Jin Cui
Impact in
- Neurology top 10%
- Neuroinflammation and Neurodegeneration Mechanisms
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- Neurogenesis and neuroplasticity mechanisms
Papers in
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- Radiomics and Machine Learning in Medical Imaging 7
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- Aortic Disease and Treatment Approaches 2
- Aortic aneurysm repair treatments 2
- Co-authors
- Maria K. Lehtinen (4 shared papers)Huixin Xu (2 shared papers)Frederick B. Shipley (2 shared papers)Neil Dani (1 shared paper)Mark L. Andermann (1 shared paper)Morgan L. Shannon (1 shared paper)Pei‐Yi Lin (1 shared paper)Ryann M. Fame (1 shared paper)
- Journals
- Neuro-Oncology (4 papers)Neuro-Oncology Advances (2 papers)Diabetic Medicine (1 paper)Frontiers in Oncology (1 paper)Trends in Neurosciences (1 paper)
- Partner nations
- United StatesChinaGermany
In The Last Decade
Jin Cui
21 papers receiving 343 citations
Peers
Comparison fields: 5 of 66
- Neurology 68
- Developmental Neuroscience 28
- Cellular and Molecular Neuroscience 96
- Biological Psychiatry 11
- Pediatrics, Perinatology and Child Health 54
Countries citing papers authored by Jin Cui
This map shows the geographic impact of Jin Cui'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 Cui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jin Cui more than expected).
Fields of papers citing papers by Jin Cui
This network shows the impact of papers produced by Jin Cui. 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 Cui. The network helps show where Jin Cui may publish in the future.
Co-authors
The 25 scholars most cited alongside Jin Cui, 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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 80 | |
| 2 | 2020 | 80 | |
| 3 | 2021 | 69 | |
| 4 | 2022 | 28 | |
| 5 | 2007 | 16 | |
| 6 | 2017 | 14 | |
| 7 | 2022 | 11 | |
| 8 | 2020 | 11 | |
| 9 | 2017 | 10 | |
| 10 | 2015 | 10 | |
| 11 | 2021 | 2 | |
| 12 | 2024 | 2 | |
| 13 | 2021 | 2 | |
| 14 | 2021 | 1 | |
| 15 | 2021 | 1 | |
| 16 | 2024 | 1 | |
| 17 | 2021 | 1 | |
| 18 | 2021 | 1 | |
| 19 | 2020 | 1 | |
| 20 | 2024 | 1 |
About Jin Cui
Jin Cui is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Neurology, Genetics and Pediatrics, Perinatology and Child Health, having authored 24 papers that have together received 343 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (7 papers), Brain Tumor Detection and Classification (4 papers), Glioma Diagnosis and Treatment (3 papers), Aortic Disease and Treatment Approaches (2 papers), Neonatal and fetal brain pathology (2 papers), Neuroinflammation and Neurodegeneration Mechanisms (2 papers), Aortic aneurysm repair treatments (2 papers) and Artificial Intelligence in Healthcare and Education (2 papers). The work is most often cited by research in Neurology (68 citations), Developmental Neuroscience (28 citations), Cellular and Molecular Neuroscience (96 citations), Biological Psychiatry (11 citations) and Pediatrics, Perinatology and Child Health (54 citations). Jin Cui has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Maria K. Lehtinen, Huixin Xu, Frederick B. Shipley, Neil Dani, Mark L. Andermann, Morgan L. Shannon, Pei‐Yi Lin, Ryann M. Fame, Amanda Vernon and Christopher A. Naranjo. Their work appears in journals such as Neuro-Oncology, Neuro-Oncology Advances, Diabetic Medicine, Frontiers in Oncology and Trends in Neurosciences.
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.