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Vasileios C. Pezoulas
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2020 – today
- 2024
- [j7]Vasileios C. Pezoulas, Fanis G. Kalatzis, Themis P. Exarchos, Andreas Goules, Athanasios G. Tzioufas
, Dimitrios I. Fotiadis
FHBF: Federated hybrid boosted forests with dropout rates for supervised learning tasks across highly imbalanced clinical datasets. Patterns 5(1): 100893 (2024) - 2023
- [c28]Vasileios C. Pezoulas, Georg Ehret, Jos A. Bosch, Dimitrios I. Fotiadis, Antonis I. Sakellarios:
Distilling knowledge from high quality biobank data towards the discovery of risk factors for patients with cardiovascular diseases and depression. BHI 2023: 1-4 - [c27]Eleftherios Trivizakis
LoockMe: An Ever Evolving Artificial Intelligence Platform for Location Scouting in Greece. EANN 2023: 315-327 - [c26]Vasileios C. Pezoulas, Themis P. Exarchos, Nikolaos S. Tachos, Andreas Goules, Athanasios G. Tzioufas
Boosting the performance of MALT lymphoma classification in patients with primary Sjögren's Syndrome through data augmentation: a case study. EMBC 2023: 1-4 - 2022
- [j6]Vasileios C. Pezoulas
ICU admission and mortality classifiers for COVID-19 patients based on subgroups of dynamically associated profiles across multiple timepoints. Comput. Biol. Medicine 141: 105176 (2022) - [c25]Orestis D. Papagiannopoulos, Costas Papaloukas, Vasileios C. Pezoulas
Comparison of Proteomic Approaches in Autoinflammatory Disease Classification. BHI 2022: 1-4 - [c24]Vasileios C. Pezoulas
A federated AI-empowered platform for disease management across a Pan-European data driven hub. BHI 2022: 1-4 - [c23]Vasileios C. Pezoulas
A hybrid approach based on dynamic trajectories to predict mortality in COVID-19 patients upon steroids administration. BHI 2022: 1-4 - [c22]Vasileios C. Pezoulas
Metabolomics in the prediction of prodromal stages of carotid artery disease using a hybrid ML algorithm. BHI 2022: 1-4 - [c21]Konstantina Tsarapatsani, Antonis I. Sakellarios, Vasileios C. Pezoulas
Machine Learning Models to Predict Myocardial Infarction Within 10-Years Follow-up of Cardiovascular Disease Progression. BHI 2022: 1-4 - [c20]Panagiota I. Tsompou, Vassiliki T. Potsika, Nikola Jovica Petrovic, Vasileios C. Pezoulas
Computational modeling of atherosclerotic plaque progression through an efficient 3D agent-based modeling approach. BHI 2022: 1-4 - [c19]Vasileios C. Pezoulas
Predicting the need for mechanical ventilation and mortality in hospitalized COVID-19 patients who received heparin. EMBC 2022: 1020-1023 - [c18]Vasileios C. Pezoulas
A "smart" Imputation Approach for Effective Quality Control Across Complex Clinical Data Structures. EMBC 2022: 1049-1052 - [c17]Konstantina Tsarapatsani, Antonis I. Sakellarios, Vasileios C. Pezoulas
Machine Learning Models for Cardiovascular Disease Events Prediction. EMBC 2022: 1066-1069 - [c16]Grigoris I. Grigoriadis, Dimitrios G. Zaridis, Vasileios C. Pezoulas, Sotiris Nikopoulos, Antonis I. Sakellarios, Nikolaos S. Tachos, Katerina K. Naka, Lampros K. Michalis, Dimitrios I. Fotiadis:
Segmentation of left atrium using CT images and a deep learning model. EMBC 2022: 3839-3842 - 2021
- [j5]Vasileios C. Pezoulas
A computational pipeline for data augmentation towards the improvement of disease classification and risk stratification models: A case study in two clinical domains. Comput. Biol. Medicine 134: 104520 (2021) - [j4]Tim Smole
A machine learning-based risk stratification model for ventricular tachycardia and heart failure in hypertrophic cardiomyopathy. Comput. Biol. Medicine 135: 104648 (2021) - [c15]Grigoris I. Grigoriadis, Vasileios C. Pezoulas
Towards the development of a unified virtual population model in hypertrophic cardiomyopathy. BHI 2021: 1-4 - [c14]Vasileios C. Pezoulas
A hybrid data harmonization workflow using word embeddings for the interlinking of heterogeneous cross-domain clinical data structures. BHI 2021: 1-4 - [c13]Vasileios C. Pezoulas
A federated AI strategy for the classification of patients with Mucosa Associated Lymphoma Tissue (MALT) lymphoma across multiple harmonized cohorts. EMBC 2021: 1666-1669 - [c12]Vasileios C. Pezoulas
Multiple additive regression trees with hybrid loss for classification tasks across heterogeneous clinical data in distributed environments: a case study. EMBC 2021: 1670-1673 - [c11]Vasileios C. Pezoulas
Variational Gaussian Mixture Models with robust Dirichlet concentration priors for virtual population generation in hypertrophic cardiomyopathy: a comparison study. EMBC 2021: 1674-1677 - [c10]Grigoris I. Grigoriadis, Maria Roumpi, Dimitrios G. Zaridis, Vasileios C. Pezoulas
Comparison of three U-Net family architectures for left ventricular myocardial wall automatic segmentation. EMBC 2021: 2932-2935 - 2020
- [c9]Antonis I. Sakellarios, Vasileios C. Pezoulas
Prediction of atherosclerotic disease progression combining computational modelling with machine learning. EMBC 2020: 2760-2763 - [c8]Vasileios C. Pezoulas
Generation of virtual patient data for in-silico cardiomyopathies drug development using tree ensembles: a comparative study. EMBC 2020: 5343-5346
2010 – 2019
- 2019
- [j3]Vasileios C. Pezoulas
Medical data quality assessment: On the development of an automated framework for medical data curation. Comput. Biol. Medicine 107: 270-283 (2019) - [j2]Vasileios C. Pezoulas
Functional Connectivity Analysis of Cerebellum Using Spatially Constrained Spectral Clustering. IEEE J. Biomed. Health Informatics 23(4): 1710-1719 (2019) - [c7]Vasileios C. Pezoulas
Generation of Virtual Patients for in Silico Cardiomyopathies Drug Development. BIBE 2019: 671-674 - [c6]Michalis D. Mantzaris, Evangelos Andreakos
A Multimodal Advanced Approach for the Stratification of Carotid Artery Disease. BIBE 2019: 706-709 - [c5]Vasileios C. Pezoulas
Predicting lymphoma outcomes and risk factors in patients with primary Sjögren's Syndrome using gradient boosting tree ensembles. EMBC 2019: 2165-2168 - 2018
- [j1]Kostas M. Tsiouris
A Long Short-Term Memory deep learning network for the prediction of epileptic seizures using EEG signals. Comput. Biol. Medicine 99: 24-37 (2018) - [c4]Vasileios C. Pezoulas
FCLAB: An EEGLAB module for performing functional connectivity analysis on single-subject EEG data. BHI 2018: 96-99 - [c3]Vasileios C. Pezoulas
Towards the Establishment of a Biomedical Ontology for the Primary Sjögren's Syndrome. EMBC 2018: 4089-4092 - [c2]Vasileios C. Pezoulas, Konstantina D. Kourou, Themis P. Exarchos, Vassiliki Andronikou, Theodora A. Varvarigou, Athanasios G. Tzioufas, Salvatore de Vita, Dimitrios I. Fotiadis:
A De-centralized Framework for Data Sharing, Ontology Matching and Distributed Analytics. SWH@ISWC 2018 - 2017
- [c1]Kostas M. Tsiouris
Discrimination of Preictal and Interictal Brain States from Long-Term EEG Data. CBMS 2017: 318-323
Coauthor Index
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last updated on 2024-10-07 21:22 CEST by the dblp team
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