Using a Guided Machine Learning Ensemble Model to Predict Discharge Disposition following Meningioma Resection.

ABSTRACT: Objective  Machine learning (ML) algorithms are powerful tools for predicting patient outcomes. This study pilots a novel approach to algorithm selection and model creation using prediction of discharge disposition following meningioma resection as a proof of concept. Materials and Methods  A diversity of ML algorithms were trained on a single-institution database of meningioma patients to predict discharge disposition. Algorithms were ranked by predictive power and top performers were combined to create an ensemble model. The final ensemble was internally validated on never-before-seen data to demonstrate generalizability. The predictive power of the ensemble was compared with a logistic regression. Further analyses were performed to identify how important variables impact t

SUBMITTER: Muhlestein WE 

PROVIDER: S-EPMC5978858 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature