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

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

doi:10.33192/smj.v76i2.266303

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

Moez Osama Omar
, Muhammad Jabran Abad Ali
, Soliman Elias Qabillie
, Ahmed Ibrahim Haji
, Mohammed Bilal Takriti
, Ahmed Hesham Atif
, Rangraze Imran

RAK Medical & Health Sciences University

Ras Al Khaima Medical and Health Sciences University

Research output: Contribution to journal › Review article › peer-review

6 Scopus citations

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.

Original language	English
Pages (from-to)	106-115
Number of pages	10
Journal	Siriraj Medical Journal
Volume	76
Issue number	2
DOIs	https://doi.org/10.33192/smj.v76i2.266303
State	Published - 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

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

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10.33192/smj.v76i2.266303

Cite this

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

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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author = "Omar, \{Moez Osama\} and Ali, \{Muhammad Jabran Abad\} and Qabillie, \{Soliman Elias\} and Haji, \{Ahmed Ibrahim\} and Takriti, \{Mohammed Bilal\} and Atif, \{Ahmed Hesham\} and Rangraze Imran",

note = "Publisher Copyright: {\textcopyright} All material is licensed under terms of the Creative Commons Attribution 4.0 International (CC-BY-NC-ND 4.0) license unless otherwise stated.",

year = "2024",

doi = "10.33192/smj.v76i2.266303",

language = "English",

volume = "76",

pages = "106--115",

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publisher = "Faculty of Medicine Siriraj Hospital, Mahidol University",

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T2 - Potential Role of AI-enabled Ocular Scans in the Prediction of Aging and Systemic Disorders

AU - Omar, Moez Osama

AU - Ali, Muhammad Jabran Abad

AU - Qabillie, Soliman Elias

AU - Haji, Ahmed Ibrahim

AU - Takriti, Mohammed Bilal

AU - Atif, Ahmed Hesham

AU - Imran, Rangraze

N1 - Publisher Copyright: © All material is licensed under terms of the Creative Commons Attribution 4.0 International (CC-BY-NC-ND 4.0) license unless otherwise stated.

PY - 2024

Y1 - 2024

N2 - 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.

AB - 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.

KW - AI-Driven ocular scans, Area under the curve (AUC)

KW - Color Fundus Photography (CFP)

KW - Convolutional Neural Network (CNN)

KW - Machine Learning (ML)

KW - ROPtool

KW - deep learning

KW - fundus autofluorescence

KW - retinal age (RA)

UR - https://www.scopus.com/pages/publications/85186127295

U2 - 10.33192/smj.v76i2.266303

DO - 10.33192/smj.v76i2.266303

M3 - Review article

AN - SCOPUS:85186127295

SN - 2629-995X

VL - 76

SP - 106

EP - 115

JO - Siriraj Medical Journal

JF - Siriraj Medical Journal

IS - 2

ER -

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

Abstract

UN SDGs

Keywords

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