Automated Identification of Different Severity Levels of Diabetic Retinopathy Using a Handheld Fundus Camera and Single-Image Protocol

Malerbi, Fernando K.; Nakayama, Luis Filipe; Melo, Gustavo Barreto; Stuchi, José A.; Lencione, Diego; Prado, Paulo V.; Ribeiro, Lucas Z.; Dib, Sergio A.; Regatieri, Caio V.

doi:10.1016/j.xops.2024.100481

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article4

Other1

Relationship

Self Cite0

Independent5

Authors

Journals

Cited by 5 publications

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Utility of handheld non-mydriatic fundoscopy in a case of bilateral, reversible vision loss in an advanced HIV patient with cryptococcal meningitis in Sub-Saharan Africa

Leon,

Mugabi,

Tran

et al. 2024

Medical Mycology Case Reports

View full text Add to dashboard Cite

Utility of handheld non-mydriatic fundoscopy in a case of bilateral, reversible vision loss in an advanced HIV patient with cryptococcal meningitis in Sub-Saharan Africa

Leon,

Mugabi,

Tran

et al. 2024

Medical Mycology Case Reports

View full text Add to dashboard Cite

Novel artificial intelligence for diabetic retinopathy and diabetic macular edema: what is new in 2024?

Vujosevic,

Limoli,

Nucci

2024

Current Opinion in Ophthalmology

View full text Add to dashboard Cite

Purpose of review Given the increasing global burden of diabetic retinopathy and the rapid advancements in artificial intelligence, this review aims to summarize the current state of artificial intelligence technology in diabetic retinopathy detection and management, assessing its potential to improve care and visual outcomes in real-world settings. Recent findings Most recent studies focused on the integration of artificial intelligence in the field of diabetic retinopathy screening, focusing on real-world efficacy and clinical implementation of such artificial intelligence models. Additionally, artificial intelligence holds the potential to predict diabetic retinopathy progression, enhance personalized treatment strategies, and identify systemic disease biomarkers from ocular images through ‘oculomics’, moving towards a more precise, efficient, and accessible care. The emergence of foundation model architectures and generative artificial intelligence, which more clearly reflect the clinical care process, may enable rapid advances in diabetic retinopathy care, research and medical education. Summary This review explores the emerging technology of artificial intelligence to assess the potential to improve patient outcomes and optimize personalized management in healthcare delivery and medical research. While artificial intelligence is expected to play an increasingly important role in diabetic retinopathy care, ongoing research and clinical trials are essential to address implementation issues and focus on long-term patient outcomes for successful real-world adoption of artificial intelligence in diabetic retinopathy.

show abstract

Diabetic-Retinopathy Classification Using a Modified VGG16 Model

Prasad,

Saikrishna,

Akash

et al. 2024

2024 International Conference on Advances in Computing Research on Science Engineering and Technology (ACROSET)

View full text Add to dashboard Cite

Automated Identification of Different Severity Levels of Diabetic Retinopathy Using a Handheld Fundus Camera and Single-Image Protocol

Cited by 5 publications

References 32 publications

Utility of handheld non-mydriatic fundoscopy in a case of bilateral, reversible vision loss in an advanced HIV patient with cryptococcal meningitis in Sub-Saharan Africa

Utility of handheld non-mydriatic fundoscopy in a case of bilateral, reversible vision loss in an advanced HIV patient with cryptococcal meningitis in Sub-Saharan Africa

Novel artificial intelligence for diabetic retinopathy and diabetic macular edema: what is new in 2024?

Diabetic-Retinopathy Classification Using a Modified VGG16 Model

Contact Info

Product

Resources

About