ArticleOphthalmology science2022
Evaluation of an Artificial Intelligence System for Retinopathy of Prematurity Screening in Nepal and Mongolia.
Article in Ophthalmology science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Assessment of Retinopathy of Prematurity Regression and Reactivation Using an Artificial Intelligence-Based Vascular Severity Score.JAMA network open · 2023Trial
- Application of a Quantitative Vascular Severity Score in Retinopathy of Prematurity in the United States and India: New Insights Into Disease Epidemiology and Pathophysiology.American journal of ophthalmology · 2026Article
- Artificial intelligence in ophthalmology clinical trials: a narrative review.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026Review
- Review of Retinopathy of Prematurity Management in the Anti-VEGF Era: Evolving Global Paradigms, Persistent Challenges and Our AI-Assisted Future.Clinical & experimental ophthalmology · 2025Review
- Artificial intelligence in ophthalmology: opportunities, challenges, and ethical considerations.Medical hypothesis, discovery & innovation ophthalmology journal · 2025Review
- Use of an Artificial Intelligence-Generated Vascular Severity Score Improved Plus Disease Diagnosis in Retinopathy of Prematurity.Ophthalmology · 2024Article
- Implementation of Artificial Intelligence in Retinopathy of Prematurity Care: Challenges and Opportunities.International ophthalmology clinics · 2024Review
- A review on retinopathy of prematurity.Medical hypothesis, discovery & innovation ophthalmology journal · 2024Review
- Epidemiologic Evaluation of Retinopathy of Prematurity Severity in a Large Telemedicine Program in India Using Artificial Intelligence.Ophthalmology · 2023Article
- Development and international validation of custom-engineered and code-free deep-learning models for detection of plus disease in retinopathy of prematurity: a retrospective study.The Lancet. Digital health · 2023Article
- Development and validation of an artificial intelligence based screening tool for detection of retinopathy of prematurity in a South Indian population.Frontiers in pediatrics · 2023Article
- External Validation of a Retinopathy of Prematurity Screening Model Using Artificial Intelligence in 3 Low- and Middle-Income Populations.JAMA ophthalmology · 2022Article
- Review
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Authors and funding
20 authors.
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Abstract
Purpose: To evaluate the performance of a deep learning (DL) algorithm for retinopathy of prematurity (ROP) screening in Nepal and Mongolia. Design: Retrospective analysis of prospectively collected clinical data. Participants: Clinical information and fundus images were obtained from infants in 2 ROP screening programs in Nepal and Mongolia. Methods: Fundus images were obtained using the Forus 3nethra neo (Forus Health) in Nepal and the RetCam Portable (Natus Medical, Inc.) in Mongolia. The overall severity of ROP was determined from the medical record using the International Classification of ROP (ICROP). The presence of plus disease was determined independently in each image using a reference standard diagnosis. The Imaging and Informatics for ROP (i-ROP) DL algorithm was trained on images from the RetCam to classify plus disease and to assign a vascular severity score (VSS) from 1 through 9. Main Outcome Measures: Area under the receiver operating characteristic curve and area under the precision-recall curve for the presence of plus disease or type 1 ROP and association between VSS and ICROP disease category. Results: The prevalence of type 1 ROP was found to be higher in Mongolia (14.0%) than in Nepal (2.2%; Conclusions: These data provide preliminary evidence of the effectiveness of the i-ROP DL algorithm for ROP screening in neonatal populations in Nepal and Mongolia using multiple camera systems and are useful for consideration in future clinical implementation of artificial intelligence-based ROP screening in low- and middle-income countries.
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