Prediction of postoperative cardiopulmonary complications after lung resection in a Chinese population: A machine learning-based study.

ABSTRACT:

Background

Approximately 20% of patients with lung cancer would experience postoperative cardiopulmonary complications after anatomic lung resection. Current prediction models for postoperative complications were not suitable for Chinese patients. This study aimed to develop and validate novel prediction models based on machine learning algorithms in a Chinese population.

Methods

Patients with lung cancer receiving anatomic lung resection and no neoadjuvant therapies from September 1, 2018 to August 31, 2019 were enrolled. The dataset was split into two cohorts at a 7:3 ratio. The logistic regression, random forest, and extreme gradient boosting were applied to construct models in the derivation cohort with 5-fold cross validation. The validation cohort accessed the model pe

SUBMITTER: Huang G 

PROVIDER: S-EPMC9539671 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature