Haoran Dou
Impact in
- Health Informatics top 5%
-
- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
Papers in
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- AI in cancer detection 11
- Domain Adaptation and Few-Shot Learning 6
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- Medical Image Segmentation Techniques 11
- Generative Adversarial Networks and Image Synthesis 5
- Co-authors
- Dong Ni (14 shared papers)Xin Yang (15 shared papers)Yunzhi Huang (5 shared papers)Luyi Han (4 shared papers)Qi Liu (2 shared papers)Honghao Luo (2 shared papers)Ali Gholipour (2 shared papers)Davood Karimi (2 shared papers)
- Journals
- Medical Image Analysis (5 papers)Computer Methods and Programs in Biomedicine (4 papers)IEEE Access (2 papers)IEEE Transactions on Medical Imaging (2 papers)Energy (2 papers)
- Partner nations
- ChinaUnited KingdomUnited States
In The Last Decade
Haoran Dou
28 papers receiving 506 citations
Peers
Comparison fields: 5 of 89
- Health Informatics 30
- Radiology, Nuclear Medicine and Imaging 242
- Artificial Intelligence 256
- Computer Vision and Pattern Recognition 160
- Neurology 58
Countries citing papers authored by Haoran Dou
This map shows the geographic impact of Haoran Dou'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 Haoran Dou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haoran Dou more than expected).
Fields of papers citing papers by Haoran Dou
This network shows the impact of papers produced by Haoran Dou. 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 Haoran Dou. The network helps show where Haoran Dou may publish in the future.
Co-authors
The 25 scholars most cited alongside Haoran Dou, 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 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 75 | |
| 2 | 2022 | 61 | |
| 3 | 2019 | 55 | |
| 4 | 2020 | 43 | |
| 5 | 2021 | 40 | |
| 6 | 2022 | 29 | |
| 7 | 2022 | 28 | |
| 8 | 2022 | 26 | |
| 9 | 2021 | 20 | |
| 10 | 2020 | 20 | |
| 11 | 2021 | 20 | |
| 12 | 2019 | 16 | |
| 13 | 2023 | 15 | |
| 14 | 2020 | 14 | |
| 15 | 2020 | 12 | |
| 16 | 2023 | 11 | |
| 17 | 2025 | 6 | |
| 18 | 2024 | 5 | |
| 19 | 2018 | 5 | |
| 20 | 2025 | 2 |
About Haoran Dou
Haoran Dou is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Pediatrics, Perinatology and Child Health and Neurology, having authored 31 papers that have together received 513 indexed citations. Recurring topics across this work include AI in cancer detection (11 papers), Medical Image Segmentation Techniques (11 papers), Radiomics and Machine Learning in Medical Imaging (8 papers), Domain Adaptation and Few-Shot Learning (6 papers), Generative Adversarial Networks and Image Synthesis (5 papers), Brain Tumor Detection and Classification (4 papers), Fetal and Pediatric Neurological Disorders (4 papers) and Ultrasound Imaging and Elastography (3 papers). The work is most often cited by research in Health Informatics (30 citations), Radiology, Nuclear Medicine and Imaging (242 citations), Artificial Intelligence (256 citations), Computer Vision and Pattern Recognition (160 citations) and Neurology (58 citations). Haoran Dou has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Dong Ni, Xin Yang, Yunzhi Huang, Luyi Han, Qi Liu, Honghao Luo, Ali Gholipour, Davood Karimi, Ruobing Huang and Guanhua Ni. Their work appears in journals such as Medical Image Analysis, Computer Methods and Programs in Biomedicine, IEEE Access, IEEE Transactions on Medical Imaging and Energy.
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.