A study on predicting the length of hospital stay for Chinese patients with ischemic stroke based on the XGBoost algorithm.

ABSTRACT:

Background

The incidence of stroke is a challenge in China, as stroke imposes a heavy burden on families, national health services, social services, and the economy. The length of hospital stay (LOS) is an essential indicator of utilization of medical services and is usually used to assess the efficiency of hospital management and patient quality of care. This study established a prediction model based on a machine learning algorithm to predict ischemic stroke patients' LOS.

Methods

A total of 18,195 ischemic stroke patients' electronic medical records and 28 attributes were extracted from electronic medical records in a large comprehensive hospital in China. The prediction of LOS was regarded as a multi classification problem, and LOS was divided into three categories: 1-7

SUBMITTER: Chen R 

PROVIDER: S-EPMC10031936 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature