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

ConclusionsOur 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.
Source: Health Information Science and Systems - Category: Information Technology Source Type: research