John Mongan
- Radiology, Nuclear Medicine and Imaging top 2%
- Pulmonary and Respiratory Medicine top 10%
- Biomedical Engineering
- Health Informatics top 0.5%
- Artificial Intelligence top 10%
- Co-authors
- Andrew TaylorClinton MielkeMarc KohliAkash P. KansagraJohn‐Paul J. YuDongwei GaoAlvin RajkomarYanjun Fu
- Topics
- Radiomics and Machine Learning in Medical Imaging (16 papers)Artificial Intelligence in Healthcare and Education (13 papers)Radiology practices and education (13 papers)
- Cited by
- Health InformaticsRadiology, Nuclear Medicine and ImagingCritical Care and Intensive Care Medicine
- Partner nations
- United StatesCanadaAustralia
In The Last Decade
John Mongan
46 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 115
- Radiology, Nuclear Medicine and Imaging 741
- Pulmonary and Respiratory Medicine 255
- Biomedical Engineering 231
- Health Informatics 209
- Artificial Intelligence 183
Countries citing papers authored by John Mongan
This map shows the geographic impact of John Mongan'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 John Mongan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Mongan more than expected).
Fields of papers citing papers by John Mongan
This network shows the impact of papers produced by John Mongan. 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 John Mongan. The network helps show where John Mongan may publish in the future.
Co-authorship network of co-authors of John Mongan
This figure shows the co-authorship network connecting the top 25 collaborators of John Mongan. A scholar is included among the top collaborators of John Mongan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with John Mongan. John Mongan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 10 | |
| 3 | 4 | |
| 4 | 6 | |
| 5 | 26 | |
| 6 | 1 | |
| 7 | 12 | |
| 8 | 9 | |
| 9 | 9 | |
| 10 | 25 | |
| 11 | 2 | |
| 12 | 4 | |
| 13 | 7 | |
| 14 | 33 | |
| 15 | 7 | |
| 16 | 1 | |
| 17 | 19 | |
| 18 | 64 | |
| 19 | 38 | |
| 20 | 50 |
About John Mongan
John Mongan is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Health Information Management, having authored 47 papers that have together received 1.1k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (16 papers), Artificial Intelligence in Healthcare and Education (13 papers) and Radiology practices and education (13 papers). The work is most often cited by research in Health Informatics (209 citations), Radiology, Nuclear Medicine and Imaging (741 citations) and Critical Care and Intensive Care Medicine (64 citations). John Mongan has collaborated with scholars based in United States, Canada and Australia. Frequent co-authors include Andrew Taylor, Clinton Mielke, Marc Kohli, Akash P. Kansagra, John‐Paul J. Yu, Dongwei Gao, Alvin Rajkomar, Yanjun Fu, Benjamin M. Yeh and Kimberly Kallianos. Their work appears in journals such as Annals of Internal Medicine, Radiology and The Journal of Urology.
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.