Literature DB >> 30500302

Introduction to Machine Learning for Ophthalmologists.

Alejandra Consejo1,2,3,4, Tomasz Melcer3, Jos J Rozema1,2.   

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.

Keywords:  Automated diagnosis; artificial intelligence; machine learning; neural networks; vision sciences

Mesh:

Year:  2018        PMID: 30500302     DOI: 10.1080/08820538.2018.1551496

Source DB:  PubMed          Journal:  Semin Ophthalmol        ISSN: 0882-0538            Impact factor:   1.975


  3 in total

1.  Novel Machine-Learning Based Framework Using Electroretinography Data for the Detection of Early-Stage Glaucoma.

Authors:  Mohan Kumar Gajendran; Landon J Rohowetz; Peter Koulen; Amirfarhang Mehdizadeh
Journal:  Front Neurosci       Date:  2022-05-04       Impact factor: 5.152

2.  Keratoconus Detection Based on a Single Scheimpflug Image.

Authors:  Alejandra Consejo; Jędrzej Solarski; Karol Karnowski; Jos J Rozema; Maciej Wojtkowski; D Robert Iskander
Journal:  Transl Vis Sci Technol       Date:  2020-06-26       Impact factor: 3.283

3.  Machine Learning to Determine Risk Factors for Myopia Progression in Primary School Children: The Anyang Childhood Eye Study.

Authors:  Shi-Ming Li; Ming-Yang Ren; Jiahe Gan; San-Guo Zhang; Meng-Tian Kang; He Li; David A Atchison; Jos Rozema; Andrzej Grzybowski; Ningli Wang
Journal:  Ophthalmol Ther       Date:  2022-01-21
  3 in total

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