Dakai Jin
Impact in
- Health Informatics top 5%
-
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Medical Imaging Techniques and Applications
Papers in
-
- Medical Imaging Techniques and Applications 12
- Radiomics and Machine Learning in Medical Imaging 12
- COVID-19 diagnosis using AI 4
-
- Medical Image Segmentation Techniques 9
- Co-authors
- Punam K. Saha (16 shared papers)Le Lü (12 shared papers)Dazhou Guo (8 shared papers)Eric A. Hoffman (7 shared papers)Cheng Chen (6 shared papers)Jing Xiao (4 shared papers)Krishna Iyer (4 shared papers)Adam P. Harrison (4 shared papers)
- Journals
- International Journal of Radiation Oncology*Biology*Physics (4 papers)Medical Physics (4 papers)IEEE Transactions on Medical Imaging (4 papers)IEEE Transactions on Visualization and Computer Graphics (1 paper)IEEE Transactions on Neural Networks and Learning Systems (1 paper)
- Partner nations
- United StatesChinaTaiwan
In The Last Decade
Dakai Jin
33 papers receiving 691 citations
Dakai Jin's Hit Papers
Peers
Comparison fields: 5 of 86
- Health Informatics 42
- Radiology, Nuclear Medicine and Imaging 370
- Computer Vision and Pattern Recognition 208
- Orthopedics and Sports Medicine 69
- Artificial Intelligence 154
Countries citing papers authored by Dakai Jin
This map shows the geographic impact of Dakai Jin'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 Dakai Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dakai Jin more than expected).
Fields of papers citing papers by Dakai Jin
This network shows the impact of papers produced by Dakai Jin. 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 Dakai Jin. The network helps show where Dakai Jin may publish in the future.
Co-authors
The 25 scholars most cited alongside Dakai Jin, 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 35 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | LViT: Language Meets Vision Transformer in Medical Image Segmentation Hit paper breakdown → | 2023 | 135 |
| 2 | 2015 | 69 | |
| 3 | 2020 | 62 | |
| 4 | 2020 | 46 | |
| 5 | 2020 | 43 | |
| 6 | 2017 | 40 | |
| 7 | 2014 | 37 | |
| 8 | 2020 | 33 | |
| 9 | 2015 | 33 | |
| 10 | 2021 | 31 | |
| 11 | 2017 | 20 | |
| 12 | 2015 | 20 | |
| 13 | 2015 | 19 | |
| 14 | 2019 | 18 | |
| 15 | 2022 | 16 | |
| 16 | 2022 | 9 | |
| 17 | 2023 | 8 | |
| 18 | 2016 | 8 | |
| 19 | 2024 | 6 | |
| 20 | 2024 | 5 |
About Dakai Jin
Dakai Jin is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine, Biomedical Engineering and Artificial Intelligence, having authored 35 papers that have together received 697 indexed citations. Recurring topics across this work include Medical Imaging Techniques and Applications (12 papers), Radiomics and Machine Learning in Medical Imaging (12 papers), Medical Image Segmentation Techniques (9 papers), Lung Cancer Diagnosis and Treatment (8 papers), Medical Imaging and Analysis (7 papers), Bone health and osteoporosis research (5 papers), AI in cancer detection (5 papers) and COVID-19 diagnosis using AI (4 papers). The work is most often cited by research in Health Informatics (42 citations), Radiology, Nuclear Medicine and Imaging (370 citations), Computer Vision and Pattern Recognition (208 citations), Orthopedics and Sports Medicine (69 citations) and Artificial Intelligence (154 citations). Dakai Jin has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Punam K. Saha, Le Lü, Dazhou Guo, Eric A. Hoffman, Cheng Chen, Jing Xiao, Krishna Iyer, Adam P. Harrison, Puyang Wang and You Zhang. Their work appears in journals such as International Journal of Radiation Oncology*Biology*Physics, Medical Physics, IEEE Transactions on Medical Imaging, IEEE Transactions on Visualization and Computer Graphics and IEEE Transactions on Neural Networks and Learning Systems.
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.