GLIMPSE: a glioblastoma prognostication model using ensemble learning-a surveillance, epidemiology, and end results study.

Kamel Aladdein Samara Zaher Al AghbariAmani Abusafia

Published in: Health information science and systems (2021)

Our ensemble models were high-performing and achieved AUROCs as high as 0.94, highlighting the importance of balancing, using ensemble techniques and statistical feature selection. Our models can potentially be used by clinicians after external validation.

Keyphrases

neural network
convolutional neural network
public health
machine learning
palliative care
deep learning
risk factors