Applying Machine Learning Techniques to Identify Undiagnosed Patients with Exocrine Pancreatic Insufficiency.

ABSTRACT:

Background

Exocrine pancreatic insufficiency (EPI) is a serious condition characterized by a lack of functional exocrine pancreatic enzymes and the resultant inability to properly digest nutrients. EPI can be caused by a variety of disorders, including chronic pancreatitis, pancreatic cancer, and celiac disease. EPI remains underdiagnosed because of the nonspecific nature of clinical symptoms, lack of an ideal diagnostic test, and the inability to easily identify affected patients using administrative claims data.

Objectives

To develop a machine learning model that identifies patients in a commercial medical claims database who likely have EPI but are undiagnosed.

Methods

A machine learning algorithm was developed in Scikit-learn, a Python module. The study population

SUBMITTER: Pyenson B 

PROVIDER: S-EPMC7299452 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature