Image-Based Differentiation of Bacterial and Fungal Keratitis Using Deep Convolutional Neural Networks.

ABSTRACT:

Purpose

Develop computer vision models for image-based differentiation of bacterial and fungal corneal ulcers and compare their performance against human experts.

Design

Cross-sectional comparison of diagnostic performance.

Participants

Patients with acute, culture-proven bacterial or fungal keratitis from 4 centers in South India.

Methods

Five convolutional neural networks (CNNs) were trained using images from handheld cameras collected from patients with culture-proven corneal ulcers in South India recruited as part of clinical trials conducted between 2006 and 2015. Their performance was evaluated on 2 hold-out test sets (1 single center and 1 multicenter) from South India. Twelve local expert cornea specialists performed remote interpretation of the images

SUBMITTER: Redd TK 

PROVIDER: S-EPMC9560557 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature