Maxine Tan
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- MRI in cancer diagnosis
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- Lung Cancer Diagnosis and Treatment
- Digital Radiography and Breast Imaging
Papers in
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- AI in cancer detection 24
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- Digital Radiography and Breast Imaging 13
- Lung Cancer Diagnosis and Treatment 7
- Co-authors
- Bin Zheng (26 shared papers)Hong Liu (11 shared papers)Jiantao Pu (7 shared papers)Rudi Deklerck (6 shared papers)Jan Cornelis (4 shared papers)Bart Jansen (4 shared papers)Michel Bister (2 shared papers)Yuchen Qiu (8 shared papers)
- Journals
- Medical Physics (4 papers)Physics in Medicine and Biology (4 papers)International Journal of Computer Assisted Radiology and Surgery (3 papers)Journal of Magnetic Resonance Imaging (2 papers)Cancers (2 papers)
- Partner nations
- United StatesMalaysiaBelgium
In The Last Decade
Maxine Tan
45 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 73
- Radiology, Nuclear Medicine and Imaging 649
- Pulmonary and Respiratory Medicine 505
- Artificial Intelligence 545
- Health Informatics 13
- Neurology 67
Countries citing papers authored by Maxine Tan
This map shows the geographic impact of Maxine Tan'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 Maxine Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maxine Tan more than expected).
Fields of papers citing papers by Maxine Tan
This network shows the impact of papers produced by Maxine Tan. 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 Maxine Tan. The network helps show where Maxine Tan may publish in the future.
Co-authors
The 25 scholars most cited alongside Maxine Tan, 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 45 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 171 | |
| 2 | 2015 | 94 | |
| 3 | 2014 | 64 | |
| 4 | 2019 | 62 | |
| 5 | 2016 | 58 | |
| 6 | 2021 | 56 | |
| 7 | 2015 | 55 | |
| 8 | 2016 | 54 | |
| 9 | 2013 | 52 | |
| 10 | 2016 | 52 | |
| 11 | 2019 | 48 | |
| 12 | 2015 | 46 | |
| 13 | 2015 | 33 | |
| 14 | 2015 | 28 | |
| 15 | 2014 | 27 | |
| 16 | 2013 | 24 | |
| 17 | 2021 | 24 | |
| 18 | 2016 | 23 | |
| 19 | 2015 | 22 | |
| 20 | 2014 | 19 |
About Maxine Tan
Maxine Tan is a scholar working on Artificial Intelligence, Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Oncology and Computer Vision and Pattern Recognition, having authored 45 papers that have together received 1.2k indexed citations. Recurring topics across this work include AI in cancer detection (24 papers), Radiomics and Machine Learning in Medical Imaging (14 papers), Digital Radiography and Breast Imaging (13 papers), Lung Cancer Diagnosis and Treatment (7 papers), Global Cancer Incidence and Screening (7 papers), MRI in cancer diagnosis (4 papers), Brain Tumor Detection and Classification (2 papers) and COVID-19 diagnosis using AI (2 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (649 citations), Pulmonary and Respiratory Medicine (505 citations), Artificial Intelligence (545 citations), Health Informatics (13 citations) and Neurology (67 citations). Maxine Tan has collaborated with scholars based in United States, Malaysia and Belgium. Frequent co-authors include Bin Zheng, Hong Liu, Jiantao Pu, Rudi Deklerck, Jan Cornelis, Bart Jansen, Michel Bister, Yuchen Qiu, David Gur and Samuel Cheng. Their work appears in journals such as Medical Physics, Physics in Medicine and Biology, International Journal of Computer Assisted Radiology and Surgery, Journal of Magnetic Resonance Imaging and Cancers.
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.