Ralf Peeters

1.8k total citations
118 papers, 1.2k citations indexed

About

Ralf Peeters is a scholar working on Cardiology and Cardiovascular Medicine, Control and Systems Engineering and Statistical and Nonlinear Physics. According to data from OpenAlex, Ralf Peeters has authored 118 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Cardiology and Cardiovascular Medicine, 24 papers in Control and Systems Engineering and 18 papers in Statistical and Nonlinear Physics. Recurrent topics in Ralf Peeters's work include ECG Monitoring and Analysis (24 papers), Control Systems and Identification (20 papers) and Cardiac electrophysiology and arrhythmias (19 papers). Ralf Peeters is often cited by papers focused on ECG Monitoring and Analysis (24 papers), Control Systems and Identification (20 papers) and Cardiac electrophysiology and arrhythmias (19 papers). Ralf Peeters collaborates with scholars based in Netherlands, France and Belgium. Ralf Peeters's co-authors include Joël Karel, Bernard Hanzon, Ronald Westra, Pietro Bonizzi, Paul G.A. Volders, Matthijs Cluitmans, Olivier Meste, Wouter A. Serdijn, Theo M. de Kok and Gökhan Ertaylan and has published in prestigious journals such as PLoS ONE, Scientific Reports and Automatica.

In The Last Decade

Ralf Peeters

108 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ralf Peeters Netherlands 17 372 259 138 122 121 118 1.2k
Hui Zhao China 25 207 0.6× 237 0.9× 135 1.0× 181 1.5× 479 4.0× 147 2.2k
Marco Sciandrone Italy 25 72 0.2× 217 0.8× 71 0.5× 160 1.3× 125 1.0× 69 1.7k
Dana Copoţ Belgium 21 118 0.3× 467 1.8× 212 1.5× 20 0.2× 92 0.8× 128 1.6k
Abou‐Bakr M. Youssef Egypt 18 235 0.6× 128 0.5× 225 1.6× 529 4.3× 372 3.1× 93 1.7k
Zhaohua Yang China 18 166 0.4× 163 0.6× 102 0.7× 203 1.7× 441 3.6× 116 1.4k
Yuanmin Li China 27 155 0.4× 98 0.4× 81 0.6× 804 6.6× 239 2.0× 123 2.0k
Te‐Jen Su Taiwan 19 33 0.1× 700 2.7× 85 0.6× 66 0.5× 161 1.3× 147 1.4k
Muhammad Moinuddin Saudi Arabia 16 48 0.1× 132 0.5× 41 0.3× 84 0.7× 256 2.1× 149 1.1k
Jukka Saarinen Finland 21 115 0.3× 58 0.2× 56 0.4× 309 2.5× 209 1.7× 151 1.7k
Dongsheng Wu United States 14 72 0.2× 56 0.2× 42 0.3× 74 0.6× 91 0.8× 78 665

Countries citing papers authored by Ralf Peeters

Since Specialization
Citations

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

Fields of papers citing papers by Ralf Peeters

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ralf Peeters

This figure shows the co-authorship network connecting the top 25 collaborators of Ralf Peeters. A scholar is included among the top collaborators of Ralf Peeters 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 Ralf Peeters. Ralf Peeters 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.
Wang, Tiantian, Joël Karel, Kurt Driessens, et al.. (2025). Deep learning based estimation of heart surface potentials. Artificial Intelligence in Medicine. 163. 103093–103093. 1 indexed citations
2.
Patel, Kiran Haresh Kumar, Uyên Châu Nguyên, Casper Mihl, et al.. (2024). Variant patterns of electrical activation and recovery in normal human hearts revealed by noninvasive electrocardiographic imaging. EP Europace. 26(7). 2 indexed citations
3.
Wang, Tiantian, Joël Karel, Pietro Bonizzi, & Ralf Peeters. (2023). Influence of the Tikhonov Regularization Parameter on the Accuracy of the Inverse Problem in Electrocardiography. Sensors. 23(4). 1841–1841. 10 indexed citations
4.
Wang, Tiantian, Joël Karel, Ismael Hernández‐Romero, et al.. (2023). Standardized 2D atrial mapping and its clinical applications. Computers in Biology and Medicine. 168. 107755–107755. 3 indexed citations
5.
Cavill, Rachel, Evgueni Smirnov, Michael Lenz, et al.. (2023). Application of transfer learning to predict drug-induced human in vivo gene expression changes using rat in vitro and in vivo data. PLoS ONE. 18(11). e0292030–e0292030.
6.
Bonizzi, Pietro, Olivier Meste, Stef Zeemering, et al.. (2020). A novel framework for noninvasive analysis of short-term atrial activity dynamics during persistent atrial fibrillation. Medical & Biological Engineering & Computing. 58(9). 1933–1945. 5 indexed citations
7.
Driessens, Kurt, Evgueni Smirnov, Michael Lenz, et al.. (2020). Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes. PLoS ONE. 15(8). e0236392–e0236392. 4 indexed citations
8.
Nguyên, Uyên Châu, et al.. (2020). An Open-Source Algorithm for Standardized Bullseye Visualization of High-Resolution Cardiac Ventricular Data: UNISYS. Computing in cardiology. 47. 4 indexed citations
9.
Jiang, Jian, et al.. (2019). The application of omics-based human liver platforms for investigating the mechanism of drug-induced hepatotoxicity in vitro. Archives of Toxicology. 93(11). 3067–3098. 18 indexed citations
10.
Cluitmans, Matthijs, et al.. (2019). The Influence of Using a Static Diastolic Geometry in ECG Imaging. Computing in cardiology. 1 indexed citations
11.
Cluitmans, Matthijs, et al.. (2019). The Influence of Using a Static Diastolic Geometry in ECG Imaging. Computing in Cardiology Conference. 1–4. 1 indexed citations
12.
Zhou, Shuang, et al.. (2015). Largest Source Subset Selection for Instance Transfer. Research Publications (Maastricht University). 423–438. 4 indexed citations
13.
Cluitmans, Matthijs, et al.. (2014). Physiology-based regularization improves noninvasive reconstruction and localization of cardiac electrical activity. Computing in Cardiology Conference. 1–4. 5 indexed citations
14.
Cluitmans, Matthijs, Pietro Bonizzi, Joël Karel, et al.. (2013). Inverse reconstruction of epicardial potentials improved by vectorcardiography and realistic potentials. Computing in Cardiology Conference. 369–372. 1 indexed citations
15.
Hanzon, Bernard, et al.. (2012). On a Finiteness Result for the Number of Critical Points of the H2 Approximation Criterion. IFAC Proceedings Volumes. 45(16). 728–733. 1 indexed citations
16.
Karel, Joël, Rachel Senden, Hans H. C. M. Savelberg, et al.. (2010). Towards unobtrusive in vivo monitoring of patients prone to falling. IEEE Engineering in Medicine and Biology Magazine. 1. 4 indexed citations
17.
Hanzon, Bernard & Ralf Peeters. (1996). A Faddeev sequence method for solving Lyapunov and Sylvester equations. Linear Algebra and its Applications. 241-243. 401–430. 51 indexed citations
18.
Peeters, Ralf. (1993). Application of the Riemannian Levenberg-Marquardt algorithm to off- line system identification. Digital Academic REpository of VU University Amsterdam (Vrije Universiteit Amsterdam). 1 indexed citations
19.
Peeters, Ralf. (1993). On a Riemannian version of the Levenberg-Marquardt algorithm. Data Archiving and Networked Services (DANS). 1 indexed citations
20.
Peeters, Ralf & Bernard Hanzon. (1992). The Riemannian interpretation of Gauss-Newton and Scoring, with application to system identification. Digital Academic REpository of VU University Amsterdam (Vrije Universiteit Amsterdam). 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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