Automatic retinoblastoma screening and surveillance using deep learning.

ABSTRACT:

Background

Retinoblastoma is the most common intraocular malignancy in childhood. With the advanced management strategy, the globe salvage and overall survival have significantly improved, which proposes subsequent challenges regarding long-term surveillance and offspring screening. This study aimed to apply a deep learning algorithm to reduce the burden of follow-up and offspring screening.

Methods

This cohort study includes retinoblastoma patients who visited Beijing Tongren Hospital from March 2018 to January 2022 for deep learning algorism development. Clinical-suspected and treated retinoblastoma patients from February 2022 to June 2022 were prospectively collected for prospective validation. Images from the posterior pole and peripheral retina were collected, and refer

SUBMITTER: Zhang R 

PROVIDER: S-EPMC10403507 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature