Victoria L. Mango
- Health Informatics top 1%
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- MRI in cancer diagnosis 15
- Radiomics and Machine Learning in Medical Imaging 12
- Cancer Research top 5%
- Breast Cancer Treatment Studies 22
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- Breast Lesions and Carcinomas 23
- Artificial Intelligence top 5%
- AI in cancer detection 17
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- Global Cancer Incidence and Screening 21
- Colorectal Cancer Screening and Detection 8
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- Digital Radiography and Breast Imaging 21
- Co-authors
- Richard HaRalph WynnSheldon FeldmanElizabeth A. MorrisMaxine S. JochelsonLauren FriedlanderDelia M. KeatingCynthia Thornton
- Partner nations
- United StatesNigeriaSwitzerland
In The Last Decade
Victoria L. Mango
65 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 93
- Health Informatics 90
- Radiology, Nuclear Medicine and Imaging 620
- Cancer Research 386
- Pathology and Forensic Medicine 381
- Artificial Intelligence 272
Countries citing papers authored by Victoria L. Mango
This map shows the geographic impact of Victoria L. Mango'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 Victoria L. Mango with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Victoria L. Mango more than expected).
Fields of papers citing papers by Victoria L. Mango
This network shows the impact of papers produced by Victoria L. Mango. 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 Victoria L. Mango. The network helps show where Victoria L. Mango may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Victoria L. Mango, 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 | 4 | |
| 4 | 2024 | 9 | |
| 5 | 2024 | 2 | |
| 6 | 2024 | 1 | |
| 7 | 2023 | 10 | |
| 8 | 2023 | 3 | |
| 9 | 2023 | 1 | |
| 10 | 2023 | 27 | |
| 11 | 2023 | 0 | |
| 12 | 2023 | 17 | |
| 13 | 2023 | 11 | |
| 14 | 2023 | 1 | |
| 15 | 2022 | 1 | |
| 16 | 2020 | 5 | |
| 17 | 2018 | 4 | |
| 18 | 2018 | 10 | |
| 19 | 2017 | 42 | |
| 20 | 2016 | 9 |
About Victoria L. Mango
Victoria L. Mango is a scholar working on Cancer Research, Radiology, Nuclear Medicine and Imaging and Pathology and Forensic Medicine, having authored 72 papers that have together received 1.2k indexed citations. Recurring topics across this work include Breast Lesions and Carcinomas (23 papers), Breast Cancer Treatment Studies (22 papers), Global Cancer Incidence and Screening (21 papers), Digital Radiography and Breast Imaging (21 papers), AI in cancer detection (17 papers), MRI in cancer diagnosis (15 papers), Radiomics and Machine Learning in Medical Imaging (12 papers) and Colorectal Cancer Screening and Detection (8 papers). The work is most often cited by research in Health Informatics (90 citations), Radiology, Nuclear Medicine and Imaging (620 citations) and Cancer Research (386 citations). Victoria L. Mango has collaborated with scholars based in United States, Nigeria and Switzerland. Frequent co-authors include Richard Ha, Ralph Wynn, Sheldon Feldman, Elizabeth A. Morris, Maxine S. Jochelson, Lauren Friedlander, Delia M. Keating, Cynthia Thornton, Elise Desperito and Chaya S. Moskowitz. Their work appears in journals such as PLoS ONE, Radiology and American Journal of Roentgenology.
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.