Sergio Uribe

3.8k total citations
151 papers, 2.5k citations indexed

About

Sergio Uribe is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Epidemiology. According to data from OpenAlex, Sergio Uribe has authored 151 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 79 papers in Radiology, Nuclear Medicine and Imaging, 53 papers in Cardiology and Cardiovascular Medicine and 34 papers in Epidemiology. Recurrent topics in Sergio Uribe's work include Advanced MRI Techniques and Applications (67 papers), Cardiovascular Function and Risk Factors (31 papers) and Cardiac Valve Diseases and Treatments (26 papers). Sergio Uribe is often cited by papers focused on Advanced MRI Techniques and Applications (67 papers), Cardiovascular Function and Risk Factors (31 papers) and Cardiac Valve Diseases and Treatments (26 papers). Sergio Uribe collaborates with scholars based in Chile, United Kingdom and Spain. Sergio Uribe's co-authors include Cristián Tejos, Reza Razavi, Tobias Schaeffter, Marcelo E. Andía, Pablo Irarrázaval, Israel Valverde, Julio Sotelo, Philipp Beerbaum, Gerald Greil and Cristóbal Arrieta and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American College of Cardiology and IEEE Transactions on Pattern Analysis and Machine Intelligence.

In The Last Decade

Sergio Uribe

135 papers receiving 2.4k citations

Peers

Sergio Uribe
Maria Drangova Canada
Xiaodan Zhao China
Pierre Croisille France
Declan P. O’Regan United Kingdom
Brett R. Cowan New Zealand
Evrim Türkbey United States
William C. Hunter United States
Jack Lee United Kingdom
Valmik Bhargava United States
Lei Xu China
Maria Drangova Canada
Sergio Uribe
Citations per year, relative to Sergio Uribe Sergio Uribe (= 1×) peers Maria Drangova

Countries citing papers authored by Sergio Uribe

Since Specialization
Citations

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

Fields of papers citing papers by Sergio Uribe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sergio Uribe

This figure shows the co-authorship network connecting the top 25 collaborators of Sergio Uribe. A scholar is included among the top collaborators of Sergio Uribe 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 Sergio Uribe. Sergio Uribe 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.
2.
Salas, Rodrigo, Rienzi Díaz‐Navarro, Stéren Chabert, et al.. (2025). AI Applied to Cardiac Magnetic Resonance for Precision Medicine in Coronary Artery Disease: A Systematic Review. Journal of Cardiovascular Development and Disease. 12(9). 345–345. 1 indexed citations
3.
Caulier‐Cisterna, Raúl, et al.. (2024). Comparison of LED- and LASER-based fNIRS technologies to record the human peri‑spinal cord neurovascular response. Medical Engineering & Physics. 127(1). 104170–104170. 1 indexed citations
4.
Dunstan, Jocelyn, et al.. (2024). Physics-informed neural networks for parameter estimation in blood flow models. Computers in Biology and Medicine. 178. 108706–108706. 11 indexed citations
5.
Uribe, Sergio, et al.. (2024). Denoising of dual‐VENC PC‐MRI with large high/low VENC ratios. Magnetic Resonance in Medicine. 93(1). 353–368.
6.
Araya, Rodolfo, et al.. (2023). Convergence analysis of pressure reconstruction methods from discrete velocities. ESAIM. Mathematical modelling and numerical analysis. 57(3). 1839–1861. 4 indexed citations
7.
Milovic, Carlos, Lambert Mathias, Cristóbal Arrieta, et al.. (2023). Toward a realistic in silico abdominal phantom for QSM. Magnetic Resonance in Medicine. 89(6). 2402–2418. 4 indexed citations
8.
Uribe, Sergio, et al.. (2023). A comparison of phase unwrapping methods in velocity‐encoded MRI for aortic flows. Magnetic Resonance in Medicine. 90(5). 2102–2115. 3 indexed citations
9.
Messina, Pablo, Denis Parra, Álvaro Soto, et al.. (2022). A Survey on Deep Learning and Explainability for Automatic Report Generation from Medical Images. ACM Computing Surveys. 54(10s). 1–40. 46 indexed citations
10.
Sotelo, Julio, et al.. (2022). Assessment of 4D flow MRI's quality by verifying its Navier–Stokes compatibility. International Journal for Numerical Methods in Biomedical Engineering. 38(6). e3603–e3603. 3 indexed citations
11.
Huertas, José I., et al.. (2021). Campus City Project: Challenge Living Lab for Smart Cities. Applied Sciences. 11(23). 11085–11085. 21 indexed citations
12.
Sotelo, Julio, et al.. (2021). Three‐dimensional quantification of circulation using finite‐element methods in four‐dimensional flow MR data of the thoracic aorta. Magnetic Resonance in Medicine. 87(2). 1036–1045. 2 indexed citations
13.
Ciampi, Ethel, et al.. (2021). Regional brain atrophy is related to social cognition impairment in multiple sclerosis. Arquivos de Neuro-Psiquiatria. 79(8). 666–675. 3 indexed citations
14.
Zacconi, Flavia C., Daniel Cabrera, Marco Arrese, et al.. (2019). Intrahepatic fatty acids composition as a biomarker of NAFLD progression from steatosis to NASH by using1H-MRS. RSC Advances. 9(72). 42132–42139. 7 indexed citations
15.
Burris, Nicholas S., David Nordsletten, Julio Sotelo, et al.. (2019). False lumen ejection fraction predicts growth in type B aortic dissection: preliminary results. European Journal of Cardio-Thoracic Surgery. 57(5). 896–903. 40 indexed citations
16.
Zhong, Liang, Eric Schrauben, Julio García, et al.. (2019). Intracardiac 4D Flow MRI in Congenital Heart Disease: Recommendations on Behalf of the ISMRM Flow & Motion Study Group. Journal of Magnetic Resonance Imaging. 50(3). 25 indexed citations
17.
Zhong, Liang, Eric Schrauben, Julio García, et al.. (2019). Intracardiac 4D Flow MRI in Congenital Heart Disease: Recommendations on Behalf of the ISMRM Flow & Motion Study Group. Journal of Magnetic Resonance Imaging. 50(3). 677–681. 38 indexed citations
18.
Arab, Juan Pablo, Francisco Barrera, Juan P. Valderas, et al.. (2017).  High prevalence of undiagnosed liver cirrhosis and advanced fibrosis in type 2 diabetic patients.. SHILAP Revista de lepidopterología. 15(5). 721–8. 33 indexed citations
19.
Uribe, Sergio, Cristián Tejos, Reza Razavi, & Tobias Schaeffter. (2011). New respiratory gating technique for whole heart cine imaging: Integration of a navigator slice in steady state free precession sequences. Journal of Magnetic Resonance Imaging. 34(1). 211–219. 9 indexed citations
20.
Clough, Rachel E., T. Carrell, Sergio Uribe, et al.. (2011). Flow-sensitised dynamic magnetic resonance imaging (MRI) can identify dominant false lumen flow and secondary entry tears in type B aortic dissection: implications for endovascular treatment. British journal of surgery. 98. 10–11. 2 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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