cff-version: 1.2.0
title: 'Code: FAIR AMD OCT Datasets Paper'
type: software
authors:
  - given-names: Nayoon
    family-names: Gim
    affiliation: Department of Ophthalmology, University of Washington (UW)
  - given-names: Bhavesh
    family-names: Patel
    affiliation: FAIR Data Innovations Hub, California Medical Innovations Institute
    orcid: https://orcid.org/0000-0002-0307-262X
identifiers:
  - type: doi
    value: 10.5281/zenodo.12662728
    description: Archive of the source code
repository-code: https://github.com/fairdataihub/code-FAIR-AMD-OCT-paper
abstract: >-
  This is the code associated with the paper title "Publicly Available Imaging
  Datasets for Age-related Macular Degeneration: Evaluation according to the
  Findable, Accessible, Interoperable, Reproducible (FAIR) Principles".
  Age-related macular degeneration (AMD), a leading cause of vision loss among
  older adults, affects more than 200 million people worldwide. In this paper,
  We evaluated openly available AMD-related datasets containing optical
  coherence tomography (OCT) data against the FAIR principles. This repository
  contains the Jupyter notebook developed to analyze data for the paper and
  generate figures.
keywords:
  - FAIR
  - Data
  - AMD
  - OCT
  - Eye
  - Biomedical
license: MIT
version: 1.2.0
date-released: '2025-02-25'
doi: 10.5281/zenodo.14926793

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      "givenName": "Bhavesh"
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  "codeRepository": "https://github.com/fairdataihub/code-FAIR-AMD-OCT-paper",
  "dateCreated": "2024-06-20",
  "dateModified": "2025-02-25",
  "datePublished": "2024-07-28",
  "description": "This is the code associated with the paper title \"Publicly Available Imaging Datasets for Age-related Macular Degeneration: Evaluation according to the Findable, Accessible, Interoperable, Reproducible (FAIR) Principles\". Age-related macular degeneration (AMD), a leading cause of vision loss among older adults, affects more than 200 million people worldwide. In this paper, We evaluated openly available AMD-related datasets containing optical coherence tomography (OCT) data against the FAIR principles. This repository contains the Jupyter notebook developed to analyze data for the paper and generate figures.",
  "downloadUrl": "https://github.com/fairdataihub/code-FAIR-AMD-OCT-paper",
  "funder": {
    "type": "Organization",
    "name": "National Institute of Health"
  },
  "identifier": "10.5281/zenodo.14926793",
  "keywords": [
    "FAIR",
    "Data",
    "AMD",
    "OCT",
    "Eye",
    "Biomedical"
  ],
  "license": "https://spdx.org/licenses/MIT",
  "name": "Code: FAIR AMD OCT Datasets Paper",
  "programmingLanguage": [
    "Jupyter Notebook",
    "Python"
  ],
  "relatedLink": "https://github.com/fairdataihub/inventory-FAIR-AMD-OCT-paper",
  "releaseNotes": "First release",
  "softwareRequirements": "Python 3.11.4",
  "version": "1.2.0",
  "developmentStatus": "inactive",
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