HARNESSING THE POWER OF ARTIFICIAL INTELLIGENCE FOR EARLY DETECTION AND MANAGEMENT OF DIABETIC RETINOPATHY, AGE-RELATED MACULAR DEGENERATION, AND GLAUCOMA: A NARRATIVE REVIEW OF DEEP LEARNING APPLICATIONS IN OPHTHALMOLOGY

Autores

  • Lázaro Felipe Costa Vilela Universidade Federal da Grande Dourados
  • Nádia Oliveira Cabral FAMERV
  • Afrânio Côgo Destefani EMESCAM
  • Vinícius Côgo Destefani DynMolLab

DOI:

https://doi.org/10.51891/rease.v10i8.15395

Palavras-chave:

Diabetic Retinopathy. Macular Degeneration. Glaucoma. Artificial Intelligence. Ophthalmological Diagnostic Techniques.

Resumo

Artificial intelligence (AI) and intense learning (DL) models have emerged as powerful tools in ophthalmology, revolutionizing the early detection and management of ocular diseases such as diabetic retinopathy (DR), age-related macular degeneration (AMD), and glaucoma. This narrative review explores AI's current applications and future potential in these domains, focusing on using convolutional neural networks (CNNs) and other DL architectures to analyze retinal fundus photographs, optical coherence tomography (OCT) images, and visual field tests. By leveraging vast datasets and identifying subtle pathological features, AI models have demonstrated high accuracy, sensitivity, and specificity in detecting these diseases, often surpassing human graders. Integrating AI into clinical practice holds promise for enhancing diagnostic efficiency, facilitating early intervention, and ultimately improving patient outcomes. However, challenges related to data quality, model interpretability (the ability to understand and trust the decisions made by AI models), and ethical considerations (such as patient privacy and consent) must be addressed to fully realize AI's potential in ophthalmology. Future research should focus on validating AI models in diverse populations, exploring novel DL architectures, and developing integrated systems seamlessly incorporating AI into clinical workflows.

Biografia do Autor

Lázaro Felipe Costa Vilela, Universidade Federal da Grande Dourados

Universidade Federal da Grande Dourados.  

Nádia Oliveira Cabral, FAMERV

UniRV - FAMERV (Campus Rio Verde).

Afrânio Côgo Destefani, EMESCAM

Santa Casa de Misericórdia de Vitoria Higher School of Sciences - EMESCAM. Santa Luíza – Vitória – ES Brazil  Molecular Dynamics and Modeling Laboratory (DynMolLab).

Vinícius Côgo Destefani, DynMolLab

Molecular Dynamics and Modeling Laboratory (DynMolLab) Santa Luíza – Vitória – ES – Brazil.

Downloads

Publicado

2024-08-26

Como Citar

Vilela, L. F. C., Cabral, N. O., Destefani, A. C., & Destefani, V. C. (2024). HARNESSING THE POWER OF ARTIFICIAL INTELLIGENCE FOR EARLY DETECTION AND MANAGEMENT OF DIABETIC RETINOPATHY, AGE-RELATED MACULAR DEGENERATION, AND GLAUCOMA: A NARRATIVE REVIEW OF DEEP LEARNING APPLICATIONS IN OPHTHALMOLOGY. Revista Ibero-Americana De Humanidades, Ciências E Educação, 10(8), 3311–3320. https://doi.org/10.51891/rease.v10i8.15395