Publication
Title
Introduction to Machine Learning for ophthalmologists
Author
Abstract
New diagnostic and imaging techniques generate such an incredible amount of data that it is often a challenge to extract all information that could be possibly useful in clinical practice. Machine Learning techniques emerged as an objective tool to assist practitioners to diagnose certain conditions and take clinical decisions. In particular, Machine Learning techniques have repeatedly shown their usefulness for ophthalmologists. The possible applications of this technology go much further than been used as diagnostic tool, as it may also be used to grade the severity of a pathology, perform early disease detection, or predict the evolution of a condition. This work reviews not only the latest achievements of Machine Learning in ocular sciences, but also aims to be a comprehensive and concise overview of all steps of the process, with clear and easy explanation for each technical term, focusing on the basic knowledge required to understand Machine Learning.
Language
English
Source (journal)
Seminars in ophthalmology. - London
Publication
Philadelphia : Taylor & francis inc , 2019
ISSN
0882-0538
DOI
10.1080/08820538.2018.1551496
Volume/pages
34 :1 (2019) , p. 19-41
ISI
000456171300003
Pubmed ID
30500302
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identifier
Creation 26.01.2019
Last edited 12.11.2024
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