Retinopathy of Prematurity: A Global Perspective and Recent Developments
Bibliographic record
Abstract
Retinopathy of prematurity (ROP) is a significant cause of potentially preventable blindness in preterm infants worldwide. It is a disease caused by abnormal retinal vascularization that, if not detected and treated in a timely manner, can lead to retinal detachment and severe long term vision impairment. Neonatologists and pediatricians have an important role in the prevention, detection, and management of ROP. Geographic differences in the epidemiology of ROP have been seen globally over the last several decades because of regional differences in neonatal care. Our understanding of the pathophysiology, risk factors, prevention, screening, diagnosis, and treatment of ROP have also evolved over the years. New technological advances are now allowing for the incorporation of telemedicine and artificial intelligence in the management of ROP. In this comprehensive update, we provide a comprehensive review of pathophysiology, classification, diagnosis, global screening, and treatment of ROP. Key historical milestones as well as touching upon the very recent updates to the ROP classification system and technological advances in the field of artificial intelligence and ROP will also be discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".