Tianfa Dong
Impact in
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- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
- Immunotherapy and Immune Responses
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- CAR-T cell therapy research
- Cancer Immunotherapy and Biomarkers
Papers in
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- Radiomics and Machine Learning in Medical Imaging 4
- MRI in cancer diagnosis 3
- Advanced Neuroimaging Techniques and Applications 1
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- Endometrial and Cervical Cancer Treatments 3
- Co-authors
- Ting Song (3 shared papers)Bo Yang (1 shared paper)Wenjun Chen (1 shared paper)Yaoshu Teng (1 shared paper)Xuehu Xu (1 shared paper)Jinshan Zhang (1 shared paper)Hanzhen Xiong (1 shared paper)Weixiang Liang (1 shared paper)
- Journals
- European Radiology (2 papers)Molecular Therapy (1 paper)Frontiers in Oncology (1 paper)BMC Pregnancy and Childbirth (1 paper)Magnetic Resonance Imaging (1 paper)
- Partner nations
- China
In The Last Decade
Tianfa Dong
12 papers receiving 399 citations
Peers
Comparison fields: 5 of 56
- Immunology 183
- Oncology 207
- Radiology, Nuclear Medicine and Imaging 93
- Pathology and Forensic Medicine 63
- Orthopedics and Sports Medicine 22
Countries citing papers authored by Tianfa Dong
This map shows the geographic impact of Tianfa Dong'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 Tianfa Dong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tianfa Dong more than expected).
Fields of papers citing papers by Tianfa Dong
This network shows the impact of papers produced by Tianfa Dong. 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 Tianfa Dong. The network helps show where Tianfa Dong may publish in the future.
Co-authors
The 25 scholars most cited alongside Tianfa Dong, 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 | 2019 | 234 | |
| 2 | 2010 | 102 | |
| 3 | 2022 | 21 | |
| 4 | 2019 | 17 | |
| 5 | 2019 | 10 | |
| 6 | 2022 | 4 | |
| 7 | 2021 | 4 | |
| 8 | 2022 | 3 | |
| 9 | 2024 | 3 | |
| 10 | 2021 | 2 | |
| 11 | 2023 | 2 | |
| 12 | 2025 | 1 |
About Tianfa Dong
Tianfa Dong is a scholar working on Radiology, Nuclear Medicine and Imaging, Obstetrics and Gynecology, Surgery, Pathology and Forensic Medicine and Orthopedics and Sports Medicine, having authored 12 papers that have together received 403 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (4 papers), MRI in cancer diagnosis (3 papers), Endometrial and Cervical Cancer Treatments (3 papers), Bone and Joint Diseases (3 papers), AI in cancer detection (2 papers), Pelvic and Acetabular Injuries (2 papers), Breast Lesions and Carcinomas (2 papers) and Advanced Neuroimaging Techniques and Applications (1 paper). The work is most often cited by research in Immunology (183 citations), Oncology (207 citations), Radiology, Nuclear Medicine and Imaging (93 citations), Pathology and Forensic Medicine (63 citations) and Orthopedics and Sports Medicine (22 citations). Tianfa Dong has collaborated with scholars based in China. Frequent co-authors include Ting Song, Bo Yang, Wenjun Chen, Yaoshu Teng, Xuehu Xu, Jinshan Zhang, Hanzhen Xiong, Weixiang Liang, Xuejuan Liu and Yan Sun. Their work appears in journals such as European Radiology, Molecular Therapy, Frontiers in Oncology, BMC Pregnancy and Childbirth and Magnetic Resonance Imaging.
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.