Literature DB >> 35218987

Artificial Intelligence for Glaucoma: Creating and Implementing Artificial Intelligence for Disease Detection and Progression.

Lama A Al-Aswad1, Rithambara Ramachandran2, Joel S Schuman3, Felipe Medeiros4, Malvina B Eydelman5.   

Abstract

On September 3, 2020, the Collaborative Community on Ophthalmic Imaging conducted its first 2-day virtual workshop on the role of artificial intelligence (AI) and related machine learning techniques in the diagnosis and treatment of various ophthalmic conditions. In a session entitled "Artificial Intelligence for Glaucoma," a panel of glaucoma specialists, researchers, industry experts, and patients convened to share current research on the application of AI to commonly used diagnostic modalities, including fundus photography, OCT imaging, standard automated perimetry, and gonioscopy. The conference participants focused on the use of AI as a tool for disease prediction, highlighted its ability to address inequalities, and presented the limitations of and challenges to its clinical application. The panelists' discussion addressed AI and health equities from clinical, societal, and regulatory perspectives.
Copyright © 2022. Published by Elsevier Inc.

Entities:  

Keywords:  Artificial intelligence; Deep learning; Glaucoma; Imaging

Year:  2022        PMID: 35218987      PMCID: PMC9399304          DOI: 10.1016/j.ogla.2022.02.010

Source DB:  PubMed          Journal:  Ophthalmol Glaucoma        ISSN: 2589-4196


  51 in total

1.  African Descent and Glaucoma Evaluation Study (ADAGES): II. Ancestry differences in optic disc, retinal nerve fiber layer, and macular structure in healthy subjects.

Authors:  Christopher A Girkin; Pamela A Sample; Jeffrey M Liebmann; Sonia Jain; Christopher Bowd; Lida M Becerra; Felipe A Medeiros; Lyne Racette; Keri A Dirkes; Robert N Weinreb; Linda M Zangwill
Journal:  Arch Ophthalmol       Date:  2010-05

2.  Detecting Preperimetric Glaucoma with Standard Automated Perimetry Using a Deep Learning Classifier.

Authors:  Ryo Asaoka; Hiroshi Murata; Aiko Iwase; Makoto Araie
Journal:  Ophthalmology       Date:  2016-07-07       Impact factor: 12.079

3.  Deep Learning and Glaucoma Specialists: The Relative Importance of Optic Disc Features to Predict Glaucoma Referral in Fundus Photographs.

Authors:  Sonia Phene; R Carter Dunn; Naama Hammel; Yun Liu; Jonathan Krause; Naho Kitade; Mike Schaekermann; Rory Sayres; Derek J Wu; Ashish Bora; Christopher Semturs; Anita Misra; Abigail E Huang; Arielle Spitze; Felipe A Medeiros; April Y Maa; Monica Gandhi; Greg S Corrado; Lily Peng; Dale R Webster
Journal:  Ophthalmology       Date:  2019-09-24       Impact factor: 12.079

4.  Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.

Authors:  Varun Gulshan; Lily Peng; Marc Coram; Martin C Stumpe; Derek Wu; Arunachalam Narayanaswamy; Subhashini Venugopalan; Kasumi Widner; Tom Madams; Jorge Cuadros; Ramasamy Kim; Rajiv Raman; Philip C Nelson; Jessica L Mega; Dale R Webster
Journal:  JAMA       Date:  2016-12-13       Impact factor: 56.272

5.  Racial variations in the prevalence of primary open-angle glaucoma. The Baltimore Eye Survey.

Authors:  J M Tielsch; A Sommer; J Katz; R M Royall; H A Quigley; J Javitt
Journal:  JAMA       Date:  1991-07-17       Impact factor: 56.272

6.  A Deep Learning Algorithm to Quantify Neuroretinal Rim Loss From Optic Disc Photographs.

Authors:  Atalie C Thompson; Alessandro A Jammal; Felipe A Medeiros
Journal:  Am J Ophthalmol       Date:  2019-01-26       Impact factor: 5.258

7.  Assessing Glaucoma Progression Using Machine Learning Trained on Longitudinal Visual Field and Clinical Data.

Authors:  Avyuk Dixit; Jithin Yohannan; Michael V Boland
Journal:  Ophthalmology       Date:  2020-12-25       Impact factor: 14.277

8.  An objective structural and functional reference standard in glaucoma.

Authors:  Eduardo B Mariottoni; Alessandro A Jammal; Samuel I Berchuck; Leonardo S Shigueoka; Ivan M Tavares; Felipe A Medeiros
Journal:  Sci Rep       Date:  2021-01-18       Impact factor: 4.379

Review 9.  Ethics of Artificial Intelligence in Medicine and Ophthalmology.

Authors:  Yasser Ibraheem Abdullah; Joel S Schuman; Ridwan Shabsigh; Arthur Caplan; Lama A Al-Aswad
Journal:  Asia Pac J Ophthalmol (Phila)       Date:  2021 May-Jun 01

Review 10.  A review of algorithms for segmentation of optical coherence tomography from retina.

Authors:  Raheleh Kafieh; Hossein Rabbani; Saeed Kermani
Journal:  J Med Signals Sens       Date:  2013-01
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  1 in total

Review 1.  The Development and Clinical Application of Innovative Optical Ophthalmic Imaging Techniques.

Authors:  Palaiologos Alexopoulos; Chisom Madu; Gadi Wollstein; Joel S Schuman
Journal:  Front Med (Lausanne)       Date:  2022-06-30
  1 in total

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