Machine learning classification of vitamin D levels in spondyloarthritis patients

Abstract

.

Objectives: Predict the 25 dihydroxy 20 epi vitamin d3 level (low, medium, or high) in spondyloarthritis patients. Methods: Observational, descriptive, and cross-sectional study. We collected information from 115 patients. From a total of 32 variables, we selected the most relevant using mutual information tests, and, finally, we estimated two classification models using machine learning. Result: We obtain an interpretable decision tree and an ensemble maximizing the expected accuracy using Bayesian optimization and 10-fold cross-validation over a preprocessed dataset. Conclusion: We identify relevant variables not considered in previous research, such as age and post-treatment. We also estimate more flexible and high-capacity models using advanced data science techniques.