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Record W2070723979 · doi:10.4103/0974-9233.110619

Teleglaucoma: Improving access and efficiency for glaucoma care

2013· review· en· W2070723979 on OpenAlexaffabout
KarimF Damji, Faazil Kassam, Yogesan Kanagasingam, Enitan Sogbesan, LouisR Pasquale

Bibliographic record

VenueMiddle East African Journal of Ophthalmology · 2013
Typereview
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsMcMaster UniversityMcMaster University Medical CentreUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsMedicineTelemedicineHealth careGlaucomaWork (physics)Emerging technologiesHealthcare systemOptometryRisk analysis (engineering)Computer scienceEngineeringEconomic growthOphthalmology

Abstract

fetched live from OpenAlex

Teleglaucoma is the application of telemedicine for glaucoma. We review and present the current literature on teleglaucoma; present our experience with teleglaucoma programs in Alberta, Canada and Western Australia; and discuss the challenges and opportunities in this emerging field. Teleglaucoma is a novel area that was first explored a little over a decade ago and early studies highlighted the technical challenges of delivering glaucoma care remotely. Advanced technologies have since emerged that show great promise in providing access to underserviced populations. Additionally, these technologies can improve the efficiency of healthcare systems burdened with an increasing number of patients with glaucoma, and a limited supply of ophthalmologists. Additional benefits of teleglaucoma systems include e-learning and e-research. Further work is needed to fully validate and study the cost and comparative effectiveness of this approach relative to traditional models of healthcare.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.005
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.002

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.

Opus teacher head0.073
GPT teacher head0.337
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations46
Published2013
Admission routes2
Has abstractyes

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