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Deep Learning for the Discrimination Among Different Types of Keratits: a Nationwide Study

Keratitis Clinical Trial

Official title:
Deep Learning for the Discrimination Among Bacterial, Fungal, Viral, Amebic and Noninfectious Keratitis: a Nationwide Study

Clinical Trial Summary

Detecting the cause of keratitis fast is the premise of providing targeted therapy for reducing vision loss and preventing severe complications. Due to overlapping inflammatory features, even expert cornea specialists have relatively poor performance in the identification of causative pathogen of infectious keraitis. In this project, the investigators aim to develop an automated and accurate deep learning system to discriminate among bacterial, fungal, viral, amebic and noninfectious keratitis based on slit-lamp images and evaluated this system using the datasets obtained from mutiple independent clinical centers across China.

Clinical Trial Description

n/a

Study Design

Related Conditions & MeSH terms

Clinical Trial Details
NCT number NCT05538793
Study type Observational
Source Ningbo Eye Hospital
Contact
Status Completed
Phase
Start date July 1, 2020
Completion date October 20, 2023
View Details
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