Exploring artificial intelligence techniques for diabetic retinopathy detection: A case study

Title

Exploring artificial intelligence techniques for diabetic retinopathy detection: A case study

Creator

Vijayalakshmi A.; Unnisa S.; Joshi H.

Description

There is a notable increase in the prevalence of Diabetic Retinopathy (DR) globally. This increase is caused due to type2 diabetes, diabetes mellitus (DM). Among people, diabetes leads to vision loss or Diabetic Retinopathy. Early detection is very much necessary for timely intervention and appropriate treatment on vision loss among diabetic patients. This chapter explores how Artificial Intelligence (AI) methods are helpful in automated detection of diabetic retinopathy. In this chapter deep learning algorithm is proposed that is used to extract important features from retinal images and classify the images to identify the presence of DR. The model is evaluated using various metrics like specificity, sensitivity etc. The results of the case study provide an AI driven solution to existing methods used to identify DR and this can improve the early detection and appropriate treatment at the right time. 2024, IGI Global. All rights reserved.

Source

Intersection of AI and Business Intelligence in Data-Driven Decision-Making, pp. 351-366.

Date

2024-01-01

Publisher

IGI Global

Coverage

Vijayalakshmi A., Christ University, India; Unnisa S., Mount Carmel College, India; Joshi H., Christ University, India

Rights

Restricted Access

Relation

ISBN: 979-836935289-2; 979-836935288-5

Format

Online

Language

English

Type

Book chapter

Identifier

https://doi.org/10.4018/979-8-3693-5288-5.ch013

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215355494&doi=10.4018%2f979-8-3693-5288-5.ch013&partnerID=40&md5=6c53adbc4ae3249e886e85d9463e214b