Glaucoma screening: analysis of conventional and telemedicine‐friendly devices
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Portable, telemedicine-friendly devices offer novel opportunity for screening and monitoring glaucoma in the remote and rural regions of the world. This study examines the effective combination of telemedicine-friendly screening devices for detection of glaucoma in relation with conventional, hospital-based devices. METHODS: A total of 399 eyes were screened with telemedicine-friendly devices and conventional, hospital-based devices such as ophthalmoscope, tonometer and perimeter. RESULTS: Combination of age and family history of glaucoma alone has a sensitivity of 35.6% (specificity 94.2%, area under the curve 0.81, correctly classified 81.1%) and an addition of telemedicine-friendly or conventional visual field tests optimized the sensitivity to 91.1% (specificity 93.6%, area under the curve 0.95, correctly classified 93%). Analysis indicates good agreement between vertical cup-to-disc ratio by ophthalmoscopy and digital image reading. An addition of intraocular pressure test does not change sensitivity (35.6%) and specificity (94.2%). CONCLUSION: This study indicates that evaluations of cup-to-disc ratio and visual field, using telemedicine-friendly devices, are most useful tools in screening for glaucoma. When used together these devices may be an alternative for conventional glaucoma screenings.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it