Beyond Vision: Potential Role of AI-enabled Ocular Scans in the Prediction of Aging and Systemic Disorders: Role of AI-enabled Ocular Scans in the Prediction of Aging and Systemic Disorders

Moaz Osama Omar; Muhammed Jabran         Abad Ali; Soliman Elias                    Qabillie; Ahmed Ibrahim                      Haji; Mohammed Bilal Takriti                 Takriti; Ahmed Hesham                    Atif; Imran Rangraze

doi:10.33192/smj.v76i2.266303

Authors

Moaz Osama Omar RAK Medical and Health Sciences University, RAK, United Arab Emirates
Muhammed Jabran Abad Ali RAK Medical and Health Sciences University, RAK, United Arab Emirates
Soliman Elias Qabillie RAK Medical and Health Sciences University, RAK, United Arab Emirates
Ahmed Ibrahim Haji RAK Medical and Health Sciences University, RAK, United Arab Emirates
Mohammed Bilal Takriti Takriti RAK Medical and Health Sciences University, RAK, United Arab Emirates
Ahmed Hesham Atif RAK Medical and Health Sciences University, RAK, United Arab Emirates
Imran Rangraze Internal Medicine, RAK Medical and Health Sciences University, RAK, United Arab Emirates

DOI:

https://doi.org/10.33192/smj.v76i2.266303

Keywords:

fundus autofluorescence, ROPtool, Convolutional Neural Network (CNN), Color Fundus Photography (CFP), Machine Learning (ML), AI-Driven ocular scans, Area under the curve (AUC), deep learning, retinal age (RA)

Abstract

In all medical subfields, including ophthalmology, the development of artificial intelligence (AI), particularly cutting-edge deep learning frameworks, has sparked a quiet revolution. The eyes and the rest of the body are anatomically related because of the unique microvascular and neuronal structures they possess. Therefore, ocular image-based AI technology may be a helpful substitute or extra screening method for systemic disorders, particularly in areas with limited resources. This paper provides an overview of existing AI applications for the prediction of systemic diseases from multimodal ocular pictures, including retinal diseases, neurological diseases, anemia, chronic kidney disease, autoimmune diseases, sleep disorders, cardiovascular diseases, and various others. It also covers the process of aging and its predictive biomarkers obtained from AI-based retinal scans. Finally, we also go through these applications existing problems and potential future paths.

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