Yutong Xie
- Health Informatics top 1%
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- Radiomics and Machine Learning in Medical Imaging 16
- COVID-19 diagnosis using AI 14
- Artificial Intelligence top 0.5%
- AI in cancer detection 10
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- Advanced Neural Network Applications 9
- Medical Image Segmentation Techniques 4
- Neurology top 5%
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- Lung Cancer Diagnosis and Treatment 5
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- Hydrological Forecasting Using AI 4
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- Cutaneous Melanoma Detection and Management 4
Yutong Xie
50 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 160
- Health Informatics 134
- Radiology, Nuclear Medicine and Imaging 1.6k
- Artificial Intelligence 1.5k
- Computer Vision and Pattern Recognition 812
- Neurology 237
Countries citing papers authored by Yutong Xie
This map shows the geographic impact of Yutong Xie'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 Yutong Xie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yutong Xie more than expected).
Fields of papers citing papers by Yutong Xie
This network shows the impact of papers produced by Yutong Xie. 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 Yutong Xie. The network helps show where Yutong Xie may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yutong Xie, 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 | 2026 | 0 | |
| 2 | 2025 | 8 | |
| 3 | 2025 | 0 | |
| 4 | 2025 | 7 | |
| 5 | 2025 | 0 | |
| 6 | 2025 | 5 | |
| 7 | 2025 | 7 | |
| 8 | 2024 | 7 | |
| 9 | 2024 | 0 | |
| 10 | 2024 | 3 | |
| 11 | 2024 | 0 | |
| 12 | 2024 | 2 | |
| 13 | TransUNet: Rethinking the U-Net architecture design for medical image segmentation through the lens of transformersbreakdown → | 2024 | 287 |
| 14 | 2023 | 6 | |
| 15 | 2023 | 2 | |
| 16 | 2023 | 2 | |
| 17 | 2022 | 6 | |
| 18 | 2022 | 13 | |
| 19 | Medical image classification using synergic deep learningbreakdown → | 2019 | 269 |
| 20 | 2017 | 88 |
About Yutong Xie
Yutong Xie is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Computer Vision and Pattern Recognition, having authored 62 papers that have together received 3.2k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (16 papers), COVID-19 diagnosis using AI (14 papers), AI in cancer detection (10 papers), Advanced Neural Network Applications (9 papers), Lung Cancer Diagnosis and Treatment (5 papers), Hydrological Forecasting Using AI (4 papers), Medical Image Segmentation Techniques (4 papers) and Cutaneous Melanoma Detection and Management (4 papers). The work is most often cited by research in Health Informatics (134 citations), Radiology, Nuclear Medicine and Imaging (1.6k citations) and Artificial Intelligence (1.5k citations). Yutong Xie has collaborated with scholars based in China, Australia and United States. Frequent co-authors include Yong Xia, Jianpeng Zhang, Chunhua Shen, Michael Fulham, Qi Wu, Dagan Feng, Yi Li, Weidong Cai, Yang Song and Yanning Zhang. Their work appears in journals such as Proceedings of the National Academy of Sciences, IEEE Transactions on Pattern Analysis and Machine Intelligence and Environmental Pollution.
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.