Development and multi-center validation of machine learning model for early detection of fungal keratitis.

ABSTRACT:

Background

Fungal keratitis (FK) is a leading cause of corneal blindness in developing countries due to poor clinical recognition and laboratory identification. Here, we aimed to identify the distinct clinical signature of FK and develop a diagnostic model to differentiate FK from other types of infectious keratitis.

Methods

We reviewed the electronic health records (EHRs) of all patients with suspected infectious keratitis in Beijing Tongren Hospital from January 2011 to December 2021. Twelve clinical signs of slit-lamp images were assessed by Lasso regression analysis and collinear variables were excluded. Three models based on binary logistic regression, random forest classification, and decision tree classification were trained for FK diagnosis and employed for internal

SUBMITTER: Wei Z 

PROVIDER: S-EPMC9869416 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature