Neural network prediction of severe lower intestinal bleeding and the need for surgical intervention.

ABSTRACT:

Background

The prognosis for patients with severe acute lower intestinal bleeding (ALIB) may be assessed by complex artificial neural networks (ANNs) or user-friendly regression-based models. Comparisons between these modalities are limited, and predicting the need for surgical intervention remains elusive. We hypothesized that ANNs would outperform the Strate rule to predict severe bleeding and would also predict the need for surgical intervention.

Methods

We performed a 4-y retrospective analysis of 147 adult patients who underwent endoscopy, angiography, or surgery for ALIB. Baseline characteristics, Strate risk factors, management parameters, and outcomes were analyzed. The primary outcomes were severe bleeding and surgical intervention. ANNs were created in SPSS. Models

SUBMITTER: Loftus TJ 

PROVIDER: S-EPMC5644023 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature