Tele-Oncology: A Validation Study of Choroidal and Iris Nevi
Bibliographic record
Abstract
BACKGROUND/AIMS: To evaluate teleophthalmological assessment of choroidal and iris nevi (tele-oncology) compared to traditional in-person clinical evaluation for detection of either axial or basal growth. METHODS: This is a validation study. All 97 eyes of 99 patients were evaluated with an in-person ocular oncology visit utilizing standard testing, and subsequently had a tele-oncology evaluation with the standardized tests. The tele-oncology reviewer was blinded to the in-person examination findings. The primary study outcome was detection of nevus growth on tele-oncology compared to in-person clinical examination. RESULTS: = 38; 44%). By tele-oncology assessment, 11 eyes showed growth. Ten of these patients had growth confirmed on in-person clinical examination. Resultantly, tele-oncology assessment of choroidal and iris nevi growth had a sensitivity of 100%, specificity of 99%, positive predictive value (PPV) of 91%, and negative predictive value (NPV) of 100%. CONCLUSIONS: The results of this study suggest that tele-oncology is a safe platform for monitoring choroidal and iris nevi for growth, with excellent sensitivity, specificity, PPV, and NPV.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".