Jaume Coll‐Font

882 total citations
57 papers, 520 citations indexed

About

Jaume Coll‐Font is a scholar working on Cardiology and Cardiovascular Medicine, Radiology, Nuclear Medicine and Imaging and Electrical and Electronic Engineering. According to data from OpenAlex, Jaume Coll‐Font has authored 57 papers receiving a total of 520 indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Cardiology and Cardiovascular Medicine, 21 papers in Radiology, Nuclear Medicine and Imaging and 9 papers in Electrical and Electronic Engineering. Recurrent topics in Jaume Coll‐Font's work include Cardiac electrophysiology and arrhythmias (25 papers), ECG Monitoring and Analysis (22 papers) and Advanced MRI Techniques and Applications (20 papers). Jaume Coll‐Font is often cited by papers focused on Cardiac electrophysiology and arrhythmias (25 papers), ECG Monitoring and Analysis (22 papers) and Advanced MRI Techniques and Applications (20 papers). Jaume Coll‐Font collaborates with scholars based in United States, Netherlands and Germany. Jaume Coll‐Font's co-authors include Dana H. Brooks, Burak Erem, Rob MacLeod, Wilson Good, Jess Tate, Christopher Nguyen, Linwei Wang, Peter van Dam, Brett Burton and Brian Zenger and has published in prestigious journals such as Circulation, Journal of the American College of Cardiology and Scientific Reports.

In The Last Decade

Jaume Coll‐Font

57 papers receiving 516 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jaume Coll‐Font United States 13 294 210 65 55 34 57 520
Jess Tate United States 13 357 1.2× 109 0.5× 51 0.8× 46 0.8× 38 1.1× 51 480
Ronald Westra Netherlands 12 352 1.2× 69 0.3× 71 1.1× 97 1.8× 38 1.1× 39 630
Axel Loewe Germany 22 1.4k 4.7× 144 0.7× 37 0.6× 241 4.4× 107 3.1× 158 1.7k
Matthias A. F. Gsell Austria 15 590 2.0× 96 0.5× 16 0.2× 204 3.7× 17 0.5× 37 824
Adityo Prakosa United States 22 1.1k 3.7× 243 1.2× 32 0.5× 147 2.7× 24 0.7× 57 1.3k
Caroline H. Roney United Kingdom 21 1.3k 4.4× 192 0.9× 33 0.5× 107 1.9× 66 1.9× 95 1.5k
Dongdong Deng China 10 567 1.9× 114 0.5× 27 0.4× 68 1.2× 12 0.4× 35 691
Fijoy Vadakkumpadan United States 14 1.0k 3.6× 324 1.5× 29 0.4× 136 2.5× 25 0.7× 29 1.2k
Robert Blake United States 8 835 2.8× 155 0.7× 28 0.4× 156 2.8× 20 0.6× 19 999
Jatin Relan France 12 685 2.3× 184 0.9× 18 0.3× 71 1.3× 10 0.3× 29 775

Countries citing papers authored by Jaume Coll‐Font

Since Specialization
Citations

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

Fields of papers citing papers by Jaume Coll‐Font

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jaume Coll‐Font. 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 Jaume Coll‐Font. The network helps show where Jaume Coll‐Font may publish in the future.

Co-authorship network of co-authors of Jaume Coll‐Font

This figure shows the co-authorship network connecting the top 25 collaborators of Jaume Coll‐Font. A scholar is included among the top collaborators of Jaume Coll‐Font 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 Jaume Coll‐Font. Jaume Coll‐Font 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.
Yurista, Salva R., Jaume Coll‐Font, Shi Chen, et al.. (2023). Contrast‐Enhanced Cardiac Magnetic Resonance Imaging With a Manganese‐Based Alternative to Gadolinium for Tissue Characterization of Acute Myocardial Infarction. Journal of the American Heart Association. 12(8). e026923–e026923. 16 indexed citations
2.
Kim, Daeun, Jaume Coll‐Font, Daniel Stäb, et al.. (2023). Single breath‐hold CINE imaging with combined simultaneous multislice and region‐optimized virtual coils. Magnetic Resonance in Medicine. 90(1). 222–230. 2 indexed citations
3.
Herz, Kai, Jaume Coll‐Font, Elizabeth R. Gerstner, et al.. (2022). Accelerated and quantitative three‐dimensional molecular MRI using a generative adversarial network. Magnetic Resonance in Medicine. 89(5). 1901–1914. 13 indexed citations
4.
Yurista, Salva R., Mohammad Rashedul Islam, Yin‐Ching Iris Chen, et al.. (2022). Exercise-induced CITED4 expression is necessary for regional remodeling of cardiac microstructural tissue helicity. Communications Biology. 5(1). 656–656. 6 indexed citations
5.
6.
Eder, R., Salva R. Yurista, Mohammad Rashedul Islam, et al.. (2022). REGIONAL HETEROGENEITY OF EXERCISE-INDUCED CITED4 EXPRESSION IS SPATIALLY LINKED WITH CARDIAC MICROSTRUCTURAL REMODELING CHARACTERIZED BY DIFFUSION TENSOR CARDIAC MAGNETIC RESONANCE. Journal of the American College of Cardiology. 79(9). 1984–1984. 1 indexed citations
7.
Bergquist, Jake, Jaume Coll‐Font, Brian Zenger, et al.. (2022). Reconstruction of cardiac position using body surface potentials. Computers in Biology and Medicine. 142. 105174–105174. 5 indexed citations
8.
Mahamdeh, Mohammed, et al.. (2022). Pocket CLARITY enables distortion-mitigated cardiac microstructural tissue characterization of large-scale specimens. Frontiers in Cardiovascular Medicine. 9. 1037500–1037500. 1 indexed citations
9.
Zenger, Brian, Wilson Good, Jaume Coll‐Font, et al.. (2022). Heart Position Uncertainty Quantification in the Inverse Problem of ECGI. Computing in cardiology. 3 indexed citations
10.
Fan, Yiling, et al.. (2021). Characterization of Exercise-Induced Myocardium Growth Using Finite Element Modeling and Bayesian Optimization. Frontiers in Physiology. 12. 694940–694940. 4 indexed citations
11.
Bozkurt, Alican, Kıvanç Köse, Jaume Coll‐Font, et al.. (2021). Skin strata delineation in reflectance confocal microscopy images using recurrent convolutional networks with attention. Scientific Reports. 11(1). 12576–12576. 12 indexed citations
12.
Bear, Laura, Yeşim Serinağaoğlu Doğrusöz, Wilson Good, et al.. (2020). The Impact of Torso Signal Processing on Noninvasive Electrocardiographic Imaging Reconstructions. IEEE Transactions on Biomedical Engineering. 68(2). 436–447. 17 indexed citations
13.
Erem, Burak, et al.. (2020). Characterizing the transient electrocardiographic signature of ischemic stress using Laplacian Eigenmaps for dimensionality reduction. Computers in Biology and Medicine. 127. 104059–104059. 7 indexed citations
14.
Bear, Laura, Yeşim Serinağaoğlu Doğrusöz, Jana Švehlíková, et al.. (2018). Effects of ECG Signal Processing on the Inverse Problem of Electrocardiography. Computing in cardiology. 45. 20 indexed citations
15.
Good, Wilson, Burak Erem, Brian Zenger, et al.. (2018). Temporal Performance of Laplacian Eigenmaps and 3D Conduction Velocity in Detecting Ischemic Stress. Journal of Electrocardiology. 51(6). S116–S120. 13 indexed citations
16.
Good, Wilson, Jaume Coll‐Font, Brian Zenger, et al.. (2018). Novel Metric Using Laplacian Eigenmaps to Evaluate Ischemic Stress on the Torso Surface. Computing in cardiology. 45. 5 indexed citations
17.
Good, Wilson, Burak Erem, Jaume Coll‐Font, Dana H. Brooks, & Rob MacLeod. (2017). Detecting Ischemic Stress to the Myocardium Using Laplacian Eigenmaps and Changes to Conduction Velocity. Computing in cardiology. 44. 6 indexed citations
18.
Aras, Kedar, Wilson Good, Jess Tate, et al.. (2015). Experimental Data and Geometric Analysis Repository—EDGAR. Journal of Electrocardiology. 48(6). 975–981. 65 indexed citations
19.
Coll‐Font, Jaume, et al.. (2015). A statistical approach to incorporate multiple ECG or EEG recordings with artifactual variability into inverse solutions. PubMed. 2015. 1053–1056. 3 indexed citations
20.
Coll‐Font, Jaume, et al.. (2014). Using a new time-independent average method for non-invasive cardiac potential imaging of endocardial pacing with imprecise thorax geometry. Computing in Cardiology. 825–828. 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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