Marco Guevara-Vega
- Health Informatics top 2%
- Health Information Management top 10%
- Biophysics top 10%
- Spectroscopy Techniques in Biomedical and Chemical Research 4
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- HIV Research and Treatment 1
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- Mosquito-borne diseases and control 7
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- Viral Infections and Vectors 5
- SARS-CoV-2 and COVID-19 Research 1
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- COVID-19 diagnosis using AI 2
- Radiomics and Machine Learning in Medical Imaging 1
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- interferon and immune responses 1
- Co-authors
- Danielle S. BittermanShan ChenHugo J.W.L. AertsRobinson Sabino‐SilvaShalini MoningiBenjamin H. KannGuergana SavovaRaymond H. Mak
- Journals
- Scientific Reports (1 paper)International Journal of Molecular Sciences (1 paper)International Journal of Biological Macromolecules (1 paper)
- Partner nations
- BrazilUnited StatesCanada
In The Last Decade
Marco Guevara-Vega
18 papers receiving 308 citations
Hit Papers
Peers
Comparison fields: 5 of 101
- Health Informatics 71
- Health Information Management 26
- Biophysics 30
- Family Practice 8
- Virology 13
Countries citing papers authored by Marco Guevara-Vega
This map shows the geographic impact of Marco Guevara-Vega'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 Marco Guevara-Vega with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marco Guevara-Vega more than expected).
Fields of papers citing papers by Marco Guevara-Vega
This network shows the impact of papers produced by Marco Guevara-Vega. 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 Marco Guevara-Vega. The network helps show where Marco Guevara-Vega may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Marco Guevara-Vega, 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 | 11 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 4 | |
| 4 | 2024 | 3 | |
| 5 | 2024 | 2 | |
| 6 | Large language models to identify social determinants of health in electronic health recordsbreakdown → | 2024 | 119 |
| 7 | 2024 | 49 | |
| 8 | 2024 | 1 | |
| 9 | 2023 | 9 | |
| 10 | 2023 | 5 | |
| 11 | 2023 | 13 | |
| 12 | 2023 | 8 | |
| 13 | 2023 | 10 | |
| 14 | 2023 | 3 | |
| 15 | 2022 | 5 | |
| 16 | 2022 | 13 | |
| 17 | 2022 | 33 | |
| 18 | 2021 | 17 | |
| 19 | 2016 | 8 |
About Marco Guevara-Vega
Marco Guevara-Vega is a scholar working on Health Informatics, Biophysics and General Dentistry, having authored 19 papers that have together received 313 indexed citations. Recurring topics across this work include Mosquito-borne diseases and control (7 papers), Viral Infections and Vectors (5 papers), Spectroscopy Techniques in Biomedical and Chemical Research (4 papers), COVID-19 diagnosis using AI (2 papers), Radiomics and Machine Learning in Medical Imaging (1 paper), SARS-CoV-2 and COVID-19 Research (1 paper), interferon and immune responses (1 paper) and HIV Research and Treatment (1 paper). The work is most often cited by research in Health Informatics (71 citations), Health Information Management (26 citations) and Biophysics (30 citations). Marco Guevara-Vega has collaborated with scholars based in Brazil, United States and Canada. Frequent co-authors include Danielle S. Bitterman, Shan Chen, Hugo J.W.L. Aerts, Robinson Sabino‐Silva, Shalini Moningi, Benjamin H. Kann, Guergana Savova, Raymond H. Mak, Paul J. Catalano and Jack M. Qian. Their work appears in journals such as Scientific Reports, International Journal of Molecular Sciences and International Journal of Biological Macromolecules.
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.