John Arévalo
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
- Retinal Imaging and Analysis
- Artificial Intelligence top 2%
- AI in cancer detection
Papers in
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- Digital Imaging for Blood Diseases 5
- Advanced Image and Video Retrieval Techniques 5
- Image Retrieval and Classification Techniques 5
- Multimodal Machine Learning Applications 4
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- AI in cancer detection 12
- Co-authors
- Fabio A. González (21 shared papers)Ángel Cruz-Roa (10 shared papers)Raúl Ramos-Pollán (5 shared papers)Miguel Guevara (2 shared papers)José Luís Oliveira (2 shared papers)Anant Madabhushi (4 shared papers)Thamar Solorio (3 shared papers)Manuel Montes-y-Gómez (3 shared papers)
- Journals
- Nature Communications (2 papers)Artificial Intelligence in Medicine (1 paper)SLAS DISCOVERY (1 paper)PLoS Computational Biology (1 paper)Computer Methods and Programs in Biomedicine (1 paper)
- Partner nations
- ColombiaUnited StatesMexico
In The Last Decade
John Arévalo
34 papers receiving 1.2k citations
John Arévalo's Hit Papers
Peers
Comparison fields: 5 of 106
- Radiology, Nuclear Medicine and Imaging 537
- Artificial Intelligence 841
- Health Informatics 29
- Computer Vision and Pattern Recognition 458
- Biophysics 103
Countries citing papers authored by John Arévalo
This map shows the geographic impact of John Arévalo'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 John Arévalo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Arévalo more than expected).
Fields of papers citing papers by John Arévalo
This network shows the impact of papers produced by John Arévalo. 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 John Arévalo. The network helps show where John Arévalo may publish in the future.
Co-authors
The 25 scholars most cited alongside John Arévalo, 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 36 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Representation learning for mammography mass lesion classification with convolutional neural networks Hit paper breakdown → | 2016 | 369 |
| 2 | 2013 | 308 | |
| 3 | 2015 | 113 | |
| 4 | 2015 | 74 | |
| 5 | 2020 | 68 | |
| 6 | 2016 | 44 | |
| 7 | 2014 | 33 | |
| 8 | 2017 | 28 | |
| 9 | 2024 | 27 | |
| 10 | 2015 | 24 | |
| 11 | 2012 | 23 | |
| 12 | 2017 | 22 | |
| 13 | HISTOPATHOLOGY IMAGE REPRESENTATION FOR AUTOMATIC ANALYSIS: A STATE-OF-THE-ART REVIEW | 2014 | 22 |
| 14 | 2015 | 21 | |
| 15 | 2017 | 19 | |
| 16 | 2022 | 12 | |
| 17 | 2015 | 12 | |
| 18 | 2013 | 11 | |
| 19 | 2012 | 9 | |
| 20 | 2014 | 9 |
About John Arévalo
John Arévalo is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Radiology, Nuclear Medicine and Imaging, Biophysics and Biomedical Engineering, having authored 36 papers that have together received 1.3k indexed citations. Recurring topics across this work include AI in cancer detection (12 papers), Cell Image Analysis Techniques (8 papers), Digital Imaging for Blood Diseases (5 papers), Radiomics and Machine Learning in Medical Imaging (5 papers), Advanced Image and Video Retrieval Techniques (5 papers), Image Retrieval and Classification Techniques (5 papers), Retinal Imaging and Analysis (4 papers) and Multimodal Machine Learning Applications (4 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (537 citations), Artificial Intelligence (841 citations), Health Informatics (29 citations), Computer Vision and Pattern Recognition (458 citations) and Biophysics (103 citations). John Arévalo has collaborated with scholars based in Colombia, United States and Mexico. Frequent co-authors include Fabio A. González, Ángel Cruz-Roa, Raúl Ramos-Pollán, Miguel Guevara, José Luís Oliveira, Anant Madabhushi, Thamar Solorio, Manuel Montes-y-Gómez, Eduardo Romero and Oscar Perdómo. Their work appears in journals such as Nature Communications, Artificial Intelligence in Medicine, SLAS DISCOVERY, PLoS Computational Biology and Computer Methods and Programs in Biomedicine.
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.