@inproceedings{2ab654f01ec541ce8601ddd33775154c,
title = "Using AI for Detection, Prediction and Classification of Retinal Detachment",
abstract = "The current state of machine learning (ML) and deep learning (DL) algorithms used to detect, classify and predict the onset of retinal detachment (RD) were examined in this scoping review. This severe eye condition can cause vision loss if left untreated. By analyzing the medical imaging modalities such as fundus photography, AI could help to detect peripheral detachment at an earlier stage. We have searched five databases: PubMed, Google Scholar, ScienceDirect, Scopus, and IEEE. Two reviewers independently carried out the selection of the studies and their data extractions. 32 studies fulfilled our eligibility criteria from the 666 references collected. In particular, based on the performance metrics employed in these studies, this scoping review provides a general overview of emerging trends and practices concerning using ML and DL algorithms for detecting, classifying, and predicting RD.",
keywords = "Retina, Retinal Detachment, convolutional neural networks, deep learning, machine learning",
author = "Hesham Zaky and Ahmed Salem and Mahmoud Alzubaidi and Shah, {Hurmat Ali} and Tanvir Alam and Zubair Shah and Mowafa Househ",
note = "Publisher Copyright: {\textcopyright} 2023 The authors and IOS Press.; 21st International Conference on Informatics, Management, and Technology in Healthcare, ICIMTH 2023 ; Conference date: 01-07-2023 Through 03-07-2023",
year = "2023",
month = jun,
day = "29",
doi = "10.3233/SHTI230578",
language = "English",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press BV",
pages = "636--639",
editor = "John Mantas and Parisis Gallos and Emmanouil Zoulias and Arie Hasman and Househ, {Mowafa S.} and Martha Charalampidou and Andriana Magdalinou",
booktitle = "Healthcare Transformation with Informatics and Artificial Intelligence",
address = "Netherlands",
}