Crossmark

Machine learning to improve interpretability of clinical, radiological and panel-based genomic data of glioma grade 4 patients undergoing surgical resection

Crossref DOI link: https://doi.org/10.1186/s12967-023-04308-y

Published Online: 2023-07-07

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Dal Bo, Michele

Polano, Maurizio https://orcid.org/0000-0002-6101-1382
Ius, Tamara

Di Cintio, Federica

Mondello, Alessia

Manini, Ivana

Pegolo, Enrico

Cesselli, Daniela

Di Loreto, Carla

Skrap, Miran

Toffoli, Giuseppe
Funding

Funding for this research was provided by:

Regione Autonoma Friuli Venezia Giulia (Progetto di Ricerca Finalizzata Regione Friuli Venezia Giulia Anno 2021 LR 13/2021, art. 8, c. 28-30)

Ministero della Salute (Progetto Giovani Ricercatori n. GR-2016-02364678)
License Information

Text and Data Mining valid from 2023-07-07

Version of Record valid from 2023-07-07
More Information

Article History

Received: 26 April 2023

Accepted: 24 June 2023

First Online: 7 July 2023

Declarations

:

: Written informed consent was obtained for surgery. Patients provided informed consent in accordance with the local institutional review board requirements and the Declaration of Helsinki. Patients were included in the study approved by the local Ethics Committee protocol N. 0036566 /P/ GEN/EGAS, ID study 2538.

: All subjects provided consent for the use of their data.

: The authors declare that they have no competing interest.

Document is current

Any future updates will be listed below