Utilization of deep learning to quantify fluid volume of neovascular age-related macular degeneration patients based on swept-source OCT imaging: The ONTARIO study

• Simrat K. Sodhi,

  Roles Data curation, Formal analysis, Investigation, Methodology, Writing – original draft

  Affiliation School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom

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• Austin Pereira,

  Roles Writing – original draft, Writing – review & editing

  Affiliation Department of Ophthalmology & Visual Sciences, University of Toronto, Toronto, ON Canada

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• Jonathan D. Oakley,

  Roles Software, Validation

  Affiliation Voxeleron LLC, San Francisco, United States of America

  https://orcid.org/0000-0003-2474-9609

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• John Golding,

  Roles Methodology

  Affiliation Vitreous Retina Macula Specialists of Toronto, Etobicoke, ON, Canada

  https://orcid.org/0000-0003-0363-7325

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• Carmelina Trimboli,

  Roles Project administration

  Affiliation Vitreous Retina Macula Specialists of Toronto, Etobicoke, ON, Canada

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• Daniel B. Russakoff,

  Roles Software

  Affiliation Voxeleron LLC, San Francisco, United States of America

  https://orcid.org/0000-0002-5713-1242

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• Netan Choudhry

  Roles Conceptualization, Funding acquisition, Supervision, Writing – review & editing

  * E-mail: netan.choudhry@vrmto.com

  Affiliations Department of Ophthalmology & Visual Sciences, University of Toronto, Toronto, ON Canada, Vitreous Retina Macula Specialists of Toronto, Etobicoke, ON, Canada, Cleveland Clinic Canada, Toronto, ON, Canada

  https://orcid.org/0000-0002-1998-2257

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