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.