Study of machine learning techniques for disease detection in the eye

Machine learning is a branch of artificial intelligence in which a computer learns to make predictions from a set of data without explicit human intervention. In recent years, deep learning emerges as one of the most promising machine learning methods due to its powerful generalizing capability to d...

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Main Author:	Yogaindran S/O Murugan
Other Authors:	Ng Beng Koon
Format:	Final Year Project
Language:	English
Published:	Nanyang Technological University 2023
Subjects:	Engineering::Electrical and electronic engineering
Online Access:	https://hdl.handle.net/10356/167066
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Institution:	Nanyang Technological University
Language:	English

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spelling	sg-ntu-dr.10356-1670662023-07-07T15:46:01Z Study of machine learning techniques for disease detection in the eye Yogaindran S/O Murugan Ng Beng Koon School of Electrical and Electronic Engineering EBKNg@ntu.edu.sg Engineering::Electrical and electronic engineering Machine learning is a branch of artificial intelligence in which a computer learns to make predictions from a set of data without explicit human intervention. In recent years, deep learning emerges as one of the most promising machine learning methods due to its powerful generalizing capability to different modality of data. For medical Summary diagnosis, machine learning-based systems have been deployed in several subfields such as oncology, cardiology and ophthalmology to help doctors identify diseased areas from medical images within short period of time. This project will investigate segmentation techniques for OCT angiography and multimodal learning for comprehensive retinal diseases detection and diagnosis. Bachelor of Engineering (Electrical and Electronic Engineering) 2023-05-21T11:01:50Z 2023-05-21T11:01:50Z 2023 Final Year Project (FYP) Yogaindran S/O Murugan (2023). Study of machine learning techniques for disease detection in the eye. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/167066 https://hdl.handle.net/10356/167066 en A2197-221 application/pdf Nanyang Technological University
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	Engineering::Electrical and electronic engineering
spellingShingle	Engineering::Electrical and electronic engineering Yogaindran S/O Murugan Study of machine learning techniques for disease detection in the eye
description	Machine learning is a branch of artificial intelligence in which a computer learns to make predictions from a set of data without explicit human intervention. In recent years, deep learning emerges as one of the most promising machine learning methods due to its powerful generalizing capability to different modality of data. For medical Summary diagnosis, machine learning-based systems have been deployed in several subfields such as oncology, cardiology and ophthalmology to help doctors identify diseased areas from medical images within short period of time. This project will investigate segmentation techniques for OCT angiography and multimodal learning for comprehensive retinal diseases detection and diagnosis.
author2	Ng Beng Koon
author_facet	Ng Beng Koon Yogaindran S/O Murugan
format	Final Year Project
author	Yogaindran S/O Murugan
author_sort	Yogaindran S/O Murugan
title	Study of machine learning techniques for disease detection in the eye
title_short	Study of machine learning techniques for disease detection in the eye
title_full	Study of machine learning techniques for disease detection in the eye
title_fullStr	Study of machine learning techniques for disease detection in the eye
title_full_unstemmed	Study of machine learning techniques for disease detection in the eye
title_sort	study of machine learning techniques for disease detection in the eye
publisher	Nanyang Technological University
publishDate	2023
url	https://hdl.handle.net/10356/167066
_version_	1772827790851178496

Study of machine learning techniques for disease detection in the eye

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