Jaron Chong
Impact in
- Health Informatics top 0.2%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
- MRI in cancer diagnosis
- Medical Imaging Techniques and Applications
- Radiology practices and education
Papers in
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- Artificial Intelligence in Healthcare and Education 14
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- Radiomics and Machine Learning in Medical Imaging 20
- Radiology practices and education 6
- Cardiac Imaging and Diagnostics 3
- Co-authors
- Caroline ReinholdB. GallixShuo LiAnthony DohanAn TangPeter SavadjievBo ChenMaria Vakalopoulou
- Journals
- Journal of the American College of Radiology (6 papers)European Radiology (4 papers)Medical Image Analysis (4 papers)Journal of Magnetic Resonance Imaging (3 papers)International Journal of Radiation Oncology*Biology*Physics (2 papers)
- Partner nations
- CanadaUnited StatesFrance
In The Last Decade
Jaron Chong
49 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 120
- Health Informatics 293
- Radiology, Nuclear Medicine and Imaging 649
- Internal Medicine 35
- Obstetrics and Gynecology 69
- Artificial Intelligence 209
Countries citing papers authored by Jaron Chong
This map shows the geographic impact of Jaron Chong'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 Jaron Chong with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jaron Chong more than expected).
Fields of papers citing papers by Jaron Chong
This network shows the impact of papers produced by Jaron Chong. 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 Jaron Chong. The network helps show where Jaron Chong may publish in the future.
Co-authors
The 25 scholars most cited alongside Jaron Chong, 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 | 2025 | 0 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 30 | |
| 4 | 2024 | 26 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 4 | |
| 7 | 2023 | 1 | |
| 8 | 2023 | 1 | |
| 9 | 2022 | 3 | |
| 10 | 2021 | 29 | |
| 11 | 2021 | 29 | |
| 12 | 2020 | 32 | |
| 13 | 2019 | 66 | |
| 14 | 2018 | 104 | |
| 15 | 2018 | 26 | |
| 16 | 2018 | 4 | |
| 17 | 2014 | 57 | |
| 18 | 2013 | 23 | |
| 19 | 2012 | 9 | |
| 20 | 2009 | 53 |
About Jaron Chong
Jaron Chong is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging, Internal Medicine, Urology and Biomedical Engineering, having authored 52 papers that have together received 1.2k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (20 papers), Artificial Intelligence in Healthcare and Education (14 papers), Medical Imaging and Analysis (7 papers), Radiology practices and education (6 papers), Advanced Neural Network Applications (4 papers), AI in cancer detection (4 papers), Renal cell carcinoma treatment (3 papers) and Cardiac Imaging and Diagnostics (3 papers). The work is most often cited by research in Health Informatics (293 citations), Radiology, Nuclear Medicine and Imaging (649 citations), Internal Medicine (35 citations), Obstetrics and Gynecology (69 citations) and Artificial Intelligence (209 citations). Jaron Chong has collaborated with scholars based in Canada, United States and France. Frequent co-authors include Caroline Reinhold, B. Gallix, Shuo Li, Anthony Dohan, An Tang, Peter Savadjiev, Bo Chen, Maria Vakalopoulou, Nikos Paragios and Ismail Ben Ayed. Their work appears in journals such as Journal of the American College of Radiology, European Radiology, Medical Image Analysis, Journal of Magnetic Resonance Imaging and International Journal of Radiation Oncology*Biology*Physics.
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.