Leonard Wee
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- MRI in cancer diagnosis
Papers in
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- Radiomics and Machine Learning in Medical Imaging 61
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- Lung Cancer Diagnosis and Treatment 14
- Co-authors
- Andre Dekker (93 shared papers)Alberto Traverso (32 shared papers)Robert J. Gillies (2 shared papers)David A. Jaffray (8 shared papers)Zhenwei Shi (23 shared papers)Mattea L. Welch (9 shared papers)Iñigo Bermejo (17 shared papers)Juha V. Korhonen (3 shared papers)
- Journals
- Medical Physics (11 papers)Radiotherapy and Oncology (9 papers)Physica Medica (6 papers)Journal of Applied Physics (5 papers)Physics in Medicine and Biology (5 papers)
- Partner nations
- NetherlandsChinaAustralia
In The Last Decade
Leonard Wee
132 papers receiving 3.3k citations
Leonard Wee's Hit Papers
Peers
Comparison fields: 5 of 153
- Health Informatics 207
- Radiology, Nuclear Medicine and Imaging 1.7k
- Radiation 228
- Pulmonary and Respiratory Medicine 484
- Otorhinolaryngology 51
Countries citing papers authored by Leonard Wee
This map shows the geographic impact of Leonard Wee'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 Leonard Wee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leonard Wee more than expected).
Fields of papers citing papers by Leonard Wee
This network shows the impact of papers produced by Leonard Wee. 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 Leonard Wee. The network helps show where Leonard Wee may publish in the future.
Co-authors
The 25 scholars most cited alongside Leonard Wee, 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 146 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Repeatability and Reproducibility of Radiomic Features: A Systematic Review Hit paper breakdown → | 2018 | 679 |
| 2 | 2018 | 250 | |
| 3 | 2018 | 243 | |
| 4 | 2020 | 90 | |
| 5 | 2021 | 85 | |
| 6 | 2021 | 76 | |
| 7 | 2018 | 71 | |
| 8 | 2016 | 69 | |
| 9 | 2019 | 64 | |
| 10 | 2022 | 61 | |
| 11 | 2019 | 60 | |
| 12 | 2020 | 57 | |
| 13 | 1999 | 57 | |
| 14 | 2020 | 54 | |
| 15 | 2018 | 51 | |
| 16 | 2019 | 49 | |
| 17 | 2019 | 47 | |
| 18 | 2021 | 44 | |
| 19 | 2021 | 40 | |
| 20 | 2014 | 40 |
About Leonard Wee
Leonard Wee is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine, Health Informatics, Radiation and Artificial Intelligence, having authored 146 papers that have together received 3.3k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (61 papers), AI in cancer detection (15 papers), Advanced X-ray and CT Imaging (14 papers), Lung Cancer Diagnosis and Treatment (14 papers), Magnetic properties of thin films (11 papers), Advanced Radiotherapy Techniques (11 papers), Magnetic Properties and Applications (11 papers) and Artificial Intelligence in Healthcare and Education (8 papers). The work is most often cited by research in Health Informatics (207 citations), Radiology, Nuclear Medicine and Imaging (1.7k citations), Radiation (228 citations), Pulmonary and Respiratory Medicine (484 citations) and Otorhinolaryngology (51 citations). Leonard Wee has collaborated with scholars based in Netherlands, China and Australia. Frequent co-authors include Andre Dekker, Alberto Traverso, Robert J. Gillies, David A. Jaffray, Zhenwei Shi, Mattea L. Welch, Iñigo Bermejo, Juha V. Korhonen, Robert L. Stamps and Johan van Soest. Their work appears in journals such as Medical Physics, Radiotherapy and Oncology, Physica Medica, Journal of Applied Physics and Physics in Medicine and Biology.
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.