Diabetic Retinopathy (DR) Detection and Grading Using Federated Learning (FL)

S, Pooja Yadav; Vijaykumar, Dehannathparambil Kottarathil; K.R, Mahesh; Suryaprakash, P.; Sasikumar, R.

doi:10.47392/irjash.2023.s054

IRJASH

2023

DOI: 10.47392/irjash.2023.s054

|View full text |Cite

Diabetic Retinopathy (DR) Detection and Grading Using Federated Learning (FL)

Pooja Yadav S¹,

Dehannathparambil Kottarathil Vijaykumar²,

Mahesh K.R³

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Book1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

A Hybrid ArtInt Model to Predict Diabetic Retinopathy

Arumugam,

Mohan

2024

Advances in Healthcare Information Systems and Administration

View full text Add to dashboard Cite

Diabetic retinopathy (DR) is retinal blood vessel damage caused by diabetes (DED). Untreated, the condition can cause blindness. Early visual impairment can be averted by monitoring and treating diabetes. Many scientists have developed machine learning techniques to detect DR earlier. Model results proved their usefulness. A WHO research predicts that 40–45% of the world's 347 million diabetics have DR. Early DR diagnosis and therapy can substantially slow visual loss. Current DR detection approaches entail skilled doctors manually analysing digital fundus images, which can cause miscommunication and postpone therapy. This study grades DR intensity as mild, moderate, or severe. A new AI model uses support vector machines and Vgg-16 to classify DR. The results suggest that integrating both models yields better outcomes than standard models.

show abstract

A Hybrid ArtInt Model to Predict Diabetic Retinopathy

Arumugam,

Mohan

2024

Advances in Healthcare Information Systems and Administration

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Diabetic Retinopathy (DR) Detection and Grading Using Federated Learning (FL)

Cited by 1 publication

References 0 publications

A Hybrid ArtInt Model to Predict Diabetic Retinopathy

A Hybrid ArtInt Model to Predict Diabetic Retinopathy

Contact Info

Product

Resources

About