 | 25 | |
| 13 | 2023 | 24 | |
| 14 | 2018 | 20 | |
| 15 | 2020 | 18 | |
| 16 | 2013 | 18 | |
| 17 | 2021 | 17 | |
| 18 | 2014 | 16 | |
| 19 | 2018 | 14 | |
| 20 | 2019 | 14 |
About Yanlin Tan
Yanlin Tan is a scholar working on Pathology and Forensic Medicine, Radiology, Nuclear Medicine and Imaging, Surgery, Artificial Intelligence and Health Information Management, having authored 37 papers that have together received 642 indexed citations. Recurring topics across this work include Spine and Intervertebral Disc Pathology (12 papers), Radiomics and Machine Learning in Medical Imaging (10 papers), AI in cancer detection (8 papers), Artificial Intelligence in Healthcare (6 papers), Cervical and Thoracic Myelopathy (5 papers), Musculoskeletal pain and rehabilitation (5 papers), Lung Cancer Diagnosis and Treatment (4 papers) and Medical Imaging Techniques and Applications (2 papers). The work is most often cited by research in Health Information Management (47 citations), Radiology, Nuclear Medicine and Imaging (210 citations), Health Informatics (13 citations), Computer Vision and Pattern Recognition (131 citations) and Pathology and Forensic Medicine (102 citations). Yanlin Tan has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Jia Wu, Zhigang Chen, Fangfang Gou, Genghua Yu, Ming Zhao, Bayan Aghdasi, Hirokazu Inoue, Scott R. Montgomery, Yunhua Wang and Jeffrey C. Wang. Their work appears in journals such as The Spine Journal, Medicine, Spine, IEEE Journal of Biomedical and Health Informatics and IEEE Access.
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.