James Monaco
Impact in
- Biophysics top 2%
- Cell Image Analysis Techniques
- Health Informatics top 10%
Papers in
-
- AI in cancer detection 17
- Bayesian Methods and Mixture Models 5
-
- Medical Image Segmentation Techniques 10
- Image Retrieval and Classification Techniques 4
- Optical measurement and interference techniques 3
- Digital Imaging for Blood Diseases 3
- Co-authors
- Anant Madabhushi (26 shared papers)Michael D. Feldman (11 shared papers)Ajay Basavanhally (4 shared papers)Shridar Ganesan (3 shared papers)Gyan Bhanot (2 shared papers)Shannon C. Agner (1 shared paper)J E Tomaszewski (1 shared paper)Scott Doyle (5 shared papers)
- Journals
- Journal of Pathology Informatics (5 papers)Analytical Cellular Pathology (2 papers)Medical Image Analysis (2 papers)IEEE Transactions on Biomedical Engineering (1 paper)IEEE Transactions on Medical Imaging (1 paper)
- Partner nations
- United StatesNetherlandsCanada
In The Last Decade
James Monaco
37 papers receiving 817 citations
Peers
Comparison fields: 5 of 93
- Biophysics 125
- Health Informatics 21
- Computer Vision and Pattern Recognition 339
- Artificial Intelligence 523
- Radiology, Nuclear Medicine and Imaging 218
Countries citing papers authored by James Monaco
This map shows the geographic impact of James Monaco'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 James Monaco with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Monaco more than expected).
Fields of papers citing papers by James Monaco
This network shows the impact of papers produced by James Monaco. 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 James Monaco. The network helps show where James Monaco may publish in the future.
Co-authors
The 25 scholars most cited alongside James Monaco, 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 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 226 | |
| 2 | 2010 | 99 | |
| 3 | 2011 | 62 | |
| 4 | 2011 | 56 | |
| 5 | 2009 | 36 | |
| 6 | 2010 | 33 | |
| 7 | 2009 | 30 | |
| 8 | 2012 | 26 | |
| 9 | 2012 | 24 | |
| 10 | 2010 | 21 | |
| 11 | 2011 | 16 | |
| 12 | 2020 | 15 | |
| 13 | 2011 | 15 | |
| 14 | 2012 | 14 | |
| 15 | 2012 | 13 | |
| 16 | 2018 | 12 | |
| 17 | 2009 | 12 | |
| 18 | 2010 | 12 | |
| 19 | 2012 | 11 | |
| 20 | 2008 | 11 |
About James Monaco
James Monaco is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Oncology and Media Technology, having authored 38 papers that have together received 841 indexed citations. Recurring topics across this work include AI in cancer detection (17 papers), Medical Image Segmentation Techniques (10 papers), Bayesian Methods and Mixture Models (5 papers), Colorectal Cancer Screening and Detection (4 papers), Radiomics and Machine Learning in Medical Imaging (4 papers), Image Retrieval and Classification Techniques (4 papers), Optical measurement and interference techniques (3 papers) and Digital Imaging for Blood Diseases (3 papers). The work is most often cited by research in Biophysics (125 citations), Health Informatics (21 citations), Computer Vision and Pattern Recognition (339 citations), Artificial Intelligence (523 citations) and Radiology, Nuclear Medicine and Imaging (218 citations). James Monaco has collaborated with scholars based in United States, Netherlands and Canada. Frequent co-authors include Anant Madabhushi, Michael D. Feldman, Ajay Basavanhally, Shridar Ganesan, Gyan Bhanot, Shannon C. Agner, J E Tomaszewski, Scott Doyle, John Tomaszewski and Ulysses J. Balis. Their work appears in journals such as Journal of Pathology Informatics, Analytical Cellular Pathology, Medical Image Analysis, IEEE Transactions on Biomedical Engineering and IEEE Transactions on Medical Imaging.
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.