Along He
Impact in
- Ophthalmology top 5%
- Retinal Diseases and Treatments
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- Retinal Imaging and Analysis
- Radiomics and Machine Learning in Medical Imaging
Papers in
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- Medical Image Segmentation Techniques 4
- Advanced Neural Network Applications 3
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- COVID-19 diagnosis using AI 2
- Retinal Imaging and Analysis 2
- Radiomics and Machine Learning in Medical Imaging 2
- Co-authors
- Huazhu Fu (7 shared papers)Tao Li (7 shared papers)Kai Wang (5 shared papers)Ning Li (1 shared paper)Shuang Xia (1 shared paper)Hong Kang (2 shared papers)Bo Wang (1 shared paper)Yuxi Wang (1 shared paper)
In The Last Decade
Along He
12 papers receiving 507 citations
Along He's Hit Papers
Peers
Comparison fields: 5 of 78
- Ophthalmology 140
- Radiology, Nuclear Medicine and Imaging 289
- Computer Vision and Pattern Recognition 248
- Neurology 89
- Health Information Management 46
Countries citing papers authored by Along He
This map shows the geographic impact of Along He'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 Along He with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Along He more than expected).
Fields of papers citing papers by Along He
This network shows the impact of papers produced by Along He. 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 Along He. The network helps show where Along He may publish in the future.
Co-authors
The 21 scholars most cited alongside Along He, 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 | CABNet: Category Attention Block for Imbalanced Diabetic Retinopathy Grading Hit paper breakdown → | 2020 | 241 |
| 2 | H2Former: An Efficient Hierarchical Hybrid Transformer for Medical Image Segmentation Hit paper breakdown → | 2023 | 160 |
| 3 | 2022 | 39 | |
| 4 | 2019 | 34 | |
| 5 | 2020 | 13 | |
| 6 | 2023 | 12 | |
| 7 | 2024 | 5 | |
| 8 | 2024 | 4 | |
| 9 | 2025 | 4 | |
| 10 | 2024 | 4 | |
| 11 | 2021 | 1 | |
| 12 | 2020 | 1 | |
| 13 | 2025 | 0 | |
| 14 | 2024 | 0 |
About Along He
Along He is a scholar working on Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, General Health Professions and Ophthalmology, having authored 14 papers that have together received 518 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (4 papers), AI in cancer detection (3 papers), Advanced Neural Network Applications (3 papers), COVID-19 diagnosis using AI (2 papers), Brain Tumor Detection and Classification (2 papers), Retinal Imaging and Analysis (2 papers), Radiomics and Machine Learning in Medical Imaging (2 papers) and Retinal and Optic Conditions (2 papers). The work is most often cited by research in Ophthalmology (140 citations), Radiology, Nuclear Medicine and Imaging (289 citations), Computer Vision and Pattern Recognition (248 citations), Neurology (89 citations) and Health Information Management (46 citations). Along He has collaborated with scholars based in China, Singapore and Hong Kong. Frequent co-authors include Huazhu Fu, Tao Li, Kai Wang, Ning Li, Shuang Xia, Hong Kang, Bo Wang, Yuxi Wang, Xiaolin Nie and He Bu. Their work appears in journals such as IEEE Transactions on Medical Imaging, Knowledge-Based Systems, IEEE Journal of Biomedical and Health Informatics, Neural Networks and Medical Image Analysis.
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.