Dewei Hu
Impact in
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- Medical Image Segmentation Techniques
- Advanced Neural Network Applications
Papers in
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- Retinal Imaging and Analysis 4
- COVID-19 diagnosis using AI 3
- Radiomics and Machine Learning in Medical Imaging 3
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- Advanced Neural Network Applications 5
- Medical Image Segmentation Techniques 3
- Digital Imaging for Blood Diseases 2
- Co-authors
- İpek Oğuz (14 shared papers)Yuankai K. Tao (6 shared papers)Damian Szklarczyk (2 shared papers)Tao Fang (1 shared paper)Sampo Pyysalo (1 shared paper)Mikaela Koutrouli (1 shared paper)Peer Bork (1 shared paper)Qingyao Huang (1 shared paper)
- Journals
- Nucleic Acids Research (1 paper)Bioinformatics (1 paper)Lecture notes in computer science (3 papers)PubMed (2 papers)2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) (1 paper)
- Partner nations
- United StatesSwitzerlandDenmark
In The Last Decade
Dewei Hu
16 papers receiving 178 citations
Dewei Hu's Hit Papers
Peers
Comparison fields: 5 of 72
- Health Informatics 6
- Computer Vision and Pattern Recognition 45
- Biophysics 10
- Radiology, Nuclear Medicine and Imaging 39
- Neurology 13
Countries citing papers authored by Dewei Hu
This map shows the geographic impact of Dewei Hu'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 Dewei Hu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dewei Hu more than expected).
Fields of papers citing papers by Dewei Hu
This network shows the impact of papers produced by Dewei Hu. 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 Dewei Hu. The network helps show where Dewei Hu may publish in the future.
Co-authors
The 25 scholars most cited alongside Dewei Hu, 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 | The STRING database in 2025: protein networks with directionality of regulation Hit paper breakdown → | 2024 | 93 |
| 2 | 2022 | 35 | |
| 3 | 2024 | 13 | |
| 4 | 2022 | 8 | |
| 5 | 2021 | 7 | |
| 6 | 2020 | 7 | |
| 7 | 2020 | 5 | |
| 8 | 2023 | 2 | |
| 9 | 2023 | 2 | |
| 10 | 2022 | 2 | |
| 11 | 2024 | 1 | |
| 12 | 2010 | 1 | |
| 13 | 2024 | 1 | |
| 14 | 2023 | 1 | |
| 15 | 2024 | 1 | |
| 16 | 2021 | 1 | |
| 17 | 2025 | 0 |
About Dewei Hu
Dewei Hu is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Biomedical Engineering, Ophthalmology and Artificial Intelligence, having authored 17 papers that have together received 180 indexed citations. Recurring topics across this work include Optical Coherence Tomography Applications (5 papers), Advanced Neural Network Applications (5 papers), Retinal Imaging and Analysis (4 papers), COVID-19 diagnosis using AI (3 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Medical Image Segmentation Techniques (3 papers), Digital Imaging for Blood Diseases (2 papers) and Glaucoma and retinal disorders (2 papers). The work is most often cited by research in Health Informatics (6 citations), Computer Vision and Pattern Recognition (45 citations), Biophysics (10 citations), Radiology, Nuclear Medicine and Imaging (39 citations) and Neurology (13 citations). Dewei Hu has collaborated with scholars based in United States, Switzerland and Denmark. Frequent co-authors include İpek Oğuz, Yuankai K. Tao, Damian Szklarczyk, Tao Fang, Sampo Pyysalo, Mikaela Koutrouli, Peer Bork, Qingyao Huang, Farrokh Mehryary and Lars Juhl Jensen. Their work appears in journals such as Nucleic Acids Research, Bioinformatics, Lecture notes in computer science, PubMed and 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI).
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.