Presented at the 27th International Symposium on Amyotrophic Lateral Sclerosis and Motor Neurone Disease, Dublin Ireland, December 2016.

Objectives:  To develop a model that predicts SVC using the PRO-ACT database.

Conclusions:  We hypothesized the possibility of using FVC records to predict SVC scores of ALS patients using machine learning techniques. Our results support our hypothesis and showed acceptable correlation. GBM outperformed other models and we selected GBM as our core model for developing a tool to predict SVC.

Authors: Jahandideh S, Taylor A, Bian A, Meng L, Beaulieu D, Keymer M, Andrews J, Ennist D



Download this Poster by Entering Your Email Address Below:

Share This