Maryellen L. Giger
- Radiology, Nuclear Medicine and Imaging top 0.01%
- Artificial Intelligence top 0.05%
- Pulmonary and Respiratory Medicine top 0.2%
- Computer Vision and Pattern Recognition top 0.2%
- Biomedical Engineering top 1%
- Co-authors
- Kunio DoiHui LiCarl J. VybornyKaren DrukkerHeber MacMahonCharles E. MetzUlrich BickRobert M. Nishikawa
- Topics
- Radiomics and Machine Learning in Medical Imaging (244 papers)AI in cancer detection (229 papers)MRI in cancer diagnosis (86 papers)
- Journals
- Journal of Clinical InvestigationSHILAP Revista de lepidopterologíaNature Immunology
- Partner nations
- United StatesChinaGermany
In The Last Decade
Maryellen L. Giger
460 papers receiving 17.9k citations
Hit Papers
Peers
Comparison fields: 5 of 195
- Radiology, Nuclear Medicine and Imaging 12.5k
- Artificial Intelligence 9.3k
- Pulmonary and Respiratory Medicine 5.2k
- Computer Vision and Pattern Recognition 3.3k
- Biomedical Engineering 2.3k
Countries citing papers authored by Maryellen L. Giger
This map shows the geographic impact of Maryellen L. Giger'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 Maryellen L. Giger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maryellen L. Giger more than expected).
Fields of papers citing papers by Maryellen L. Giger
This network shows the impact of papers produced by Maryellen L. Giger. 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 Maryellen L. Giger. The network helps show where Maryellen L. Giger may publish in the future.
Co-authorship network of co-authors of Maryellen L. Giger
This figure shows the co-authorship network connecting the top 25 collaborators of Maryellen L. Giger. A scholar is included among the top collaborators of Maryellen L. Giger 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 Maryellen L. Giger. Maryellen L. Giger is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 4 | |
| 5 | 1 | |
| 6 | 4 | |
| 7 | 1 | |
| 8 | 9 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | Criteria for the translation of radiomics into clinically useful testsbreakdown → | 127 |
| 12 | 31 | |
| 13 | 6 | |
| 14 | Medical Imaging and Data Resource Center: Imaging in Covid | 2 |
| 15 | 24 | |
| 16 | Correlative Analysis of FFDM and DCE-MRI for Improved Breast CADx | 8 |
| 17 | 69 | |
| 18 | 155 | |
| 19 | Investigation of regularized neural networks for the computerized detection of mass lesions in digital mammograms | 3 |
| 20 | 44 |
About Maryellen L. Giger
Maryellen L. Giger is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Artificial Intelligence, having authored 477 papers that have together received 18.6k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (244 papers), AI in cancer detection (229 papers) and MRI in cancer diagnosis (86 papers). The work is most often cited by research in Health Informatics (877 citations), Radiology, Nuclear Medicine and Imaging (12.5k citations) and Artificial Intelligence (9.3k citations). Maryellen L. Giger has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Kunio Doi, Hui Li, Carl J. Vyborny, Karen Drukker, Heber MacMahon, Charles E. Metz, Ulrich Bick, Robert M. Nishikawa, Benjamin Q. Huynh and Robert A. Schmidt. Their work appears in journals such as Journal of Clinical Investigation, SHILAP Revista de lepidopterología and Nature Immunology.
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.