Ágnes Vathy-Fogarassy

556 total citations
44 papers, 315 citations indexed

About

Ágnes Vathy-Fogarassy is a scholar working on Artificial Intelligence, Molecular Biology and Information Systems. According to data from OpenAlex, Ágnes Vathy-Fogarassy has authored 44 papers receiving a total of 315 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 10 papers in Molecular Biology and 8 papers in Information Systems. Recurrent topics in Ágnes Vathy-Fogarassy's work include Vehicle Dynamics and Control Systems (4 papers), Advanced Clustering Algorithms Research (4 papers) and Biomedical Text Mining and Ontologies (4 papers). Ágnes Vathy-Fogarassy is often cited by papers focused on Vehicle Dynamics and Control Systems (4 papers), Advanced Clustering Algorithms Research (4 papers) and Biomedical Text Mining and Ontologies (4 papers). Ágnes Vathy-Fogarassy collaborates with scholars based in Hungary, United Kingdom and France. Ágnes Vathy-Fogarassy's co-authors include János Abonyi, István Kenessey, Miklós Kásler, Tamás Forster, István Kósa, Krisztina Tóth, István Vassányi, Balázs Feil, Csaba Polgár and Péter Nagy and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Ágnes Vathy-Fogarassy

40 papers receiving 301 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ágnes Vathy-Fogarassy Hungary 10 77 38 37 37 36 44 315
Tomasz Wiktorski Norway 11 76 1.0× 33 0.9× 21 0.6× 15 0.4× 76 2.1× 51 383
Matthias Steinbrecher Germany 8 131 1.7× 18 0.5× 16 0.4× 49 1.3× 40 1.1× 14 321
Riccardo Rosati Italy 10 93 1.2× 49 1.3× 8 0.2× 43 1.2× 25 0.7× 30 315
Omar Ibrahim Obaid Iraq 11 167 2.2× 86 2.3× 19 0.5× 23 0.6× 50 1.4× 19 372
Mansour Esmaeilpour Iran 9 171 2.2× 100 2.6× 11 0.3× 33 0.9× 68 1.9× 25 373
Khrystyna Zub Ukraine 8 80 1.0× 26 0.7× 13 0.4× 35 0.9× 23 0.6× 13 246
Alexander Karlsson Sweden 10 132 1.7× 24 0.6× 98 2.6× 44 1.2× 22 0.6× 37 418
Noureen Talpur Malaysia 9 193 2.5× 31 0.8× 11 0.3× 37 1.0× 31 0.9× 14 386
Pradip Dhal India 7 194 2.5× 35 0.9× 26 0.7× 29 0.8× 51 1.4× 13 386

Countries citing papers authored by Ágnes Vathy-Fogarassy

Since Specialization
Citations

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

Fields of papers citing papers by Ágnes Vathy-Fogarassy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ágnes Vathy-Fogarassy. 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 Ágnes Vathy-Fogarassy. The network helps show where Ágnes Vathy-Fogarassy may publish in the future.

Co-authorship network of co-authors of Ágnes Vathy-Fogarassy

This figure shows the co-authorship network connecting the top 25 collaborators of Ágnes Vathy-Fogarassy. A scholar is included among the top collaborators of Ágnes Vathy-Fogarassy 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 Ágnes Vathy-Fogarassy. Ágnes Vathy-Fogarassy 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.
Vathy-Fogarassy, Ágnes, et al.. (2025). Predicting the effectiveness of chemotherapy treatment in lung cancer utilizing artificial intelligence-supported serum N-glycome analysis. Computers in Biology and Medicine. 186. 109681–109681. 3 indexed citations
2.
Vathy-Fogarassy, Ágnes, et al.. (2025). Sensitivity Analysis of Long Short-Term Memory-Based Neural Network Model for Vehicle Yaw Rate Prediction. Sensors. 25(5). 1363–1363.
3.
Vathy-Fogarassy, Ágnes, et al.. (2025). Improved analytical workflow towards machine learning supported N-glycomics-based biomarker discovery. Talanta. 295. 128389–128389.
4.
Kosztyán, Zsolt Tibor, et al.. (2025). Automated research methodology classification using machine learning. Engineering Applications of Artificial Intelligence. 156. 111039–111039. 1 indexed citations
5.
Bagyura, Zsolt, et al.. (2024). Time-dependent frequent sequence mining-based survival analysis. Knowledge-Based Systems. 296. 111885–111885. 2 indexed citations
6.
Vathy-Fogarassy, Ágnes, et al.. (2024). Quaternion-based irradiance calculation method applicable to solar power plants energy production. Energy. 309. 133127–133127. 1 indexed citations
7.
Vathy-Fogarassy, Ágnes, et al.. (2023). Aggregated Rankings of Top Leagues’ Football Teams: Application and Comparison of Different Ranking Methods. Applied Sciences. 13(7). 4556–4556. 8 indexed citations
8.
Vathy-Fogarassy, Ágnes, et al.. (2023). Surpassing early stopping: A novel correlation-based stopping criterion for neural networks. Neurocomputing. 567. 127028–127028. 27 indexed citations
9.
Vathy-Fogarassy, Ágnes, et al.. (2023). A general text mining method to extract echocardiography measurement results from echocardiography documents. Artificial Intelligence in Medicine. 143. 102584–102584. 5 indexed citations
10.
Kenessey, István, István Szatmári, András Wéber, et al.. (2022). Comparison of Cancer Survival Trends in Hungary in the Periods 2001–2005 and 2011–2015 According to a Population-Based Cancer Registry. Pathology & Oncology Research. 28. 1610668–1610668. 7 indexed citations
11.
Vathy-Fogarassy, Ágnes, et al.. (2022). Energy trading strategy for storage-based renewable power plants. Energy. 250. 123788–123788. 14 indexed citations
12.
Vathy-Fogarassy, Ágnes, István Vassányi, & István Kósa. (2021). Multi-level process mining methodology for exploring disease-specific care processes. Journal of Biomedical Informatics. 125. 103979–103979. 9 indexed citations
13.
Vathy-Fogarassy, Ágnes, et al.. (2020). Managing Alternative Patient Appointments Using P-Graph Methodology. Studies in health technology and informatics. 271. 57–64. 2 indexed citations
14.
Vathy-Fogarassy, Ágnes, et al.. (2020). The Efficiency of Different Distance Metrics for Keyword-Based Search in Medical Documents: A Short Case Study. Studies in health technology and informatics. 271. 232–239. 2 indexed citations
15.
Vathy-Fogarassy, Ágnes, et al.. (2020). Weighted nearest neighbours-based control group selection method for observational studies. PLoS ONE. 15(7). e0236531–e0236531. 4 indexed citations
16.
Vathy-Fogarassy, Ágnes, et al.. (2019). Risk prediction model for long-term heart failure incidence after epirubicin chemotherapy for breast cancer – A real-world data-based, nationwide classification analysis. International Journal of Cardiology. 285. 47–52. 30 indexed citations
17.
Vathy-Fogarassy, Ágnes, et al.. (2018). Design-Oriented Structural Controllability and Observability Analysis of Heat Exchanger Networks. SHILAP Revista de lepidopterología. 3 indexed citations
18.
Vathy-Fogarassy, Ágnes, et al.. (2017). Controllability and observability in complex networks – the effect of connection types. Scientific Reports. 7(1). 151–151. 33 indexed citations
19.
Vathy-Fogarassy, Ágnes & János Abonyi. (2013). Graph-Based Clustering and Data Visualization Algorithms. SpringerBriefs in computer science. 23 indexed citations
20.
Vathy-Fogarassy, Ágnes, et al.. (2008). Virtual Reality Simulations in the Education of Mathematics and Physics. EdMedia: World Conference on Educational Media and Technology. 2008(1). 5478–5483. 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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