Sufang Tian
- Infectious Diseases top 1%
- SARS-CoV-2 and COVID-19 Research 3
- Neurology top 2%
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- Radiomics and Machine Learning in Medical Imaging 4
- Oncology top 10%
- Viral-associated cancers and disorders 4
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- Lung Cancer Diagnosis and Treatment 5
- Lung Cancer Treatments and Mutations 5
- Ferroptosis and cancer prognosis 4
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- Lymphoma Diagnosis and Treatment 5
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- Glioma Diagnosis and Treatment 3
- Co-authors
- Shu‐Yuan XiaoLi NiuHuan LiuWeidong HuHaibo XuMeiyan LiaoYong XiongJianchun Guo
- Journals
- FEBS Letters (1 paper)Archives of Biochemistry and Biophysics (1 paper)The American Journal of Surgical Pathology (1 paper)
- Partner nations
- ChinaUnited StatesNetherlands
In The Last Decade
Sufang Tian
40 papers receiving 1.9k citations
Hit Papers
Peers
Comparison fields: 5 of 110
- Infectious Diseases 1.3k
- Neurology 633
- Critical Care and Intensive Care Medicine 117
- Radiology, Nuclear Medicine and Imaging 307
- Oncology 357
Countries citing papers authored by Sufang Tian
This map shows the geographic impact of Sufang Tian'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 Sufang Tian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sufang Tian more than expected).
Fields of papers citing papers by Sufang Tian
This network shows the impact of papers produced by Sufang Tian. 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 Sufang Tian. The network helps show where Sufang Tian may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Sufang Tian, 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 | 2025 | 0 | |
| 2 | 2024 | 10 | |
| 3 | 2024 | 5 | |
| 4 | 2024 | 3 | |
| 5 | 2023 | 2 | |
| 6 | 2022 | 1 | |
| 7 | 2022 | 1 | |
| 8 | 2021 | 8 | |
| 9 | 2020 | 24 | |
| 10 | 2020 | 1 | |
| 11 | Pathological study of the 2019 novel coronavirus disease (COVID-19) through postmortem core biopsiesbreakdown → | 2020 | 645 |
| 12 | Pulmonary Pathology of Early-Phase 2019 Novel Coronavirus (COVID-19) Pneumonia in Two Patients With Lung Cancerbreakdown → | 2020 | 989 |
| 13 | 2020 | 1 | |
| 14 | 2019 | 21 | |
| 15 | 2019 | 5 | |
| 16 | 2018 | 18 | |
| 17 | 2018 | 4 | |
| 18 | 2008 | 5 | |
| 19 | 2005 | 22 | |
| 20 | Expressions of VEGF and MMP-2 in gastric adenocarcinoma and their involvment in tumor invasion and metastasis | 2004 | 1 |
About Sufang Tian
Sufang Tian is a scholar working on Pathology and Forensic Medicine, Cancer Research and Oncology, having authored 41 papers that have together received 2.0k indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (5 papers), Lung Cancer Treatments and Mutations (5 papers), Lymphoma Diagnosis and Treatment (5 papers), Ferroptosis and cancer prognosis (4 papers), Viral-associated cancers and disorders (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), SARS-CoV-2 and COVID-19 Research (3 papers) and Glioma Diagnosis and Treatment (3 papers). The work is most often cited by research in Infectious Diseases (1.3k citations), Neurology (633 citations) and Critical Care and Intensive Care Medicine (117 citations). Sufang Tian has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Shu‐Yuan Xiao, Li Niu, Huan Liu, Weidong Hu, Haibo Xu, Meiyan Liao, Yong Xiong, Jianchun Guo, Huan Liu and Hanfei Zhang. Their work appears in journals such as FEBS Letters, Archives of Biochemistry and Biophysics and The American Journal of Surgical Pathology.
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.