Mutation-based clustering and classification analysis reveals distinctive age groups and age-related biomarkers for glioma

Mutation-based clustering and classification analysis reveals distinctive age groups and age-related biomarkers for glioma

Abstract Background Malignant brain tumor diseases exhibit differences within molecular features depending on the patient’s age. Methods In this work, we use gene mutation data from public resources to explore age specifics about glioma. We use both an explainable clustering as well as classificatio...

Full description

Bibliographic Details
Main Authors: Claire Jean-Quartier, Fleur Jeanquartier, Aydin Ridvan, Matthias Kargl, Tica Mirza, Tobias Stangl, Robi Markaĉ, Mauro Jurada, Andreas Holzinger
Format: Article
Language:English
Published: BMC 2021-02-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Glioma classification
pediatric cancer
explainable artificial intelligence
XAI
Age clusters
K-Means
Online Access:https://doi.org/10.1186/s12911-021-01420-1

Internet

https://doi.org/10.1186/s12911-021-01420-1

Similar Items