Machine learning classification of vitamin D levels in spondyloarthritis patients
Fecha
2024-02-22Estado
info:eu-repo/semantics/publishedVersionMetadatos
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. 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.
Machine learning classification of vitamin D levels in spondyloarthritis patients
Tipo de Actividad
Artículos en revistasISSN
2666-5212Palabras Clave
.Ankylosing spondyloarthritis Machine learning Arthritic psoriasis 1 alpha 25 dihydroxy 20 epi vitamin d3