Jin-Ling Tang
Impact in
- Infectious Diseases top 2%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
- SARS-CoV-2 detection and testing
- Oncology top 5%
- Colorectal Cancer Treatments and Studies
- Lung Cancer Research Studies
Papers in
- Oncology 14
- Colorectal Cancer Treatments and Studies 7
- Co-authors
- Zu‐Yao YangChen MaoAllan HackshawXiaohong FuJoan K. MorrisYuelun ZhangJin-Qiu YuanSadie Boniface
- Journals
- Cochrane Database of Systematic Reviews (3 papers)EClinicalMedicine (3 papers)Scientific Reports (2 papers)BMJ evidence-based medicine (2 papers)Public Health (2 papers)
- Partner nations
- ChinaHong KongUnited Kingdom
In The Last Decade
Jin-Ling Tang
65 papers receiving 3.3k citations
Hit Papers
Peers
Comparison fields: 5 of 158
- Infectious Diseases 906
- Oncology 870
- Pulmonary and Respiratory Medicine 927
- Obstetrics and Gynecology 186
- Modeling and Simulation 105
Countries citing papers authored by Jin-Ling Tang
This map shows the geographic impact of Jin-Ling Tang'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 Jin-Ling Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jin-Ling Tang more than expected).
Fields of papers citing papers by Jin-Ling Tang
This network shows the impact of papers produced by Jin-Ling Tang. 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 Jin-Ling Tang. The network helps show where Jin-Ling Tang may publish in the future.
Co-authors
The 25 scholars most cited alongside Jin-Ling Tang, 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 | 2025 | 4 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 1 | |
| 5 | 2024 | 7 | |
| 6 | 2024 | 3 | |
| 7 | Efficacy of SARS-CoV-2 vaccines and the dose–response relationship with three major antibodies: a systematic review and meta-analysis of randomised controlled trials Hit paper breakdown → | 2023 | 68 |
| 8 | 2023 | 4 | |
| 9 | 2022 | 1 | |
| 10 | 2021 | 5 | |
| 11 | 2020 | 15 | |
| 12 | 2016 | 19 | |
| 13 | 2016 | 8 | |
| 14 | 2015 | 5 | |
| 15 | 2015 | 32 | |
| 16 | 2012 | 22 | |
| 17 | 2011 | 9 | |
| 18 | 2009 | 12 | |
| 19 | 2006 | 192 | |
| 20 | 1995 | 51 |
About Jin-Ling Tang
Jin-Ling Tang is a scholar working on Modeling and Simulation, Oncology, Geriatrics and Gerontology, Finance and Complementary and alternative medicine, having authored 73 papers that have together received 3.4k indexed citations. Recurring topics across this work include Colorectal Cancer Treatments and Studies (7 papers), Lung Cancer Treatments and Mutations (6 papers), Health Systems, Economic Evaluations, Quality of Life (5 papers), SARS-CoV-2 and COVID-19 Research (5 papers), Healthcare Systems and Reforms (5 papers), Complementary and Alternative Medicine Studies (4 papers), Primary Care and Health Outcomes (4 papers) and COVID-19 Clinical Research Studies (4 papers). The work is most often cited by research in Infectious Diseases (906 citations), Oncology (870 citations), Pulmonary and Respiratory Medicine (927 citations), Obstetrics and Gynecology (186 citations) and Modeling and Simulation (105 citations). Jin-Ling Tang has collaborated with scholars based in China, Hong Kong and United Kingdom. Frequent co-authors include Zu‐Yao Yang, Chen Mao, Allan Hackshaw, Xiaohong Fu, Joan K. Morris, Yuelun Zhang, Jin-Qiu Yuan, Sadie Boniface, Dušan Milenković and Huiying Liang. Their work appears in journals such as Cochrane Database of Systematic Reviews, EClinicalMedicine, Scientific Reports, BMJ evidence-based medicine and Public Health.
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.