Evidence map›Paper›PMID 39110574›Full record

ArticleTranslational vision science & technology2024

Transformer-Based Deep Learning Prediction of 10-Degree Humphrey Visual Field Tests From 24-Degree Data.

Min Shi, Anagha Lokhande, Yu Tian, Yan Luo, Mohammad Eslami, Saber Kazeminasab, Tobias Elze, Lucy Q Shen, Louis R Pasquale, Sarah R Wellik and 6 more

Abstract read
In one paragraph

Article in Translational vision science & technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors.

Min ShiHarvard Ophthalmology AI Lab, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Anagha LokhandeHarvard Ophthalmology AI Lab, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Yu TianHarvard Ophthalmology AI Lab, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Yan LuoHarvard Ophthalmology AI Lab, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Mohammad EslamiHarvard Ophthalmology AI Lab, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Saber KazeminasabHarvard Ophthalmology AI Lab, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Tobias ElzeHarvard Ophthalmology AI Lab, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Lucy Q ShenMassachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Louis R PasqualeEye and Vision Research Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Sarah R WellikBascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, FL, USA.
Carlos Gustavo De MoraesEdward S. Harkness Eye Institute, Columbia University Medical Center, New York, NY, USA.
Jonathan S MyersWills Eye Hospital, Thomas Jefferson University, Philadelphia, PA, USA.
Nazlee ZebardastMassachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
David S FriedmanMassachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Michael V BolandMassachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Mengyu WangHarvard Ophthalmology AI Lab, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.

Funding

VISION RESEARCHP30EY003790 · NEI · SCHEPENS EYE RESEARCH INSTITUTE · PI Patricia Ann D'Amore · 1985 to 2026
$25.5M
Relationship between Glaucoma and the Three-Dimensional Optic Nerve Head Related StructureR00EY028631 · NEI · SCHEPENS EYE RESEARCH INSTITUTE · PI WANG, MENGYU · 2021 to 2023
$741k
Personalizing Circumpapillary Retinal Nerve Fiber Layer Thickness Norms for GlaucomaR21EY035298 · NEI · SCHEPENS EYE RESEARCH INSTITUTE · PI WANG, MENGYU · 2023 to 2023
$557k
NEI NIH HHS P30 EY003790NEI NIH HHS R00 EY028631NEI NIH HHS R21 EY035298
6 · The paper itself

Abstract

Purpose: To predict 10-2 Humphrey visual fields (VFs) from 24-2 VFs and associated non-total deviation features using deep learning. Methods: We included 5189 reliable 24-2 and 10-2 VF pairs from 2236 patients, and 28,409 reliable pairs of macular OCT scans and 24-2 VF from 19,527 eyes of 11,560 patients. We developed a transformer-based deep learning model using 52 total deviation values and nine VF test features to predict 68 10-2 total deviation values. The mean absolute error, root mean square error, and the R2 were evaluation metrics. We further evaluated whether the predicted 10-2 VFs can improve the structure-function relationship between macular thinning and paracentral VF loss in glaucoma. Results: The average mean absolute error and R2 for 68 10-2 VF test points were 3.30 ± 0.52 dB and 0.70 ± 0.11, respectively. The accuracy was lower in the inferior temporal region. The model placed greater emphasis on 24-2 VF points near the central fixation point when predicting the 10-2 VFs. The inclusion of nine VF test features improved the mean absolute error and R2 up to 0.17 ± 0.06 dB and 0.01 ± 0.01, respectively. Age was the most important 24-2 VF test parameter for 10-2 VF prediction. The predicted 10-2 VFs achieved an improved structure-function relationship between macular thinning and paracentral VF loss, with the R2 at the central 4, 12, and 16 locations of 24-2 VFs increased by 0.04, 0.05 and 0.05, respectively (P < 0.001). Conclusions: The 10-2 VFs may be predicted from 24-2 data. Translational Relevance: The predicted 10-2 VF has the potential to improve glaucoma diagnosis.

Indexed as

Deep LearningGlaucomaTomography, Optical CoherenceVisual FieldsVisual Field TestsAdultAgedFemaleHumansMaleMiddle AgedVision Disorders

Identifiers

PMID39110574
PMCPMC11316452

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.