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May 29, 20260 citationsOpen Access

Designing a Fair and AI-Ready Framework for Ophthalmic Imaging Sharing

Toward the Envision Portal: Designing a FAIR and AI-Ready Framework for Ophthalmic Imaging Sharing and Discovery

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Authors

BPBhavesh PatelSSSanjay SoundarajanDPDorian Portillo

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Overview

This poster introduces the Envision Portal for improving data sharing in ophthalmic imaging, indicating a step toward effective AI model training.

Key Points

  • The aim is to develop a robust framework that facilitates the sharing and discovery of ophthalmic imaging datasets for AI model advancement.
  • Introduction of the Envision Portal as an open-source platform.
  • Focus on making datasets FAIR (Findable, Accessible, Interoperable, Reusable).
  • Addressing issues of fragmented sharing and inconsistent data structure.
  • The Envision Portal provides a centralized resource for ophthalmic imaging data.
  • Enhances interoperability between diverse datasets.
  • Supports the development and testing of AI/ML models for disease detection.

Cite This Study

Patel et al. (2026) studied this question.

synapsesocial.com/papers/6a192e79fab5b468c4417975https://doi.org/10.5281/zenodo.20415743
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