Ángel Cruz-Roa
- Artificial Intelligence top 1%
- Radiology, Nuclear Medicine and Imaging top 2%
- Computer Vision and Pattern Recognition top 1%
- Oncology
- Biophysics top 1%
- Co-authors
- Fabio A. GonzálezAnant MadabhushiAjay BasavanhallyJohn TomaszewskiHannah GilmoreNatalie ShihJohn ArévaloShridar Ganesan
- Topics
- AI in cancer detection (24 papers)Digital Imaging for Blood Diseases (11 papers)Radiomics and Machine Learning in Medical Imaging (7 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
- Partner nations
- ColombiaUnited StatesMexico
In The Last Decade
Ángel Cruz-Roa
33 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 115
- Artificial Intelligence 1.4k
- Radiology, Nuclear Medicine and Imaging 852
- Computer Vision and Pattern Recognition 776
- Oncology 227
- Biophysics 206
Countries citing papers authored by Ángel Cruz-Roa
This map shows the geographic impact of Ángel Cruz-Roa'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 Ángel Cruz-Roa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ángel Cruz-Roa more than expected).
Fields of papers citing papers by Ángel Cruz-Roa
This network shows the impact of papers produced by Ángel Cruz-Roa. 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 Ángel Cruz-Roa. The network helps show where Ángel Cruz-Roa may publish in the future.
Co-authorship network of co-authors of Ángel Cruz-Roa
This figure shows the co-authorship network connecting the top 25 collaborators of Ángel Cruz-Roa. A scholar is included among the top collaborators of Ángel Cruz-Roa 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 Ángel Cruz-Roa. Ángel Cruz-Roa 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 | 0 | |
| 3 | 2 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 2 | |
| 9 | 2 | |
| 10 | 95 | |
| 11 | Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extentbreakdown → | 349 |
| 12 | 3 | |
| 13 | 66 | |
| 14 | 9 | |
| 15 | HISTOPATHOLOGY IMAGE REPRESENTATION FOR AUTOMATIC ANALYSIS: A STATE-OF-THE-ART REVIEW | 18 |
| 16 | 249 | |
| 17 | 267 | |
| 18 | 19 | |
| 19 | 8 | |
| 20 | 94 |
About Ángel Cruz-Roa
Ángel Cruz-Roa is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biophysics, having authored 40 papers that have together received 1.8k indexed citations. Recurring topics across this work include AI in cancer detection (24 papers), Digital Imaging for Blood Diseases (11 papers) and Radiomics and Machine Learning in Medical Imaging (7 papers). The work is most often cited by research in Health Informatics (72 citations), Artificial Intelligence (1.4k citations) and Computer Vision and Pattern Recognition (776 citations). Ángel Cruz-Roa has collaborated with scholars based in Colombia, United States and Mexico. Frequent co-authors include Fabio A. González, Anant Madabhushi, Ajay Basavanhally, John Tomaszewski, Hannah Gilmore, Natalie Shih, John Arévalo, Shridar Ganesan, Michael D. Feldman and Haibo Wang. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.
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.