Tao Zhou
Impact in
- Health Informatics top 5%
-
- COVID-19 diagnosis using AI
- Radiomics and Machine Learning in Medical Imaging
Papers in
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- AI in cancer detection 21
-
- Medical Image Segmentation Techniques 12
- Image and Signal Denoising Methods 8
- Co-authors
- Huiling Lu (36 shared papers)Shi Qiu (7 shared papers)Yong Xia (5 shared papers)Zaoli Yang (1 shared paper)Xinyu Ye (7 shared papers)Shi Qiu (2 shared papers)Huiling Lu (7 shared papers)Xiangxiang Zhang (5 shared papers)
- Journals
- BioMed Research International (9 papers)Computers in Biology and Medicine (5 papers)Applied Soft Computing (4 papers)Biomedical Signal Processing and Control (3 papers)Information Fusion (2 papers)
- Partner nations
- ChinaUnited KingdomAustralia
In The Last Decade
Tao Zhou
98 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 149
- Health Informatics 35
- Radiology, Nuclear Medicine and Imaging 332
- Media Technology 123
- Computer Vision and Pattern Recognition 283
- Artificial Intelligence 400
Countries citing papers authored by Tao Zhou
This map shows the geographic impact of Tao Zhou'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 Tao Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tao Zhou more than expected).
Fields of papers citing papers by Tao Zhou
This network shows the impact of papers produced by Tao Zhou. 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 Tao Zhou. The network helps show where Tao Zhou may publish in the future.
Co-authors
The 25 scholars most cited alongside Tao Zhou, 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 110 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 200 | |
| 2 | 2018 | 195 | |
| 3 | 2022 | 125 | |
| 4 | 2023 | 98 | |
| 5 | 2013 | 34 | |
| 6 | 2016 | 31 | |
| 7 | 2017 | 28 | |
| 8 | 2023 | 25 | |
| 9 | 2023 | 23 | |
| 10 | 2013 | 23 | |
| 11 | 2024 | 18 | |
| 12 | 2022 | 17 | |
| 13 | 2025 | 15 | |
| 14 | 2021 | 15 | |
| 15 | 2022 | 14 | |
| 16 | 2024 | 12 | |
| 17 | 2020 | 12 | |
| 18 | 2020 | 12 | |
| 19 | 2008 | 12 | |
| 20 | 2022 | 11 |
About Tao Zhou
Tao Zhou is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Media Technology and Electrical and Electronic Engineering, having authored 110 papers that have together received 1.2k indexed citations. Recurring topics across this work include AI in cancer detection (21 papers), Radiomics and Machine Learning in Medical Imaging (16 papers), Advanced Image Fusion Techniques (13 papers), Medical Image Segmentation Techniques (12 papers), COVID-19 diagnosis using AI (12 papers), Image and Signal Denoising Methods (8 papers), Brain Tumor Detection and Classification (7 papers) and Lung Cancer Diagnosis and Treatment (6 papers). The work is most often cited by research in Health Informatics (35 citations), Radiology, Nuclear Medicine and Imaging (332 citations), Media Technology (123 citations), Computer Vision and Pattern Recognition (283 citations) and Artificial Intelligence (400 citations). Tao Zhou has collaborated with scholars based in China, United Kingdom and Australia. Frequent co-authors include Huiling Lu, Shi Qiu, Yong Xia, Zaoli Yang, Xinyu Ye, Shi Qiu, Huiling Lu, Xiangxiang Zhang, Qianru Cheng and Qi Li. Their work appears in journals such as BioMed Research International, Computers in Biology and Medicine, Applied Soft Computing, Biomedical Signal Processing and Control and Information Fusion.
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.