Lin Lü
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- MRI in cancer diagnosis
- Health Informatics top 2%
Papers in
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- Radiomics and Machine Learning in Medical Imaging 34
- Cardiac Imaging and Diagnostics 8
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- Machine Learning in Bioinformatics 17
- Co-authors
- Binsheng Zhao (28 shared papers)Lawrence H. Schwartz (29 shared papers)Yongqiang Tan (2 shared papers)Yu‐Dong Cai (23 shared papers)Laurent Dercle (13 shared papers)Chuanmiao Xie (1 shared paper)Wei‐Yann Tsai (1 shared paper)Jing Qi (1 shared paper)
- Journals
- European Radiology (6 papers)Molecular Diversity (6 papers)Journal of Cardiovascular Magnetic Resonance (5 papers)Tomography (4 papers)American Journal of Roentgenology (3 papers)
- Partner nations
- ChinaUnited StatesFrance
In The Last Decade
Lin Lü
100 papers receiving 2.9k citations
Hit Papers
Peers
Comparison fields: 5 of 141
- Radiology, Nuclear Medicine and Imaging 1.8k
- Health Informatics 61
- Pulmonary and Respiratory Medicine 840
- Hepatology 191
- Oncology 476
Countries citing papers authored by Lin Lü
This map shows the geographic impact of Lin Lü'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 Lin Lü with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lin Lü more than expected).
Fields of papers citing papers by Lin Lü
This network shows the impact of papers produced by Lin Lü. 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 Lin Lü. The network helps show where Lin Lü may publish in the future.
Co-authors
The 25 scholars most cited alongside Lin Lü, 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 105 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Reproducibility of radiomics for deciphering tumor phenotype with imaging Hit paper breakdown → | 2016 | 412 |
| 2 | 2018 | 173 | |
| 3 | 2019 | 136 | |
| 4 | 2020 | 128 | |
| 5 | 2016 | 127 | |
| 6 | 2020 | 113 | |
| 7 | 2014 | 105 | |
| 8 | 2016 | 96 | |
| 9 | 2018 | 70 | |
| 10 | 2018 | 67 | |
| 11 | 2018 | 67 | |
| 12 | 2020 | 66 | |
| 13 | 2021 | 63 | |
| 14 | 2022 | 57 | |
| 15 | 2015 | 55 | |
| 16 | 2019 | 52 | |
| 17 | 2018 | 50 | |
| 18 | 2017 | 47 | |
| 19 | 2019 | 44 | |
| 20 | 2019 | 39 |
About Lin Lü
Lin Lü is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology, Oncology, Pulmonary and Respiratory Medicine and Biomedical Engineering, having authored 105 papers that have together received 2.9k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (34 papers), Advanced X-ray and CT Imaging (17 papers), Machine Learning in Bioinformatics (17 papers), Lung Cancer Diagnosis and Treatment (14 papers), Colorectal Cancer Screening and Detection (11 papers), AI in cancer detection (10 papers), Cardiac Imaging and Diagnostics (8 papers) and Medical Image Segmentation Techniques (7 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.8k citations), Health Informatics (61 citations), Pulmonary and Respiratory Medicine (840 citations), Hepatology (191 citations) and Oncology (476 citations). Lin Lü has collaborated with scholars based in China, United States and France. Frequent co-authors include Binsheng Zhao, Lawrence H. Schwartz, Yongqiang Tan, Yu‐Dong Cai, Laurent Dercle, Chuanmiao Xie, Wei‐Yann Tsai, Jing Qi, Fadel M. Megahed and Lei Chen. Their work appears in journals such as European Radiology, Molecular Diversity, Journal of Cardiovascular Magnetic Resonance, Tomography and American Journal of Roentgenology.
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.