Yingda Xia
Impact in
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- Advanced Neural Network Applications
- Medical Image Segmentation Techniques
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- Advanced Neural Network Applications 17
- Medical Image Segmentation Techniques 10
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- Radiomics and Machine Learning in Medical Imaging 10
- COVID-19 diagnosis using AI 6
- Co-authors
- Alan Yuille (13 shared papers)Zhuotun Zhu (7 shared papers)Fengze Liu (7 shared papers)Elliot K. Fishman (8 shared papers)Wei Shen (4 shared papers)Dong Yang (3 shared papers)Daguang Xu (3 shared papers)Jinzheng Cai (2 shared papers)
- Journals
- Lecture notes in computer science (14 papers)Medical Image Analysis (1 paper)IEEE Transactions on Neural Networks and Learning Systems (1 paper)Nature Communications (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)
- Partner nations
- United StatesChinaHong Kong
In The Last Decade
Yingda Xia
24 papers receiving 904 citations
Peers
Comparison fields: 5 of 72
- Computer Vision and Pattern Recognition 504
- Radiology, Nuclear Medicine and Imaging 393
- Artificial Intelligence 458
- Neurology 81
- Health Informatics 11
Countries citing papers authored by Yingda Xia
This map shows the geographic impact of Yingda Xia'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 Yingda Xia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yingda Xia more than expected).
Fields of papers citing papers by Yingda Xia
This network shows the impact of papers produced by Yingda Xia. 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 Yingda Xia. The network helps show where Yingda Xia may publish in the future.
Co-authors
The 25 scholars most cited alongside Yingda Xia, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 191 | |
| 2 | 2022 | 127 | |
| 3 | 2020 | 113 | |
| 4 | 2018 | 112 | |
| 5 | 2020 | 94 | |
| 6 | 2019 | 73 | |
| 7 | 2018 | 64 | |
| 8 | 2021 | 22 | |
| 9 | 2023 | 21 | |
| 10 | A 3D Coarse-to-Fine Framework for Automatic Pancreas Segmentation. | 2017 | 19 |
| 11 | 2019 | 16 | |
| 12 | 2020 | 14 | |
| 13 | 2019 | 12 | |
| 14 | 2024 | 7 | |
| 15 | 2022 | 7 | |
| 16 | 2022 | 6 | |
| 17 | 2023 | 4 | |
| 18 | 2024 | 4 | |
| 19 | Thickened 2D Networks for 3D Medical Image Segmentation. | 2019 | 3 |
| 20 | 2023 | 3 |
About Yingda Xia
Yingda Xia is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Oncology and Biomedical Engineering, having authored 26 papers that have together received 919 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (17 papers), Radiomics and Machine Learning in Medical Imaging (10 papers), Medical Image Segmentation Techniques (10 papers), AI in cancer detection (8 papers), COVID-19 diagnosis using AI (6 papers), Pancreatic and Hepatic Oncology Research (4 papers), Medical Imaging and Analysis (3 papers) and Domain Adaptation and Few-Shot Learning (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (504 citations), Radiology, Nuclear Medicine and Imaging (393 citations), Artificial Intelligence (458 citations), Neurology (81 citations) and Health Informatics (11 citations). Yingda Xia has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Alan Yuille, Zhuotun Zhu, Fengze Liu, Elliot K. Fishman, Wei Shen, Dong Yang, Daguang Xu, Jinzheng Cai, Lequan Yu and Holger R. Roth. Their work appears in journals such as Lecture notes in computer science, Medical Image Analysis, IEEE Transactions on Neural Networks and Learning Systems, Nature Communications and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.