MétaCan
Menu
Back to cohort
Record W2914068526 · doi:10.1109/mwscas.2018.8623927

Age-Related Macular Degeneration Diagnostic Tools: Hardware and Software Development

2018· article· en· W2914068526 on OpenAlexaff
Navid Mohaghegh, Samal Munidasa, X. Ziho, Qiao Owen, Sebastian Magierowski, Ebrahim Ghafar‐Zadeh

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicRetinal Imaging and Analysis
Canadian institutionsYork University
Fundersnot available
KeywordsMacular degenerationSoftwareComputer scienceGraphical user interfaceVisualizationInterface (matter)Computer hardwareEmbedded systemUser interfaceHuman–computer interactionArtificial intelligenceOperating systemMedicineOphthalmology

Abstract

fetched live from OpenAlex

The paper proposes the design and implementation of hardware and software for visual assessment of patient suffering from macular diseases. In this method, a group of graphical patterns are displayed and the patient's responses are collected. The collected data is used to reveal the progress of macular degeneration. Herein we put forward the proposed software method along with various alternative hardware methods to display and collect the data from the patents. We demonstrated the discussed the development of devices including the human computer interface (HCI) smart glove. Also the characterization results for the measurement of response time to each pattern along with the systematic error were achieved using twenty human subjects. The proposed hardware/software platform is the best solution for the visualization assessment dedicated to the patients with a macular disease such as AMD.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.370

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.270
Teacher spread0.249 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations3
Published2018
Admission routes1
Has abstractyes

Explore more

Same topicRetinal Imaging and AnalysisFrench-language works237,207