Jiří Spilka

1.3k total citations
31 papers, 872 citations indexed

About

Jiří Spilka is a scholar working on Cardiology and Cardiovascular Medicine, Pediatrics, Perinatology and Child Health and Biomedical Engineering. According to data from OpenAlex, Jiří Spilka has authored 31 papers receiving a total of 872 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Cardiology and Cardiovascular Medicine, 23 papers in Pediatrics, Perinatology and Child Health and 10 papers in Biomedical Engineering. Recurrent topics in Jiří Spilka's work include Neonatal and fetal brain pathology (23 papers), Heart Rate Variability and Autonomic Control (13 papers) and ECG Monitoring and Analysis (12 papers). Jiří Spilka is often cited by papers focused on Neonatal and fetal brain pathology (23 papers), Heart Rate Variability and Autonomic Control (13 papers) and ECG Monitoring and Analysis (12 papers). Jiří Spilka collaborates with scholars based in Czechia, Greece and France. Jiří Spilka's co-authors include Václav Chudáček, Lenka Lhotská, Michal Huptych, Petr Janků, Miroslav Burša, Lukáš Hruban, Michal Koucký, Patrice Abry, Chrysostomos Stylios and Muriel Doret and has published in prestigious journals such as PLoS ONE, BMC Pregnancy and Childbirth and Journal of Biomedical Informatics.

In The Last Decade

Jiří Spilka

31 papers receiving 859 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jiří Spilka Czechia 14 629 380 346 324 114 31 872
Václav Chudáček Czechia 14 584 0.9× 359 0.9× 336 1.0× 350 1.1× 113 1.0× 35 875
Antoniya Georgieva United Kingdom 16 512 0.8× 331 0.9× 149 0.4× 136 0.4× 98 0.9× 47 722
Philip Warrick Canada 16 489 0.8× 367 1.0× 181 0.5× 213 0.7× 28 0.2× 65 866
Michał Jeżewski Poland 17 326 0.5× 266 0.7× 273 0.8× 455 1.4× 94 0.8× 54 801
Michal Huptych Czechia 16 403 0.6× 272 0.7× 462 1.3× 242 0.7× 80 0.7× 54 959
Janusz Wróbel Poland 21 426 0.7× 359 0.9× 429 1.2× 576 1.8× 55 0.5× 93 1.1k
K. Horoba Poland 24 495 0.8× 421 1.1× 491 1.4× 709 2.2× 63 0.6× 89 1.3k
Miroslav Burša Czechia 7 276 0.4× 171 0.5× 134 0.4× 107 0.3× 73 0.6× 18 409
A. Matonia Poland 18 357 0.6× 320 0.8× 378 1.1× 688 2.1× 33 0.3× 64 1.0k
M. Moulden United Kingdom 22 1.2k 2.0× 774 2.0× 232 0.7× 399 1.2× 33 0.3× 33 1.6k

Countries citing papers authored by Jiří Spilka

Since Specialization
Citations

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

Fields of papers citing papers by Jiří Spilka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiří Spilka

This figure shows the co-authorship network connecting the top 25 collaborators of Jiří Spilka. A scholar is included among the top collaborators of Jiří Spilka 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 Jiří Spilka. Jiří Spilka 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.
Abry, Patrice, Jiří Spilka, Roberto Leonarduzzi, et al.. (2018). Sparse learning for Intrapartum fetal heart rate analysis. Biomedical Physics & Engineering Express. 4(3). 34002–34002. 22 indexed citations
2.
Georgoulas, George, Petros Karvelis, Jiří Spilka, et al.. (2017). Investigating pH based evaluation of fetal heart rate (FHR) recordings. Health and Technology. 7(2-3). 241–254. 49 indexed citations
3.
Spilka, Jiří, et al.. (2016). Sparse Support Vector Machine for Intrapartum Fetal Heart Rate Classification. IEEE Journal of Biomedical and Health Informatics. 21(3). 664–671. 74 indexed citations
4.
Doret, Muriel, Jiří Spilka, Václav Chudáček, Paulo Gonçalvès, & Patrice Abry. (2015). Fractal Analysis and Hurst Parameter for Intrapartum Fetal Heart Rate Variability Analysis: A Versatile Alternative to Frequency Bands and LF/HF Ratio. PLoS ONE. 10(8). e0136661–e0136661. 40 indexed citations
5.
Karvelis, Petros, Jiří Spilka, George Georgoulas, et al.. (2015). Combining latent class analysis labeling with multiclass approach for fetal heart rate categorization. Physiological Measurement. 36(5). 1001–1024. 7 indexed citations
6.
Leonarduzzi, Roberto, Jiří Spilka, Herwig Wendt, et al.. (2015). P-leader multifractal analysis and sparse SVM for intrapartum fetal acidosis detection. PubMed. 2015. 1971–1974. 4 indexed citations
7.
Spilka, Jiří, Patrice Abry, Paulo Gonçalvès, & Muriel Doret. (2014). Impacts of first and second labour stages on Hurst parameter based intrapartum fetal heart rate analysis. Computing in Cardiology Conference. 777–780. 4 indexed citations
8.
Chudáček, Václav, et al.. (2014). Evaluation of fetal heart rate recordings based on clustering. Computing in Cardiology Conference. 621–624. 2 indexed citations
9.
Spilka, Jiří, Václav Chudáček, Petr Janků, et al.. (2014). Analysis of obstetricians’ decision making on CTG recordings. Journal of Biomedical Informatics. 51. 72–79. 46 indexed citations
10.
Burša, Miroslav, Lenka Lhotská, Václav Chudáček, et al.. (2014). Information retrieval from hospital information system: Increasing effectivity using swarm intelligence. Journal of Applied Logic. 13(2). 126–137. 4 indexed citations
11.
Chudáček, Václav, Jiří Spilka, Miroslav Burša, et al.. (2014). Open access intrapartum CTG database. BMC Pregnancy and Childbirth. 14(1). 16–16. 201 indexed citations
12.
Spilka, Jiří, Václav Chudáček, Miroslav Burša, et al.. (2012). Stability of variability features computed from fetal heart rate with artifcially infused missing data. Computing in Cardiology. 917–920. 9 indexed citations
13.
Kužílek, Jakub, Michal Huptych, Václav Chudáček, Jiří Spilka, & Lenka Lhotská. (2011). Data driven approach to ECG signal quality assessment using multistep SVM classification. Computing in Cardiology. 453–455. 22 indexed citations
14.
Chudáček, Václav, Jakub Kužílek, Jiří Spilka, et al.. (2011). Mobile CTG — Fetal heart rate assessment using Android platform. Computing in Cardiology. 249–252. 2 indexed citations
15.
Chudáček, Václav, et al.. (2011). Simple scoring system for ECG quality assessment on Android platform. Computing in Cardiology. 449–451. 21 indexed citations
16.
Chudáček, Václav, Jiří Spilka, Petr Janků, et al.. (2011). Automatic evaluation of intrapartum fetal heart rate recordings: a comprehensive analysis of useful features. Physiological Measurement. 32(8). 1347–1360. 36 indexed citations
17.
Chudáček, Václav, Jiří Spilka, Lenka Lhotská, et al.. (2011). Assessment of features for automatic CTG analysis based on expert annotation. PubMed. 2011. 6051–6054. 15 indexed citations
18.
Spilka, Jiří, Václav Chudáček, Michal Koucký, et al.. (2011). Using nonlinear features for fetal heart rate classification. Biomedical Signal Processing and Control. 7(4). 350–357. 108 indexed citations
19.
Chudáček, Václav, Jiří Spilka, Michal Huptych, et al.. (2010). Linear and non-linear features for intrapartum cardiotocography evaluation. Computing in Cardiology. 999–1002. 6 indexed citations
20.
Chudáček, Václav, et al.. (2009). Fetal heart rate data pre-processing and annotation. 1–4. 10 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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