Miloš Kudělka

832 total citations
76 papers, 451 citations indexed

About

Miloš Kudělka is a scholar working on Computer Vision and Pattern Recognition, Statistical and Nonlinear Physics and Artificial Intelligence. According to data from OpenAlex, Miloš Kudělka has authored 76 papers receiving a total of 451 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 18 papers in Statistical and Nonlinear Physics and 18 papers in Artificial Intelligence. Recurrent topics in Miloš Kudělka's work include Complex Network Analysis Techniques (18 papers), Web Data Mining and Analysis (11 papers) and Data Visualization and Analytics (9 papers). Miloš Kudělka is often cited by papers focused on Complex Network Analysis Techniques (18 papers), Web Data Mining and Analysis (11 papers) and Data Visualization and Analytics (9 papers). Miloš Kudělka collaborates with scholars based in Czechia, Armenia and United States. Miloš Kudělka's co-authors include Eva Kriegová, Václav Snåšel, Zdeněk Horák, Jiří Gallo, Zuzana Mikulková, Petr Gajdoš, Ajith Abraham, Gayane Manukyan, Regina Fillerová and Tomáš Papajík and has published in prestigious journals such as Blood, PLoS ONE and Scientific Reports.

In The Last Decade

Miloš Kudělka

67 papers receiving 442 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Miloš Kudělka Czechia 13 91 85 64 62 61 76 451
Danqing Zhang United States 13 182 2.0× 89 1.0× 47 0.7× 110 1.8× 43 0.7× 28 418
Yuxia Yao China 12 47 0.5× 16 0.2× 19 0.3× 156 2.5× 37 0.6× 38 615
Mehmet Deveci Türkiye 15 25 0.3× 74 0.9× 98 1.5× 55 0.9× 5 0.1× 50 617
Yiling Yang China 14 52 0.6× 39 0.5× 13 0.2× 75 1.2× 30 0.5× 28 681
Yidan Zhang China 10 114 1.3× 23 0.3× 25 0.4× 42 0.7× 33 0.5× 45 466
義行 高橋 United States 11 60 0.7× 13 0.2× 33 0.5× 25 0.4× 37 0.6× 35 476
Xiangru Huang China 13 38 0.4× 39 0.5× 90 1.4× 129 2.1× 32 0.5× 29 578
Hiroshi Tezuka Japan 18 263 2.9× 35 0.4× 20 0.3× 28 0.5× 6 0.1× 42 797
Zhihua Zhang China 14 42 0.5× 10 0.1× 72 1.1× 91 1.5× 8 0.1× 57 743
Shun Zheng China 13 124 1.4× 49 0.6× 7 0.1× 129 2.1× 12 0.2× 30 695

Countries citing papers authored by Miloš Kudělka

Since Specialization
Citations

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

Fields of papers citing papers by Miloš Kudělka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Miloš Kudělka

This figure shows the co-authorship network connecting the top 25 collaborators of Miloš Kudělka. A scholar is included among the top collaborators of Miloš Kudělka 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 Miloš Kudělka. Miloš Kudělka 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.
Kriegová, Eva, et al.. (2025). Positive impact of structural asymmetries in PPI networks on protein complex detection. Applied Network Science. 10(1).
2.
Kvasnicka, Hans Michael, et al.. (2025). The utility of automated artificial intelligence‐assisted digital cytomorphology for bone marrow analysis in diagnostic haemato‐oncology. Clinical and Translational Medicine. 15(7). e70364–e70364. 1 indexed citations
3.
Schovánek, Jan, et al.. (2025). Long-Term Impact of Thyroid Eye Disease on Quality of Life: Insights From a Retrospective Cohort Study. Endocrine Practice. 31(5). 607–613.
4.
5.
Kriegová, Eva, et al.. (2023). Real-world data in rheumatoid arthritis: patient similarity networks as a tool for clinical evaluation of disease activity. Applied Network Science. 8(1). 1 indexed citations
6.
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Kriegová, Eva, et al.. (2021). A theoretical model of health management using data-driven decision-making: the future of precision medicine and health. Journal of Translational Medicine. 19(1). 68–68. 11 indexed citations
8.
Petráčková, Anna, et al.. (2020). Revealed heterogeneity in rheumatoid arthritis based on multivariate innate signature analysis. Clinical and Experimental Rheumatology. 38(2). 289–298. 12 indexed citations
9.
Gallo, Jiří, et al.. (2020). Gender Differences in Contribution of Smoking, Low Physical Activity, and High BMI to Increased Risk of Early Reoperation After TKA. The Journal of Arthroplasty. 35(6). 1545–1557. 14 indexed citations
10.
Kriegová, Eva, et al.. (2019). Inflammation time-axis in aseptic loosening of total knee arthroplasty: A preliminary study. PLoS ONE. 14(8). e0221056–e0221056. 14 indexed citations
11.
Gallo, Jiří, et al.. (2018). Smoking, Preoperative Activity, and Waiting Time for the Surgery Could Predict the Risk of Early Reoperation in Total Knee Arthroplasty. Acta chirurgiae orthopaedicae et traumatologiae Cechoslovaca. 85(6). 410–417. 2 indexed citations
12.
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Kriegová, Eva, et al.. (2017). Quantitative assessment of informative immunophenotypic markers increases the diagnostic value of immunophenotyping in mature CD5‐positive B‐cell neoplasms. Cytometry Part B Clinical Cytometry. 94(4). 576–587. 16 indexed citations
14.
Kudělka, Miloš & Michal Haindl. (2016). Texture fidelity criterion. ASEP. 2062–2066. 5 indexed citations
15.
Fillerová, Regina, Miloš Kudělka, Monika Žůrková, et al.. (2015). Correlation Network Analysis Reveals Relationships between MicroRNAs, Transcription Factor T-bet, and Deregulated Cytokine/Chemokine‐Receptor Network in Pulmonary Sarcoidosis. Mediators of Inflammation. 2015(1). 121378–121378. 22 indexed citations
16.
Kudělka, Miloš, et al.. (2014). Local representativeness in vector data. 29. 894–899. 2 indexed citations
17.
Kudělka, Miloš, et al.. (2013). Visualization of Large Graphs Using GPU Computing. 662–667. 5 indexed citations
18.
Kudělka, Miloš, Zdeněk Horák, Vit Voženílek, & Václav Snåšel. (2012). ORTHOPHOTO FEATURE EXTRACTION AND CLUSTERING. Neural Network World. 22(2). 103–121. 18 indexed citations
19.
Horák, Zdeněk, Miloš Kudělka, Václav Snåšel, & Vit Voženílek. (2011). Orthophoto Map Feature Extraction Based on Neural Networks. 216–225. 4 indexed citations
20.
Horák, Zdeněk, Miloš Kudělka, & Václav Snåšel. (2011). Feature clustering for orthophotomap analysis. 13. 307–312. 1 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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