Video interpretation and diagnosis of pediatric amblyopia and eye disease
Bibliographic record
Abstract
AIM: The aim of this study was to assess the potential of using video screening to interpret the results of paediatric eye examinations. DESIGN: Prospective multi-centred, blinded study. METHODS: Children aged 5 months to 11 years referred to a paediatric ophthalmology centre were enrolled in the study. Outcome measures included the degree of agreement between examiners for assessment of various aspects of paediatric eye examination. In Phase 1, children were individually assessed in the clinic by three different examiners to determine the level of agreement. In Phase 2 a video recording was made of the first ophthalmologist examining the children. The other two examiners viewed the video recordings to make their diagnoses. Areas of assessment included lid function, pupillary function, ocular motility, strabismus, nystagmus, torticollis and facial asymmetry. Agreement between examiners was measured using Gwet's agreement coefficient (AC1). RESULTS: A total of 27 patients in Phase 1 (mean age 4.0 years) and 160 children in Phase 2 (mean age 4.8 years) underwent clinical and video-recorded screening. In Phase 1, all but one area of ocular examination (heterotropia) achieved ≥84% agreement between three examiners. In Phase 2, there was greater variation between direct clinical examination and interpretation of video findings, ranging from 55-100% agreement. CONCLUSION: Using experienced clinicians and changing only one variable in Phase 2 (the method of assessment - direct examination versus video interpretation), the results show the possible usefulness of video-recorded screening as a means of assessing children. Further research is indicated to assess the accuracy of ophthalmologists interpreting video recordings of eye examinations performed by trained non-eye-care professionals.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".