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Using an Automated Hirschberg Test App to Evaluate Ocular Alignment

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Quantitative Assessment of Strabismus Using Cloud AI Computing: Validation Study.

Junxian He^1,2, Jiawei Zhang³, Zheng Wang⁴

¹Schepens Eye Research Institute of Mass Eye & Ear, Harvard Medical School, Boston, MA, United States.

JMIR Formative Research

|November 4, 2025

Summary

This summary is machine-generated.

A new cloud-based AI system, Eyeturn Cloud, accurately measures strabismus angles using smartphone images. This technology offers a convenient and accessible method for vision screening and assessment, potentially aiding in telehealth applications.

Keywords:

AI models artificial intelligence cloud computing smartphone strabismus web app

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Area of Science:

Ophthalmology
Artificial Intelligence
Medical Imaging

Background:

Strabismus measurement is crucial for vision assessment and screening.
Traditional methods often require skilled clinicians or specialized equipment.
Photographic methods offer improved accessibility and convenience.

Purpose of the Study:

To evaluate Eyeturn Cloud, an AI system for measuring strabismus angles.
The system uses smartphone-captured eye images under cover test conditions.

Main Methods:

Eyeturn Cloud employs AI to recognize ocular features and segment the iris.
Strabismus is calculated using iris boundary fitting and corneal reflection.
The system was validated against clinical prism alternate cover test measurements.

Main Results:

A strong correlation (R²=0.95) was observed between Eyeturn Cloud and clinical strabismus measurements.
Bland-Altman analysis showed 95% limits of agreement from -20.2 to 14.6 prism diopters (PD).
Repeatability testing yielded a standard deviation of 1.53 PD.

Conclusions:

The cloud-based AI web app reliably computes strabismus angles.
Its potential utility in telehealth requires further investigation.