4 citations · 11 across the 6 of their papers we have counts for
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q-bio.QM2021★ 1 cited
Deep learning can differentiate IDH-mutant from IDH-wild type GBM
Luca Pasquini, Antonio Napolitano, Emanuela Tagliente +10
Background: Distinction of IDH mutant and wildtype GBMs is challenging on MRI, since conventional imaging shows considerable overlap. While few studies employed deep-learning in a…
q-bio.QM2021★ 2 cited
Comparison of Machine Learning Classifiers to Predict Patient Survival and Genetics of GBM: Towards a Standardized Model for Clinical Implementation
Luca Pasquini, Antonio Napolitano, Martina Lucignani +11
Radiomic models have been shown to outperform clinical data for outcome prediction in glioblastoma (GBM). However, clinical implementation is limited by lack of parameters standard…