A multicenter prospective study on postoperative pulmonary complications prediction in geriatric patients with deep neural network model.

ABSTRACT:

Aim

Postoperative pulmonary complications (PPCs) can increase the risk of postoperative mortality, and the geriatric population has high incidence of PPCs. Early identification of high-risk geriatric patients is of great value for clinical decision making and prognosis improvement. Existing prediction models are based purely on structured data, and they lack predictive accuracy in geriatric patients. We aimed to develop and validate a deep neural network model based on combined natural language data and structured data for improving the prediction of PPCs in geriatric patients.

Methods

We consecutively enrolled patients aged ≥65 years who underwent surgery under general anesthesia at seven hospitals in China. Data from the West China Hospital of Sichuan University were used

SUBMITTER: Peng X 

PROVIDER: S-EPMC9395933 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature