Jun Ni
Impact in
- Neurology top 1%
- Intracerebral and Subarachnoid Hemorrhage Research
- Intracranial Aneurysms: Treatment and Complications
- Neurological Disease Mechanisms and Treatments
- Cerebrovascular and genetic disorders
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- Cerebrovascular and Carotid Artery Diseases
Papers in
- Neurology 48
- Intracerebral and Subarachnoid Hemorrhage Research 23
- Cerebrovascular and genetic disorders 11
- Cerebral Venous Sinus Thrombosis 8
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- Cerebrovascular and Carotid Artery Diseases 18
- Co-authors
- Ming Yao (78 shared papers)Lixin Zhou (70 shared papers)Zhengyu Jin (42 shared papers)Mingli Li (34 shared papers)Bin Peng (34 shared papers)Yi‐Cheng Zhu (66 shared papers)Liying Cui (36 shared papers)Shan Gao (9 shared papers)
- Journals
- Neurology (9 papers)Frontiers in Neurology (9 papers)Journal of Alzheimer s Disease (8 papers)Stroke (7 papers)BMC Neurology (7 papers)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Jun Ni
166 papers receiving 2.9k citations
Peers
Comparison fields: 5 of 134
- Neurology 845
- Neurology 244
- Pulmonary and Respiratory Medicine 754
- Psychiatry and Mental health 246
- Epidemiology 506
Countries citing papers authored by Jun Ni
This map shows the geographic impact of Jun Ni'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 Jun Ni with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Ni more than expected).
Fields of papers citing papers by Jun Ni
This network shows the impact of papers produced by Jun Ni. 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 Jun Ni. The network helps show where Jun Ni may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Ni, 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 186 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 211 | |
| 2 | 2010 | 192 | |
| 3 | 2011 | 146 | |
| 4 | 2011 | 120 | |
| 5 | 2008 | 108 | |
| 6 | 2018 | 92 | |
| 7 | 2014 | 80 | |
| 8 | 2013 | 79 | |
| 9 | 2022 | 75 | |
| 10 | 2014 | 65 | |
| 11 | 2010 | 64 | |
| 12 | 2018 | 60 | |
| 13 | 2022 | 55 | |
| 14 | 2022 | 51 | |
| 15 | 2015 | 49 | |
| 16 | 2014 | 45 | |
| 17 | 2016 | 45 | |
| 18 | 2015 | 44 | |
| 19 | 2021 | 39 | |
| 20 | 2018 | 39 |
About Jun Ni
Jun Ni is a scholar working on Neurology, Pulmonary and Respiratory Medicine, Epidemiology, Rheumatology and Cellular and Molecular Neuroscience, having authored 186 papers that have together received 2.9k indexed citations. Recurring topics across this work include Acute Ischemic Stroke Management (27 papers), Intracerebral and Subarachnoid Hemorrhage Research (23 papers), Cerebrovascular and Carotid Artery Diseases (18 papers), Cerebrovascular and genetic disorders (11 papers), Advanced Neuroimaging Techniques and Applications (10 papers), Moyamoya disease diagnosis and treatment (9 papers), Cerebral Venous Sinus Thrombosis (8 papers) and Cardiovascular Health and Disease Prevention (8 papers). The work is most often cited by research in Neurology (845 citations), Neurology (244 citations), Pulmonary and Respiratory Medicine (754 citations), Psychiatry and Mental health (246 citations) and Epidemiology (506 citations). Jun Ni has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Ming Yao, Lixin Zhou, Zhengyu Jin, Mingli Li, Bin Peng, Yi‐Cheng Zhu, Liying Cui, Shan Gao, Liying Cui and Weihai Xu. Their work appears in journals such as Neurology, Frontiers in Neurology, Journal of Alzheimer s Disease, Stroke and BMC Neurology.
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.