An Improvised Classification Model for Predicting Delirium.
Journal:
Studies in health technology and informatics
Published Date:
Aug 21, 2019
Abstract
With the vast increase of digital healthcare data, there is an opportunity to mine the data for understanding inherent health patterns. Although machine-learning techniques demonstrated their applications in healthcare to answer several questions, there is still room for improvement in every aspect. In this paper, we are demonstrating a method that improves the performance of a delirium prediction model using random forest in combination with logistic regression.