American Psychological Association 6th edition

Gavriilidis, G., orcid:0000-0003-2575-, Vasileiou, V., Psomopoulos, F., Dimitsaki, S., Giannakakis, A., Pavlopoulos, G., & Karakatsoulis, G. (2025). APNet, an explainable sparse deep learning model to discover differentially active drivers of severe COVID-19. Zenodo. https://doi.org/10.5281/zenodo.14680520

ISO-690 (author-date, English)

GAVRIILIDIS, George, orcid:0000-0003-2575-, VASILEIOU, Vasileios, PSOMOPOULOS, Fotis, DIMITSAKI, Stella, GIANNAKAKIS, Antonis, PAVLOPOULOS, Georgios and KARAKATSOULIS, Georgios, 2025. APNet, an explainable sparse deep learning model to discover differentially active drivers of severe COVID-19. Zenodo.

Modern Language Association 9th edition

Gavriilidis, G., orcid:0000-0003-2575-, V. Vasileiou, F. Psomopoulos, S. Dimitsaki, A. Giannakakis, G. Pavlopoulos, and G. Karakatsoulis. APNet, an explainable sparse deep learning model to discover differentially active drivers of severe COVID-19. Zenodo, 2025, https://doi.org/10.5281/zenodo.14680520.

Mohr Siebeck - Recht (Deutsch - Österreich)

Gavriilidis, George/orcid:0000-0003-2575-/Vasileiou, Vasileios/Psomopoulos, Fotis/Dimitsaki, Stella/Giannakakis, Antonis et al.: APNet, an explainable sparse deep learning model to discover differentially active drivers of severe COVID-19, 2025.

Emerald - Harvard

Gavriilidis, G., orcid:0000-0003-2575-, Vasileiou, V., Psomopoulos, F., Dimitsaki, S., Giannakakis, A., Pavlopoulos, G. and Karakatsoulis, G. (2025), APNet, an explainable sparse deep learning model to discover differentially active drivers of severe COVID-19, Vol. , Zenodo, available at:https://doi.org/10.5281/zenodo.14680520.

Warning: These citations may not always be 100% accurate.