Development of a machine learning model for early prediction of plasma leakage in suspected dengue patients.

ABSTRACT:

Background

At least a third of dengue patients develop plasma leakage with increased risk of life-threatening complications. Predicting plasma leakage using laboratory parameters obtained in early infection as means of triaging patients for hospital admission is important for resource-limited settings.

Methods

A Sri Lankan cohort including 4,768 instances of clinical data from N = 877 patients (60.3% patients with confirmed dengue infection) recorded in the first 96 hours of fever was considered. After excluding incomplete instances, the dataset was randomly split into a development and a test set with 374 (70%) and 172 (30%) patients, respectively. From the development set, five most informative features were selected using the minimum description length (MDL) algorithm. Ra

SUBMITTER: Zargari Marandi R 

PROVIDER: S-EPMC10035900 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature