Optical coherence tomography’s current clinical medical and dental applications: a review
Bibliographic record
Abstract
Optical coherence tomography (OCT) is a non-invasive investigative technique that is used to obtain high-resolution three-dimensional (3D) images of biological structures. This method is useful in diagnosing diseases of specific organs like the eye, where a direct biopsy cannot be conducted. Since its inception, significant advancements have been made in its technology. Apart from its initial application in ophthalmology for retinal imaging, substantial technological innovations in OCT brought by the research community have enabled its utilization beyond its original scope and allowed its application in many new clinical areas. This review presents a summary of the clinical applications of OCT in the field of medicine (ophthalmology, cardiology, otology, and dermatology) and dentistry (tissue imaging, detection of caries, analysis of dental polymer composite restorations, imaging of root canals, and diagnosis of oral cancer). In addition, potential advantages and disadvantages of OCT are also 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| 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) | 0.005 | 0.002 |
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".