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Retinopathy of Prematurity

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Application of Artificial Intelligence in the Early Detection of Retinopathy of Prematurity: Review of the Literature.

Neonatology
Retinopathy of prematurity (ROP) is a potentially blinding disease in premature neonates that requires a skilled workforce for diagnosis, monitoring, and treatment. Artificial intelligence is a valuable tool that clinicians employ to reduce the scree...

Multicenter Validation of Deep Learning Algorithm ROP.AI for the Automated Diagnosis of Plus Disease in ROP.

Translational vision science & technology
PURPOSE: Retinopathy of prematurity (ROP) is a sight-threatening vasoproliferative retinal disease affecting premature infants. The detection of plus disease, a severe form of ROP requiring treatment, remains challenging owing to subjectivity, freque...

Fairness and generalisability in deep learning of retinopathy of prematurity screening algorithms: a literature review.

BMJ open ophthalmology
BACKGROUND: Retinopathy of prematurity (ROP) is a vasoproliferative disease responsible for more than 30 000 blind children worldwide. Its diagnosis and treatment are challenging due to the lack of specialists, divergent diagnostic concordance and va...

Image Analysis-Based Machine Learning for the Diagnosis of Retinopathy of Prematurity: A Meta-analysis and Systematic Review.

Ophthalmology. Retina
TOPIC: To evaluate the performance of machine learning (ML) in the diagnosis of retinopathy of prematurity (ROP) and to assess whether it can be an effective automated diagnostic tool for clinical applications.

The scope of artificial intelligence in retinopathy of prematurity (ROP) management.

Indian journal of ophthalmology
Artificial Intelligence (AI) is a revolutionary technology that has the potential to develop into a widely implemented system that could reduce the dependence on qualified professionals/experts for screening the large at-risk population, especially i...

A fundus image dataset for intelligent retinopathy of prematurity system.

Scientific data
Image-based artificial intelligence (AI) systems stand as the major modality for evaluating ophthalmic conditions. However, most of the currently available AI systems are designed for experimental research using single-central datasets. Most of them ...