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Diagnosing Systemic Disorders with AI Algorithms Based on Ocular Images

The advent of artificial intelligence (AI), especially the state-of-the-art deep learning frameworks, has begun a silent revolution in all medical subfields, including ophthalmology. Due to their specific microvascular and neural structures, the eyes are anatomically associated with the rest of the...

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Autores principales: Li, Huimin, Cao, Jing, Grzybowski, Andrzej, Jin, Kai, Lou, Lixia, Ye, Juan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10298137/
https://www.ncbi.nlm.nih.gov/pubmed/37372857
http://dx.doi.org/10.3390/healthcare11121739
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author Li, Huimin
Cao, Jing
Grzybowski, Andrzej
Jin, Kai
Lou, Lixia
Ye, Juan
author_facet Li, Huimin
Cao, Jing
Grzybowski, Andrzej
Jin, Kai
Lou, Lixia
Ye, Juan
author_sort Li, Huimin
collection PubMed
description The advent of artificial intelligence (AI), especially the state-of-the-art deep learning frameworks, has begun a silent revolution in all medical subfields, including ophthalmology. Due to their specific microvascular and neural structures, the eyes are anatomically associated with the rest of the body. Hence, ocular image-based AI technology may be a useful alternative or additional screening strategy for systemic diseases, especially where resources are scarce. This review summarizes the current applications of AI related to the prediction of systemic diseases from multimodal ocular images, including cardiovascular diseases, dementia, chronic kidney diseases, and anemia. Finally, we also discuss the current predicaments and future directions of these applications.
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spelling pubmed-102981372023-06-28 Diagnosing Systemic Disorders with AI Algorithms Based on Ocular Images Li, Huimin Cao, Jing Grzybowski, Andrzej Jin, Kai Lou, Lixia Ye, Juan Healthcare (Basel) Review The advent of artificial intelligence (AI), especially the state-of-the-art deep learning frameworks, has begun a silent revolution in all medical subfields, including ophthalmology. Due to their specific microvascular and neural structures, the eyes are anatomically associated with the rest of the body. Hence, ocular image-based AI technology may be a useful alternative or additional screening strategy for systemic diseases, especially where resources are scarce. This review summarizes the current applications of AI related to the prediction of systemic diseases from multimodal ocular images, including cardiovascular diseases, dementia, chronic kidney diseases, and anemia. Finally, we also discuss the current predicaments and future directions of these applications. MDPI 2023-06-13 /pmc/articles/PMC10298137/ /pubmed/37372857 http://dx.doi.org/10.3390/healthcare11121739 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Li, Huimin
Cao, Jing
Grzybowski, Andrzej
Jin, Kai
Lou, Lixia
Ye, Juan
Diagnosing Systemic Disorders with AI Algorithms Based on Ocular Images
title Diagnosing Systemic Disorders with AI Algorithms Based on Ocular Images
title_full Diagnosing Systemic Disorders with AI Algorithms Based on Ocular Images
title_fullStr Diagnosing Systemic Disorders with AI Algorithms Based on Ocular Images
title_full_unstemmed Diagnosing Systemic Disorders with AI Algorithms Based on Ocular Images
title_short Diagnosing Systemic Disorders with AI Algorithms Based on Ocular Images
title_sort diagnosing systemic disorders with ai algorithms based on ocular images
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10298137/
https://www.ncbi.nlm.nih.gov/pubmed/37372857
http://dx.doi.org/10.3390/healthcare11121739
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