Outcome prediction for critical care patients with respiratory neoplasms using a multilayer perceptron neural network.

ABSTRACT:

Objective

The variation in mortality rates of intensive care unit oncological patients may imply that clinical characteristics and prognoses are very different between specific subsets of patients with cancer. The specific characteristics of patients with cancer have not been included as risk factors in the established severity-of-illness scoring systems and comorbidity scores, showing limitations in predicting mortality risk. This study aimed to devise a predictive tool for in-hospital mortality for adult patients with a respiratory neoplasm admitted to the intensive care unit, using an artificial neural network.

Methods

A total of 1,221 stays in the intensive care unit from the Beth Israel Deaconess Medical Center were studied. The primary endpoint was the all-cause in-hos

SUBMITTER: Nistal-Nuno B 

PROVIDER: S-EPMC10501764 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature