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Artificial intelligence for detection of optic disc abnormalities.

Dan Milea^1,2,3, Shweta Singhal^1,2,3,4, Raymond P Najjar^2,3

¹Singapore National Eye Centre.

Current Opinion in Neurology

|December 3, 2019

Summary

This summary is machine-generated.

Artificial intelligence (AI) and deep learning methods offer novel ways to detect optic disc abnormalities from retinal images. These AI tools aid in identifying neurological and neuro-ophthalmic conditions, potentially revolutionizing patient care.

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Area of Science:

Ophthalmology
Artificial Intelligence
Neuroscience

Background:

Optic disc abnormalities can indicate serious neurological or neuro-ophthalmic conditions.
Traditional detection methods are being advanced by new AI-driven approaches.
Retinal fundus imaging is crucial for early detection and prediction of complications.

Purpose of the Study:

To review novel artificial intelligence (AI)-based methods for detecting optic disc abnormalities.
To focus on the application of AI in neurology and neuro-ophthalmology.
To highlight the potential of AI in predicting sight and life-threatening complications.

Main Methods:

Review of recent advancements in AI and deep learning for analyzing retinal fundus images.
Focus on automated detection and classification algorithms for optic disc abnormalities.
Integration of AI with innovative fundus imaging hardware.

Main Results:

AI, particularly deep learning, is increasingly vital for detecting and classifying neuro-ophthalmic optic disc abnormalities.
AI methods applied to retinal imaging show promise in predicting complications.
Automated AI detection can significantly aid non-ophthalmic healthcare providers.

Conclusions:

AI-based methods are transforming the detection of optic disc abnormalities.
Deep learning offers a powerful tool for neuro-ophthalmic diagnosis using fundus images.
The integration of AI in fundus imaging may revolutionize neurological and neuro-ophthalmic practice.