Huiling Lu
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 17
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- Radiomics and Machine Learning in Medical Imaging 12
- COVID-19 diagnosis using AI 10
- Co-authors
- Tao Zhou (36 shared papers)Shi Qiu (5 shared papers)Yong Xia (1 shared paper)Zaoli Yang (1 shared paper)Xinyu Ye (7 shared papers)Junjie Zhang (1 shared paper)Hongbin Shi (1 shared paper)Hongwei Wang (1 shared paper)
- Journals
- BioMed Research International (8 papers)Computers, materials & continua/Computers, materials & continua (Print) (3 papers)Applied Soft Computing (3 papers)Computers in Biology and Medicine (2 papers)Electronics (2 papers)
- Partner nations
- ChinaUnited Kingdom
In The Last Decade
Huiling Lu
41 papers receiving 744 citations
Peers
Comparison fields: 5 of 124
- Health Informatics 32
- Radiology, Nuclear Medicine and Imaging 268
- Artificial Intelligence 328
- Neurology 62
- Computer Vision and Pattern Recognition 163
Countries citing papers authored by Huiling Lu
This map shows the geographic impact of Huiling Lu'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 Huiling Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Huiling Lu more than expected).
Fields of papers citing papers by Huiling Lu
This network shows the impact of papers produced by Huiling Lu. 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 Huiling Lu. The network helps show where Huiling Lu may publish in the future.
Co-authors
The 25 scholars most cited alongside Huiling Lu, 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 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 200 | |
| 2 | 2018 | 195 | |
| 3 | 2022 | 125 | |
| 4 | 2016 | 31 | |
| 5 | 2023 | 25 | |
| 6 | Clustering algorithm research advances on data mining | 2012 | 18 |
| 7 | 2024 | 18 | |
| 8 | 2022 | 17 | |
| 9 | 2020 | 12 | |
| 10 | 2008 | 12 | |
| 11 | 2022 | 8 | |
| 12 | 2024 | 8 | |
| 13 | 2023 | 7 | |
| 14 | 2007 | 7 | |
| 15 | 2020 | 6 | |
| 16 | 2021 | 6 | |
| 17 | 2023 | 5 | |
| 18 | 2021 | 5 | |
| 19 | 2022 | 5 | |
| 20 | 2022 | 5 |
About Huiling Lu
Huiling Lu is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Neurology and Media Technology, having authored 48 papers that have together received 761 indexed citations. Recurring topics across this work include AI in cancer detection (17 papers), Radiomics and Machine Learning in Medical Imaging (12 papers), COVID-19 diagnosis using AI (10 papers), Medical Image Segmentation Techniques (9 papers), Brain Tumor Detection and Classification (7 papers), Advanced Image Fusion Techniques (7 papers), Advanced Algorithms and Applications (4 papers) and Advanced Neural Network Applications (4 papers). The work is most often cited by research in Health Informatics (32 citations), Radiology, Nuclear Medicine and Imaging (268 citations), Artificial Intelligence (328 citations), Neurology (62 citations) and Computer Vision and Pattern Recognition (163 citations). Huiling Lu has collaborated with scholars based in China and United Kingdom. Frequent co-authors include Tao Zhou, Shi Qiu, Yong Xia, Zaoli Yang, Xinyu Ye, Junjie Zhang, Hongbin Shi, Hongwei Wang, Yanning Zhang and Huiyu Zhou. Their work appears in journals such as BioMed Research International, Computers, materials & continua/Computers, materials & continua (Print), Applied Soft Computing, Computers in Biology and Medicine and Electronics.
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.