A federated AI strategy for the classification of patients with Mucosa Associated Lymphoma Tissue (MALT) lymphoma across multiple harmonized cohorts. - Vasileios C. Pezoulas; Fanis G. Kalatzis; Themis P. Exarchos; Luke Chatzis; Saviana Gandolfo; Andreas Goules; Salvatore de Vita; Athanasios G. Tzioufas; Dimitrios I. Fotiadis (EMBC, 2021)

A computational pipeline for data augmentation towards the improvement of disease classification and risk stratification models: A case study in two clinical domains. - Vasileios C. Pezoulas; Grigoris I. Grigoriadis; George Gkois; Nikolaos S. Tachos; Tim Smole; Zoran Bosnic; Matej Piculin; Iacopo Olivotto; Fausto Barlocco; Marko Robnik-Sikonja; Djordje G. Jakovljevic; Andreas Goules; et al. (Comput. Biol. Medicine, 2021)

Boosting the performance of MALT lymphoma classification in patients with primary Sjögren's Syndrome through data augmentation: a case study. - Vasileios C. Pezoulas; Themis P. Exarchos; Nikolaos S. Tachos; Andreas Goules; Athanasios G. Tzioufas; Dimitrios I. Fotiadis (EMBC, 2023)

FHBF: Federated hybrid boosted forests with dropout rates for supervised learning tasks across highly imbalanced clinical datasets. - Vasileios C. Pezoulas; Fanis G. Kalatzis; Themis P. Exarchos; Andreas Goules; Athanasios G. Tzioufas; Dimitrios I. Fotiadis (Patterns, 2024)