Machine Learning Approaches to Predict 6-Month Mortality Among Patients With Cancer.

ABSTRACT:

Importance

Machine learning algorithms could identify patients with cancer who are at risk of short-term mortality. However, it is unclear how different machine learning algorithms compare and whether they could prompt clinicians to have timely conversations about treatment and end-of-life preferences.

Objectives

To develop, validate, and compare machine learning algorithms that use structured electronic health record data before a clinic visit to predict mortality among patients with cancer.

Design, setting, and participants

Cohort study of 26 525 adult patients who had outpatient oncology or hematology/oncology encounters at a large academic cancer center and 10 affiliated community practices between February 1, 2016, and July 1, 2016. Patients were not required to

SUBMITTER: Parikh RB 

PROVIDER: S-EPMC6822091 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature