Alzheimer’s Disease Detection from Retinal Images Using Machine Learning and Deep Learning Techniques: A Perspective
Year: 2025
Type: article
Abstract: Alzheimer’s disease (AD) is a neurodegenerative disease that results in a loss of cognitive functions. The early discovery of it can potentially stop or decrease the severity of AD. Extensive research has been conducted to find AD biomarkers. In recent years, due to the development of AI technologies and the ease of obtaining retinal images, various machine learning (ML)- and deep learning (DL)-based methods of identifying AD patients from these images have been proposed. These models are significant as they represent a potential screening tool for AD and a tool for identifying biomarkers from retinal images. This paper reviews the recent progress in this direction. It presents an overview of relevant methods and analyzes their strengths and limitations. Also, it discusses common challenges and possible future directions related to this topic.
Source: Applied Sciences
DOI: 10.3390/app15094963
Authors: Adilet Uvaliyev, Leanne Lai Hang Chan
Institution: City University of Hong Kong
Language: English
Topic: Retinal Imaging and Analysis
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,896
Funder: City University of Hong Kong
Award: G8693793903
OpenAlex ID: W4409965380