Automated machine learning (AutoML) can predict 90-day mortality after gastrectomy for cancer.

ABSTRACT: Early postoperative mortality risk prediction is crucial for clinical management of gastric cancer. This study aims to predict 90-day mortality in gastric cancer patients undergoing gastrectomy using automated machine learning (AutoML), optimize models for preoperative prediction, and identify factors influential in prediction. National Cancer Database was used to identify stage I-III gastric cancer patients undergoing gastrectomy between 2004 and 2016. 26 features were used to train predictive models using H2O.ai AutoML. Performance on validation cohort was measured. In 39,108 patients, 90-day mortality rate was 8.8%. The highest performing model was an ensemble (AUC = 0.77); older age, nodal ratio, and length of inpatient stay (LOS) following surgery were most influential for prediction.

SUBMITTER: SenthilKumar G 

PROVIDER: S-EPMC10329647 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature