Prediction of hospital mortality in intensive care unit patients from clinical and laboratory data: A machine learning approach.

ABSTRACT:

Background

Intensive care unit (ICU) patients demand continuous monitoring of several clinical and laboratory parameters that directly influence their medical progress and the staff's decision-making. Those data are vital in the assistance of these patients, being already used by several scoring systems. In this context, machine learning approaches have been used for medical predictions based on clinical data, which includes patient outcomes.

Aim

To develop a binary classifier for the outcome of death in ICU patients based on clinical and laboratory parameters, a set formed by 1087 instances and 50 variables from ICU patients admitted to the emergency department was obtained in the "WiDS (Women in Data Science) Datathon 2020: ICU Mortality Prediction" dataset.

Methods

SUBMITTER: Caires Silveira E 

PROVIDER: S-EPMC9483004 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature