Paula Toro
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Radiomics and Machine Learning in Medical Imaging
Papers in
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- Radiomics and Machine Learning in Medical Imaging 13
- Oncology 12
- Cancer Immunotherapy and Biomarkers 8
- Co-authors
- Anant Madabhushi (21 shared papers)Germán Corredor (17 shared papers)Vidya Sankar Viswanathan (6 shared papers)Sanjay Mukhopadhyay (2 shared papers)Cheng Lu (6 shared papers)Pingfu Fu (11 shared papers)Kaustav Bera (6 shared papers)Aparna Harbhajanka (3 shared papers)
- Journals
- Journal of Clinical Oncology (6 papers)Journal of Personalized Medicine (1 paper)Clinical Breast Cancer (1 paper)The Lancet Digital Health (1 paper)Applied immunohistochemistry & molecular morphology (1 paper)
- Partner nations
- United StatesSwitzerlandColombia
In The Last Decade
Paula Toro
26 papers receiving 251 citations
Peers
Comparison fields: 5 of 53
- Health Informatics 22
- Radiology, Nuclear Medicine and Imaging 100
- Otorhinolaryngology 16
- Biophysics 18
- Artificial Intelligence 86
Countries citing papers authored by Paula Toro
This map shows the geographic impact of Paula Toro'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 Paula Toro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paula Toro more than expected).
Fields of papers citing papers by Paula Toro
This network shows the impact of papers produced by Paula Toro. 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 Paula Toro. The network helps show where Paula Toro may publish in the future.
Co-authors
The 25 scholars most cited alongside Paula Toro, 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 60 | |
| 2 | 2021 | 45 | |
| 3 | 2022 | 33 | |
| 4 | 2021 | 24 | |
| 5 | 2023 | 17 | |
| 6 | 2023 | 14 | |
| 7 | 2022 | 13 | |
| 8 | 2022 | 12 | |
| 9 | 2022 | 8 | |
| 10 | 2024 | 4 | |
| 11 | 2021 | 3 | |
| 12 | [Clomipramine dependence in a drug addict. 1st case]. | 1989 | 3 |
| 13 | 2021 | 3 | |
| 14 | 2013 | 2 | |
| 15 | 2021 | 2 | |
| 16 | 2020 | 2 | |
| 17 | 2022 | 1 | |
| 18 | 2021 | 1 | |
| 19 | 2024 | 1 | |
| 20 | 2022 | 1 |
About Paula Toro
Paula Toro is a scholar working on Radiology, Nuclear Medicine and Imaging, Oncology, Artificial Intelligence, Pulmonary and Respiratory Medicine and Surgery, having authored 28 papers that have together received 255 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (13 papers), AI in cancer detection (9 papers), Cancer Immunotherapy and Biomarkers (8 papers), Head and Neck Cancer Studies (3 papers), Ferroptosis and cancer prognosis (2 papers), Breast Cancer Treatment Studies (2 papers), Lung Cancer Diagnosis and Treatment (2 papers) and Esophageal Cancer Research and Treatment (2 papers). The work is most often cited by research in Health Informatics (22 citations), Radiology, Nuclear Medicine and Imaging (100 citations), Otorhinolaryngology (16 citations), Biophysics (18 citations) and Artificial Intelligence (86 citations). Paula Toro has collaborated with scholars based in United States, Switzerland and Colombia. Frequent co-authors include Anant Madabhushi, Germán Corredor, Vidya Sankar Viswanathan, Sanjay Mukhopadhyay, Cheng Lu, Pingfu Fu, Kaustav Bera, Aparna Harbhajanka, Hannah Gilmore and Lori J. Goldstein. Their work appears in journals such as Journal of Clinical Oncology, Journal of Personalized Medicine, Clinical Breast Cancer, The Lancet Digital Health and Applied immunohistochemistry & molecular morphology.
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.