Hybrid Minimal Spanning Tree and Mixture of Gaussians Based Clustering Algorithm. - Ágnes Vathy-Fogarassy; Attila Kiss 001; János Abonyi (FoIKS, 2006)

Visualization of Topology Representing Networks. - Ágnes Vathy-Fogarassy; Agnes Werner-Stark; Balázs Gaál; János Abonyi (IDEAL, 2007)

Improvement of Jarvis-Patrick Clustering Based on Fuzzy Similarity. - Ágnes Vathy-Fogarassy; Attila Kiss 001; János Abonyi (WILF, 2007)

Topology Representing Networks for the Visualization of Manifolds. - Ágnes Vathy-Fogarassy; Agnes Werner-Stark; János Abonyi (J. Math. Model. Algorithms, 2008)

Topology Representing Network Map - A New Tool for Visualization of High-Dimensional Data. - Ágnes Vathy-Fogarassy; Attila Kiss 001; János Abonyi (Trans. Comput. Sci., 2008)

Local and global mappings of topology representing networks. - Ágnes Vathy-Fogarassy; János Abonyi (Inf. Sci., 2009)

Novel Graph Based Clustering and Visualization Algorithms for Data Mining - Ágnes Vathy-Fogarassy (2009)

Graph-Based Clustering and Data Visualization Algorithms. - Ágnes Vathy-Fogarassy; János Abonyi (Springer, 2013)

Fuzzy c-Medoid Graph Clustering. - András Király; Ágnes Vathy-Fogarassy; János Abonyi (ICAISC (2), 2014)

Geodesic distance based fuzzy c-medoid clustering - searching for central points in graphs and high dimensional data. - András Király; Ágnes Vathy-Fogarassy; János Abonyi (Fuzzy Sets Syst., 2016)

Comparison of Control Group Generating Methods. - Szabolcs Szekér; György Fogarassy; Ágnes Vathy-Fogarassy (eHealth, 2017)

Frequent Treatment Sequence Mining from Medical Databases. - Krisztina Tóth; István Kósa; Ágnes Vathy-Fogarassy (eHealth, 2017)

Uniform data access platform for SQL and NoSQL database systems. - Ágnes Vathy-Fogarassy; Tamás Hugyák (Inf. Syst., 2017)

The Effect of Latent Binary Variables on the Uncertainty of the Prediction of a Dichotomous Outcome Using Logistic Regression Based Propensity Score Matching. - Szabolcs Szekér; Ágnes Vathy-Fogarassy (eHealth, 2018)

Network Distance-Based Simulated Annealing and Fuzzy Clustering for Sensor Placement Ensuring Observability and Minimal Relative Degree. - Daniel Leitold; Ágnes Vathy-Fogarassy; János Abonyi (Sensors, 2018)

Application of Named Entity Recognition Methods to Extract Information from Echocardiography Reports. - Szabolcs Szekér; György Fogarassy; Károly Machalik; Ágnes Vathy-Fogarassy (dHealth, 2019)

The Effect of the Different Data Aggregation Methods and their Detail Levels to the Prediction of Bitcoin's Exchange Rate. - Tamás Miseta; Ágnes Vathy-Fogarassy (IWOBI, 2019)

How Can the Similarity of the Case and Control Groups be Measured in Case-Control Studies? - Szabolcs Szekér; Ágnes Vathy-Fogarassy (IWOBI, 2019)

Empirical working time distribution-based line balancing with integrated simulated annealing and dynamic programming. - Daniel Leitold; Ágnes Vathy-Fogarassy; János Abonyi (Central Eur. J. Oper. Res., 2019)

Network-based Observability and Controllability Analysis of Dynamical Systems: the NOCAD toolbox. - Dániel Leitold; Ágnes Vathy-Fogarassy; János Abonyi (F1000Research, 2019)

Managing Alternative Patient Appointments Using P-Graph Methodology. - Zoltán Süle; János Baumgartner; Ágnes Vathy-Fogarassy (dHealth, 2020)

The Efficiency of Different Distance Metrics for Keyword-Based Search in Medical Documents: A Short Case Study. - Ágnes Vathy-Fogarassy; Szabolcs Szekér; Balázs Szolár; György Fogarassy (dHealth, 2020)

Network-Based Analysis of Dynamical Systems - Methods for Controllability and Observability Analysis, and Optimal Sensor Placement - Dániel Leitold; Ágnes Vathy-Fogarassy; János Abonyi (Springer, 2020)

Optimized Weighted Nearest Neighbours Matching Algorithm for Control Group Selection. - Szabolcs Szekér; Ágnes Vathy-Fogarassy (Algorithms, 2021)

Software Framework and Graph-based Methodology for Optimal Patient Appointment Planning. - Zoltán Süle; János Baumgartner; Dániel Leitold; Tibor Dulai; Ákos Orosz; Ágnes Vathy-Fogarassy (CENTERIS/ProjMAN/HCist, 2022)

Multi-level process mining methodology for exploring disease-specific care processes. - Ágnes Vathy-Fogarassy; István Vassányi; István Kósa (J. Biomed. Informatics, 2022)

Prediction for Future Yaw Rate Values of Vehicles Using Long Short-Term Memory Network. - János Kontos; Balázs Kránicz; Ágnes Vathy-Fogarassy (Sensors, 2023)

A general text mining method to extract echocardiography measurement results from echocardiography documents. - Szabolcs Szekér; György Fogarassy; Ágnes Vathy-Fogarassy (Artif. Intell. Medicine, 2023)

Forecasting Longitudinal Acceleration in Urban Vehicles. - János Kontos; László Bódis; Ágnes Vathy-Fogarassy (AIAI (3), 2024)

Time-dependent frequent sequence mining-based survival analysis. - Róbert Csalódi; Zsolt Bagyura; Ágnes Vathy-Fogarassy; János Abonyi (Knowl. Based Syst., 2024)

Surpassing early stopping: A novel correlation-based stopping criterion for neural networks. - Tamás Miseta; Attila Fodor; Ágnes Vathy-Fogarassy (Neurocomputing, 2024)

Evaluation of a New-Concept Secure File Server Solution. - Gábor Arányi; Ágnes Vathy-Fogarassy; Veronika Szücs (Future Internet, 2024)

Predicting the effectiveness of chemotherapy treatment in lung cancer utilizing artificial intelligence-supported serum N-glycome analysis. - Rebeka Torok; Brigitta Meszaros; Veronika Gombas; Ágnes Vathy-Fogarassy; Miklos Szabo; Eszter Csanky; Gábor Járvás; Andras Guttman (Comput. Biol. Medicine, 2025)

Automated research methodology classification using machine learning. - Zsolt Tibor Kosztyán; Tünde Király; Tibor Csizmadia; Attila Imre Katona; Ágnes Vathy-Fogarassy (Eng. Appl. Artif. Intell., 2025)