Volume 10, Number 19, December 2020

Predicting Disease Activity for Biologic Selection in Rheumatoid Arthritis

  Authors

Morio YAMAUCHI¹, Kazuhisa NAKANO², Yoshiya TANAKA² and Keiichi HORIO¹, ¹Kyushu Institute of Technology, Japan, ²University of Occupational and Environmental Health, Japan

  Abstract

In this article, we implemented a regression model and conducted experiments for predicting disease activity using data from 1929 rheumatoid arthritis patients to assist in the selection of biologics for rheumatoid arthritis. On modelling, the missing variables in the data were completed by three different methods, mean value, self-organizing map and random value. Experimental results showed that the prediction error of the regression model was large regardless of the missing completion method, making it difficult to predict the prognosis of rheumatoid arthritis patients.

  Keywords

Rheumatoid Arthritis, Gaussian Process Regression, Self-Organizing Map.