Jari Hyttinen

7.2k total citations
296 papers, 5.1k citations indexed

About

Jari Hyttinen is a scholar working on Biomedical Engineering, Cellular and Molecular Neuroscience and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Jari Hyttinen has authored 296 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 106 papers in Biomedical Engineering, 73 papers in Cellular and Molecular Neuroscience and 63 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Jari Hyttinen's work include Neuroscience and Neural Engineering (68 papers), Cardiac electrophysiology and arrhythmias (40 papers) and Neural dynamics and brain function (32 papers). Jari Hyttinen is often cited by papers focused on Neuroscience and Neural Engineering (68 papers), Cardiac electrophysiology and arrhythmias (40 papers) and Neural dynamics and brain function (32 papers). Jari Hyttinen collaborates with scholars based in Finland, Italy and United Kingdom. Jari Hyttinen's co-authors include Jaakko Malmivuo, Katriina Aalto‐Setälä, Michelangelo Paci, Jari Viik, Markus Hannula, Stefano Severi, P. Kauppinen, Ville‐Pekka Seppä, Heli Skottman and Jarno M. A. Tanskanen and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Macromolecules.

In The Last Decade

Jari Hyttinen

281 papers receiving 5.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jari Hyttinen Finland 39 2.0k 1.2k 1.2k 931 734 296 5.1k
Xiaofeng Jia United States 36 2.1k 1.0× 1.2k 0.9× 1.1k 0.9× 234 0.3× 878 1.2× 192 6.0k
Tzung K. Hsiai United States 41 3.2k 1.6× 1.7k 1.3× 334 0.3× 1.2k 1.3× 744 1.0× 201 7.4k
Inchan Youn South Korea 29 1.4k 0.7× 540 0.4× 476 0.4× 288 0.3× 566 0.8× 101 3.8k
Guanglin Li China 48 5.3k 2.6× 420 0.3× 1.8k 1.5× 727 0.8× 476 0.6× 462 9.4k
Daniel H. Turnbull United States 45 1.6k 0.8× 2.7k 2.2× 893 0.7× 587 0.6× 268 0.4× 125 7.1k
Hideaki Fujita Japan 37 1.1k 0.6× 1.5k 1.2× 437 0.4× 659 0.7× 399 0.5× 149 4.7k
Il‐Joo Cho South Korea 33 1.4k 0.7× 445 0.4× 1.2k 1.0× 375 0.4× 130 0.2× 151 3.6k
G.T.A. Kovacs United States 44 4.8k 2.3× 559 0.5× 1.2k 1.0× 1.5k 1.6× 772 1.1× 165 7.5k
Théoden I. Netoff United States 35 1.2k 0.6× 761 0.6× 1.9k 1.5× 229 0.2× 1.8k 2.4× 105 6.1k
Yoram Palti Israel 32 1.4k 0.7× 1.3k 1.0× 1.1k 0.9× 210 0.2× 128 0.2× 166 4.5k

Countries citing papers authored by Jari Hyttinen

Since Specialization
Citations

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

Fields of papers citing papers by Jari Hyttinen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jari Hyttinen

This figure shows the co-authorship network connecting the top 25 collaborators of Jari Hyttinen. A scholar is included among the top collaborators of Jari Hyttinen 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 Jari Hyttinen. Jari Hyttinen 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.
Panichella, Giorgia, Alessandra Fornaro, Josè Manuel Pioner, et al.. (2025). Artificial intelligence applications in hypertrophic cardiomyopathy: turns and loopholes. European Heart Journal - Digital Health. 6(5). 853–867. 1 indexed citations
2.
3.
Ressler, Antonia, Setareh Zakeri, Joana Maia Dias, et al.. (2024). Vat photopolymerization of biomimetic bone scaffolds based on Mg, Sr, Zn-substituted hydroxyapatite: Effect of sintering temperature. Ceramics International. 50(15). 27403–27415. 13 indexed citations
4.
Paci, Michelangelo, et al.. (2024). In silico study of the mechanisms of hypoxia and contractile dysfunction during ischemia and reperfusion of hiPSC cardiomyocytes. Disease Models & Mechanisms. 17(4). 2 indexed citations
5.
Tanskanen, Jarno M. A., et al.. (2024). Electric field temporal interference stimulation of neurons in vitro. Lab on a Chip. 24(16). 3945–3957. 6 indexed citations
6.
Ressler, Antonia, Tomislav Ivanković, Markus Hannula, et al.. (2024). Multifunctional Sr, Mg, Ag-substituted octacalcium phosphate/carboxymethyl chitosan scaffolds: Antibacterial activity and osteogenic differentiation of human mesenchymal stem cells. Materialia. 34. 102077–102077. 3 indexed citations
7.
Penttinen, Kirsi, Antti Ahola, Jenny E. Párraga, et al.. (2024). Gellan gum-gelatin based cardiac models support formation of cellular networks and functional cardiomyocytes. Cytotechnology. 76(4). 483–502. 6 indexed citations
8.
Hopia, Anu, et al.. (2023). Micro-computed tomography shows silent bubbles in squeaky mozzarella. SHILAP Revista de lepidopterología. 9(1). 5–8. 1 indexed citations
9.
Tanskanen, Jarno M. A., et al.. (2021). Astrocytes Exhibit a Protective Role in Neuronal Firing Patterns under Chemically Induced Seizures in Neuron–Astrocyte Co-Cultures. International Journal of Molecular Sciences. 22(23). 12770–12770. 18 indexed citations
10.
Bartolucci, Chiara, Michelangelo Paci, Jari Hyttinen, Elisa Passini, & Stefano Severi. (2019). Evolution of the Seminal O'Hara Rudy Model to More Accurately Simulate the Electrophysiology of Human Ventricular Cardiomyocytes. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 1 indexed citations
11.
Hannula, Markus, et al.. (2019). Characterisation and in vitro and in vivo evaluation of supercritical-CO2-foamed β-TCP/PLCL composites for bone applications. European Cells and Materials. 38. 35–50. 9 indexed citations
12.
Juntunen, Miia, et al.. (2018). Porous poly- l -lactide-co-ɛ-caprolactone scaffold: a novel biomaterial for vaginal tissue engineering. Royal Society Open Science. 5(8). 180811–180811. 23 indexed citations
13.
Paci, Michelangelo, Elisa Passini, Aleksandra Klimas, et al.. (2018). In Silico Populations Optimized on Optogenetic Recordings Predict Drug Effects in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes. Computing in cardiology. 45. 6 indexed citations
14.
Tanskanen, Jarno M. A., et al.. (2017). Lead field theory provides a powerful tool for designing microelectrode array impedance measurements for biological cell detection and observation. BioMedical Engineering OnLine. 16(1). 85–85. 3 indexed citations
15.
Paci, Michelangelo, Stefano Severi, & Jari Hyttinen. (2014). Computational modeling supports induced pluripotent stem cell-derived cardiomyocytes reliability as a model for human LQT3. Computing in Cardiology. 69–72. 4 indexed citations
16.
Pelto, Jani, Jari Hyttinen, Bettina Mannerström, et al.. (2012). Novel Polypyrrole-Coated Polylactide Scaffolds Enhance Adipose Stem Cell Proliferation and Early Osteogenic Differentiation. Tissue Engineering Part A. 19(7-8). 882–892. 85 indexed citations
17.
Nanni, Loris, et al.. (2011). Computer vision for human stem cell derived cardiomyocyte classification: The induced pluripotent vs embryonic stem cell case study. Computing in Cardiology. 569–572. 2 indexed citations
18.
Ilmarinen, Tanja, et al.. (2010). Microelectrode Array in Evaluation of RPE Functionality. Investigative Ophthalmology & Visual Science. 51(13). 5252–5252. 1 indexed citations
19.
Hyttinen, Jari, et al.. (2005). Application of lead field theory and computerized thorax modeling for the ECG inverse problem. 1. 363–366. 2 indexed citations
20.
Kauppinen, P., Jari Hyttinen, & Jaakko Malmivuo. (1998). Sensitivity Distributions of Impedance Cardiography Using Band and Spot Electrodes Analyzed by a Three-Dimensional Computer Model. Annals of Biomedical Engineering. 26(4). 694–702. 49 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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