Felipe Giuste

916 total citations
36 papers, 519 citations indexed

About

Felipe Giuste is a scholar working on Radiology, Nuclear Medicine and Imaging, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Felipe Giuste has authored 36 papers receiving a total of 519 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Radiology, Nuclear Medicine and Imaging, 10 papers in Molecular Biology and 9 papers in Artificial Intelligence. Recurrent topics in Felipe Giuste's work include COVID-19 diagnosis using AI (9 papers), Machine Learning in Healthcare (6 papers) and Artificial Intelligence in Healthcare and Education (6 papers). Felipe Giuste is often cited by papers focused on COVID-19 diagnosis using AI (9 papers), Machine Learning in Healthcare (6 papers) and Artificial Intelligence in Healthcare and Education (6 papers). Felipe Giuste collaborates with scholars based in United States, Japan and Switzerland. Felipe Giuste's co-authors include May D. Wang, Wenqi Shi, Yuanda Zhu, Monica Isgut, Tong Li, Matthew J. Brooks, Anand Swaroop, Gökhan Karakülah, Vijender Chaitankar and Ying Sha and has published in prestigious journals such as Journal of Clinical Oncology, Blood and PLoS ONE.

In The Last Decade

Felipe Giuste

34 papers receiving 509 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Felipe Giuste United States 11 225 94 82 72 44 36 519
Haoyang Li China 15 323 1.4× 134 1.4× 146 1.8× 53 0.7× 34 0.8× 38 720
Markus Wolfien Germany 14 259 1.2× 56 0.6× 29 0.4× 33 0.5× 39 0.9× 56 488
Lorenz Adlung Germany 8 243 1.1× 58 0.6× 35 0.4× 22 0.3× 47 1.1× 15 455
Michal Ozery-Flato Israel 10 136 0.6× 96 1.0× 38 0.5× 23 0.3× 88 2.0× 22 347
Jerome Cheng United States 14 117 0.5× 305 3.2× 185 2.3× 59 0.8× 41 0.9× 49 627
Benjamin Ulfenborg Sweden 10 193 0.9× 124 1.3× 95 1.2× 16 0.2× 23 0.5× 26 560
Matthew A. Summers Australia 13 142 0.6× 99 1.1× 80 1.0× 13 0.2× 20 0.5× 16 555
Sandra Steyaert Belgium 9 694 3.1× 74 0.8× 82 1.0× 24 0.3× 97 2.2× 20 984
Ken Asada Japan 22 521 2.3× 222 2.4× 335 4.1× 153 2.1× 35 0.8× 44 1.3k

Countries citing papers authored by Felipe Giuste

Since Specialization
Citations

This map shows the geographic impact of Felipe Giuste'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 Felipe Giuste with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Felipe Giuste more than expected).

Fields of papers citing papers by Felipe Giuste

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Felipe Giuste. 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 Felipe Giuste. The network helps show where Felipe Giuste may publish in the future.

Co-authorship network of co-authors of Felipe Giuste

This figure shows the co-authorship network connecting the top 25 collaborators of Felipe Giuste. A scholar is included among the top collaborators of Felipe Giuste 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 Felipe Giuste. Felipe Giuste is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Shi, Wenqi, et al.. (2025). Predicting pediatric patient rehabilitation outcomes after spinal deformity surgery with artificial intelligence. Communications Medicine. 5(1). 1–1. 5 indexed citations
2.
Tan, See Mieng, et al.. (2025). FHIR in Focus: Enabling Biomedical Data Harmonization for Intelligent Healthcare Systems. IEEE Reviews in Biomedical Engineering. 19. 305–336.
3.
Isgut, Monica, et al.. (2024). Identifying and characterizing disease subpopulations that most benefit from polygenic risk scores. Scientific Reports. 14(1). 22124–22124. 2 indexed citations
4.
Giuste, Felipe, et al.. (2024). Optimized Clinical Feature Analysis for Improved Cardiovascular Disease Risk Screening. IEEE Open Journal of Engineering in Medicine and Biology. 5. 816–827. 4 indexed citations
5.
Giuste, Felipe, Yuanda Zhu, Wenqi Shi, et al.. (2023). Explainable synthetic image generation to improve risk assessment of rare pediatric heart transplant rejection. Journal of Biomedical Informatics. 139. 104303–104303. 12 indexed citations
6.
Giuste, Felipe, et al.. (2023). Early and fair COVID-19 outcome risk assessment using robust feature selection. Scientific Reports. 13(1). 18981–18981. 7 indexed citations
7.
Sun, Jimin, et al.. (2023). Improving explainable AI with patch perturbation-based evaluation pipeline: a COVID-19 X-ray image analysis case study. Scientific Reports. 13(1). 19488–19488. 10 indexed citations
8.
Shi, Wenqi, Felipe Giuste, Yuanda Zhu, et al.. (2022). Development of a generalizable multi-site and multi-modality clinical data cloud infrastructure for pediatric patient care. 1–10. 8 indexed citations
9.
Allam, Mayar, et al.. (2022). Development of Machine Learning Regression Model for COVID-19 Drug Target Prediction. 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 2808–2815. 3 indexed citations
10.
Giuste, Felipe, Wenqi Shi, Yuanda Zhu, et al.. (2022). Explainable Artificial Intelligence Methods in Combating Pandemics: A Systematic Review. IEEE Reviews in Biomedical Engineering. 16. 5–21. 84 indexed citations
11.
Moghanaki, Drew, William A. Stokes, Madhusmita Behera, et al.. (2021). Association of concomitant NSAID and immunotherapy on outcomes in patients with non-small cell lung cancer: Analysis of the National Veterans Health Administration Database.. Journal of Clinical Oncology. 39(15_suppl). 9107–9107. 2 indexed citations
12.
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14.
Zhang, Luyuan, et al.. (2020). Radiomics Features Predict CIC Mutation Status in Lower Grade Glioma. Frontiers in Oncology. 10. 937–937. 25 indexed citations
15.
Giuste, Felipe, et al.. (2019). Digital imaging applications and informatics in dermatology. Seminars in Cutaneous Medicine and Surgery. 38(1). E43–E49.
16.
Sharma, Nitya V., Kathryn L. Pellegrini, Véronique Ouellet, et al.. (2018). Identification of the Transcription Factor Relationships Associated with Androgen Deprivation Therapy Response and Metastatic Progression in Prostate Cancer. Cancers. 10(10). 379–379. 28 indexed citations
17.
Harati, Sahar, Lee Cooper, Felipe Giuste, et al.. (2017). MEDICI: Mining Essentiality Data to Identify Critical Interactions for Cancer Drug Target Discovery and Development. PLoS ONE. 12(1). e0170339–e0170339. 4 indexed citations
18.
Kim, Jung-Woong, Hyun‐Jin Yang, Matthew J. Brooks, et al.. (2016). NRL-Regulated Transcriptome Dynamics of Developing Rod Photoreceptors. Cell Reports. 17(9). 2460–2473. 91 indexed citations
19.
Chaitankar, Vijender, Gökhan Karakülah, Rinki Ratnapriya, et al.. (2016). Next generation sequencing technology and genomewide data analysis: Perspectives for retinal research. Progress in Retinal and Eye Research. 55. 1–31. 55 indexed citations
20.
Schuettpelz, Laura G., et al.. (2012). Kruppel-like factor 7 overexpression suppresses hematopoietic stem and progenitor cell function. Blood. 120(15). 2981–2989. 41 indexed citations

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.

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