Panagiotis Anagnostou

According to our database, Panagiotis Anagnostou authored at least 13 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Boosting neural network performance for high dimensional data through random projections.

Panagiotis Anagnostou, Sotiris K. Tasoulis, Aristidis G. Vrahatis, Spiros V. Georgakopoulos, Vassilis P. Plagianakos

Pattern Recognit. Lett., 2026

2025

Correction: Large language models for efficient topic modeling.

Panagiotis C. Theocharopoulos, Panagiotis Anagnostou, Spiros V. Georgakopoulos, Sotiris K. Tasoulis, Vassilis P. Plagianakos

Neural Comput. Appl., December, 2025

Large language models for efficient topic modeling.

Panagiotis C. Theocharopoulos, Panagiotis Anagnostou, Spiros V. Georgakopoulos, Sotiris K. Tasoulis, Vassilis P. Plagianakos

Neural Comput. Appl., October, 2025

Short-term impacts of weather conditions on biomarkers among urban adults in Greece.

Katerina Tsiaktani, Panagiotis Anagnostou, Sotiris K. Tasoulis, Spiros V. Georgakopoulos, John A. Gittings, Dionysios E. Raitsos, Athanasia Sergounioti, Vassilis P. Plagianakos

Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 2025

Enhancing Machine Learning Models for Medical Coding: Diagnostic Codes Mapping and Synthetic Clinical Notes.

Aikaterini Bilioni, Panagiotis Anagnostou, Sotiris K. Tasoulis, Spiros V. Georgakopoulos, Vassilis P. Plagianakos

Proceedings of the IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, 2025

2024

HCER: Hierarchical Clustering-Ensemble Regressor.

Petros Barmpas, Panagiotis Anagnostou, Sotiris K. Tasoulis, Spiros V. Georgakopoulos, Vassilis P. Plagianakos

Proceedings of the Engineering Applications of Neural Networks, 2024

2023

HiPart: Hierarchical Divisive Clustering Toolbox.

Panagiotis Anagnostou, Sotiris K. Tasoulis, Vassilis P. Plagianakos, Dimitris K. Tasoulis

J. Open Source Softw., March, 2023

Ensemble Clustering for Boundary Detection in High-Dimensional Data.

Panagiotis Anagnostou, Nicos G. Pavlidis, Sotiris K. Tasoulis

Proceedings of the Machine Learning, Optimization, and Data Science, 2023

Detection of Fake Generated Scientific Abstracts.

Panagiotis C. Theocharopoulos, Panagiotis Anagnostou, Anastasia Tsoukala, Spiros V. Georgakopoulos, Sotiris K. Tasoulis, Vassilis P. Plagianakos

Proceedings of the IEEE Ninth International Conference on Big Data Computing Service and Applications, 2023

Neural Networks Voting for Projection Based Ensemble Classifiers.

Panagiotis Anagnostou, Petros Barmpas, Sotiris K. Tasoulis, Spiros V. Georgakopoulos, Vassilis P. Plagianakos

Proceedings of the IEEE International Conference on Big Data, 2023

2022

A divisive hierarchical clustering methodology for enhancing the ensemble prediction power in large scale population studies: the ATHLOS project.

Petros Barmpas, Sotiris K. Tasoulis, Aristidis G. Vrahatis, Spiros V. Georgakopoulos, Panagiotis Anagnostou, Matthew Prina, José Luis Ayuso-Mateos, Jerome Bickenbach, Ivet Bayes, Martin Bobak, Francisco Félix Caballero, Somnath Chatterji, Laia Egea-Cortés, Esther García-Esquinas, Matilde Leonardi, Seppo Koskinen, Ilona Koupil, Andrzej Pajak, Martin Prince, Warren Sanderson, Sergei Scherbov, Abdonas Tamosiunas, Aleksander Galas, Josep Maria Haro, Albert Sanchez-Niubo, Vassilis P. Plagianakos, Demosthenes Panagiotakos

Health Inf. Sci. Syst., 2022

2021

Enhancing the Human Health Status Prediction: The ATHLOS Project.

Panagiotis Anagnostou, Sotiris K. Tasoulis, Aristidis G. Vrahatis, Spiros V. Georgakopoulos, Matthew Prina, José Luis Ayuso-Mateos, Joachim Bickenbach, I. Bayes-Marin, Francisco Félix Caballero, Laia Egea-Cortés, Esther García-Esquinas, Matilde Leonardi, Sergei Scherbov, Abdonas Tamosiunas, Aleksander Galas, Josep Maria Haro, A. Sánchez-Martínez, Vassilis P. Plagianakos, Demosthenes Panagiotakos

Appl. Artif. Intell., 2021

2020

Approximate kNN Classification for Biomedical Data.

Panagiotis Anagnostou, Petros T. Barbas, Aristidis G. Vrahatis, Sotiris K. Tasoulis

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020