Development of a Machine Learning Algorithm to Predict Abnormalities in Serum Phosphate in a Large Oncology Cohort.
Journal:
JCO clinical cancer informatics
PMID:
40215448
Abstract
PURPOSE: Serum phosphate is commonly measured in oncology patients because of the relationship between oncologic conditions and treatments with abnormal phosphate. All patients attending our institution, a large specialist oncology center, have a standardized order set (SOS) measured. This consists of 15 biochemical tests, including serum phosphate. Our aim was to understand if abnormalities in serum phosphate could be predicted, using a machine learning algorithm (MLA) by other interrelated variables in the SOS.