Machine Learning Methods to Extract Documentation of Breast Cancer Symptoms From Electronic Health Records.

Context: Clinicians document cancer patients' symptoms in free-text format within electronic health record visit notes. Although symptoms are critically important to quality of life and often herald clinical status changes, computational methods to assess the trajectory of symptoms over time are woefully underdeveloped.

Objectives: To create machine learning algorithms capable of extracting patient-reported symptoms from free-text electronic health record notes.