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Strabismus and Artificial Intelligence App: Optimizing Diagnostic and Accuracy.

Laura Alves de Figueiredo¹, João Victor Pacheco Dias², Mariza Polati¹

¹Department of Strabismus, Hospital das Clínicas, University of Sao Paulo, Brazil.

Translational Vision Science & Technology

|June 17, 2021

Summary

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This study developed an AI app to objectively classify eye versions in strabismus patients, improving diagnostic accuracy. The mobile application offers a standardized tool for evaluating ocular motility.

Area of Science:

Ophthalmology
Computer Science
Artificial Intelligence

Background:

Clinical evaluation of eye versions is crucial for diagnosing strabismus.
Current methods are subjective and lack standardization, impacting diagnostic accuracy.

Purpose of the Study:

To develop an artificial intelligence (AI) application for objective classification of eye versions into nine gaze positions.
To enhance the accuracy and standardization of strabismus diagnosis.

Main Methods:

Analyzed photos of 110 strabismus patients across nine gazes.
Standardized images using OpenCV and employed a Resnet50 multilabel model with Data Augmentation.
Developed a web app using Streamlit and a mobile version via TensorFlow Lite.

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Main Results:

The AI model was trained to classify eye versions based on gaze and eye laterality.
The developed application demonstrated potential for objective ocular motility evaluation.

Conclusions:

The AI mobile app can supplement traditional clinical evaluations of ocular motility.
Further research and validation are necessary to confirm its clinical utility.