Jiatai Lin
Impact in
- Neurology top 10%
- Brain Tumor Detection and Classification
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- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
- Digital Imaging for Blood Diseases
Papers in
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- AI in cancer detection 10
- Machine Learning and ELM 4
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- Radiomics and Machine Learning in Medical Imaging 6
- COVID-19 diagnosis using AI 2
- Co-authors
- Chu Han (11 shared papers)Zaiyi Liu (11 shared papers)Xipeng Pan (6 shared papers)Zhenwei Shi (7 shared papers)Zhi Liu (5 shared papers)Bingchao Zhao (6 shared papers)Yun Zhang (4 shared papers)Zeyan Xu (4 shared papers)
In The Last Decade
Jiatai Lin
17 papers receiving 405 citations
Jiatai Lin's Hit Papers
Peers
Comparison fields: 5 of 73
- Neurology 108
- Computer Vision and Pattern Recognition 176
- Artificial Intelligence 238
- Radiology, Nuclear Medicine and Imaging 171
- Health Informatics 7
Countries citing papers authored by Jiatai Lin
This map shows the geographic impact of Jiatai Lin'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 Jiatai Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jiatai Lin more than expected).
Fields of papers citing papers by Jiatai Lin
This network shows the impact of papers produced by Jiatai Lin. 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 Jiatai Lin. The network helps show where Jiatai Lin may publish in the future.
Co-authors
The 25 scholars most cited alongside Jiatai Lin, 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 | CKD-TransBTS: Clinical Knowledge-Driven Hybrid Transformer With Modality-Correlated Cross-Attention for Brain Tumor Segmentation Hit paper breakdown → | 2023 | 103 |
| 2 | 2023 | 72 | |
| 3 | 2022 | 68 | |
| 4 | 2022 | 39 | |
| 5 | 2022 | 30 | |
| 6 | 2019 | 20 | |
| 7 | 2019 | 19 | |
| 8 | 2022 | 18 | |
| 9 | 2019 | 18 | |
| 10 | 2020 | 7 | |
| 11 | 2024 | 6 | |
| 12 | 2019 | 5 | |
| 13 | 2024 | 4 | |
| 14 | 2024 | 3 | |
| 15 | 2019 | 3 | |
| 16 | 2025 | 1 | |
| 17 | 2018 | 1 | |
| 18 | 2025 | 0 |
About Jiatai Lin
Jiatai Lin is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Control and Systems Engineering and Cognitive Neuroscience, having authored 18 papers that have together received 417 indexed citations. Recurring topics across this work include AI in cancer detection (10 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), Digital Imaging for Blood Diseases (4 papers), Machine Learning and ELM (4 papers), EEG and Brain-Computer Interfaces (3 papers), COVID-19 diagnosis using AI (2 papers), Brain Tumor Detection and Classification (2 papers) and Elevator Systems and Control (2 papers). The work is most often cited by research in Neurology (108 citations), Computer Vision and Pattern Recognition (176 citations), Artificial Intelligence (238 citations), Radiology, Nuclear Medicine and Imaging (171 citations) and Health Informatics (7 citations). Jiatai Lin has collaborated with scholars based in China, Hong Kong and Macao. Frequent co-authors include Chu Han, Zaiyi Liu, Xipeng Pan, Zhenwei Shi, Zhi Liu, Bingchao Zhao, Yun Zhang, Zeyan Xu, Guoqiang Han and Huan Lin. Their work appears in journals such as IEEE Transactions on Medical Imaging, Neurocomputing, Artificial Intelligence in Medicine, iScience and IEEE Transactions on Cybernetics.
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.