Machine learning for prediction of intra-abdominal abscesses in patients with Crohn's disease visiting the emergency department.

ABSTRACT:

Background

Intra-abdominal abscess (IA) is an important clinical complication of Crohn's disease (CD). A high index of clinical suspicion is needed as imaging is not routinely used during hospital admission. This study aimed to identify clinical predictors of an IA among hospitalized patients with CD using machine learning.

Methods

We created an electronic data repository of all patients with CD who visited the emergency department of our tertiary medical center between 2012 and 2018. We searched for the presence of an IA on abdominal imaging within 7 days from visit. Machine learning models were trained to predict the presence of an IA. A logistic regression model was compared with a random forest model.

Results

Overall, 309 patients with CD were hospitalized and und

SUBMITTER: Levartovsky A 

PROVIDER: S-EPMC8543712 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature