Literature DB >> 30556381

Can Artificial Intelligence Make Screening Faster, More Accurate, and More Accessible?

Zhixi Li1, Stuart Keel2, Chi Liu1, Mingguang He1,2.   

Abstract

Diabetic retinopathy, glaucoma, and age-related macular degeneration are leading causes of vision loss and blindness worldwide. They tend to be asymptomatic in the early phase of disease and therefore require active screening programs to identify the patients requiring referral and treatment. Deep learning-based artificial intelligence technology has recently become a major topic in the field of ophthalmology. This paper aimed to provide a general view of the major findings on the application of deep learning for the classification of eye diseases from common imaging modalities. In the future, it is expected that these technologies will be applied in real-world screening programs to improve their efficiency and affordability. Copyright 2018 Asia-Pacific Academy of Ophthalmology.

Entities:  

Keywords:  artificial intelligence; deep learning; screening

Mesh:

Year:  2018        PMID: 30556381     DOI: 10.22608/APO.2018438

Source DB:  PubMed          Journal:  Asia Pac J Ophthalmol (Phila)        ISSN: 2162-0989


  6 in total

1.  Multivariable Logistic Regression And Back Propagation Artificial Neural Network To Predict Diabetic Retinopathy.

Authors:  Litong Yao; Yifan Zhong; Jingyang Wu; Guisen Zhang; Lei Chen; Peng Guan; Desheng Huang; Lei Liu
Journal:  Diabetes Metab Syndr Obes       Date:  2019-09-25       Impact factor: 3.168

2.  Artificial intelligence in ophthalmology: Is it just hype with no substance or the real McCoy.

Authors:  Santosh V Patil
Journal:  Indian J Ophthalmol       Date:  2019-07       Impact factor: 1.848

Review 3.  Artificial intelligence in gastric cancer: a translational narrative review.

Authors:  Chaoran Yu; Ernest Johann Helwig
Journal:  Ann Transl Med       Date:  2021-02

4.  Barriers and facilitators to diabetic retinopathy screening within Australian primary care.

Authors:  Matthew J G Watson; Peter J McCluskey; John R Grigg; Yogesan Kanagasingam; Judith Daire; Mohamed Estai
Journal:  BMC Fam Pract       Date:  2021-11-30       Impact factor: 2.497

5.  Acceptability of artificial intelligence-based retina screening in general population.

Authors:  Payal Shah; Divyansh Mishra; Mahesh Shanmugam; M J Vighnesh; Hariprasad Jayaraj
Journal:  Indian J Ophthalmol       Date:  2022-04       Impact factor: 2.969

6.  Validation of Deep Convolutional Neural Network-based algorithm for detection of diabetic retinopathy - Artificial intelligence versus clinician for screening.

Authors:  Payal Shah; Divyansh K Mishra; Mahesh P Shanmugam; Bindiya Doshi; Hariprasad Jayaraj; Rajesh Ramanjulu
Journal:  Indian J Ophthalmol       Date:  2020-02       Impact factor: 1.848

  6 in total

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