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Smart Vision Transparency: Efficient Ocular Disease Prediction Model Using Explainable Artificial Intelligence.

Sagheer Abbas1, Adnan Qaisar2, Muhammad Sajid Farooq2,3

  • 1Department of Computer Science, Prince Mohammad Bin Fahd University, Dhahran 34754, Saudi Arabia.

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Summary
This summary is machine-generated.

This study introduces an explainable artificial intelligence (XAI) model for accurate ocular disease prediction. The novel transfer learning approach achieves 95.74% accuracy, enhancing trust in AI for ophthalmic diagnostics.

Keywords:
artificial intelligence (AI)explainable AI (XAI)ocular disease

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Area of Science:

  • Ophthalmic Medicine
  • Artificial Intelligence in Healthcare
  • Machine Learning for Disease Prediction

Background:

  • Early ocular disease prediction is critical in ophthalmology.
  • Current AI/ML models for eye diseases lack transparency, hindering clinical trust.
  • Traditional methods struggle with accurate ocular disease prediction.

Purpose of the Study:

  • To develop an efficient transfer learning model for ocular disease prediction.
  • To integrate explainable artificial intelligence (XAI) to ensure transparency in AI decision-making.
  • To address the limitations of traditional methods and current AI approaches in ophthalmic diagnostics.

Main Methods:

  • Proposed an efficient transfer learning model.
  • Integrated explainable artificial intelligence (XAI) for transparent decision-making.
  • Evaluated model performance on ocular disease prediction tasks.

Main Results:

  • Achieved 95.74% accuracy in ocular disease prediction.
  • Demonstrated superior performance compared to previously published methods.
  • Provided comprehensive rationale for AI-driven predictions, enhancing transparency.

Conclusions:

  • The proposed XAI-integrated transfer learning model significantly advances ocular healthcare.
  • Explainable AI is crucial for building trust and enhancing clinical decision-making in AI-powered diagnostics.
  • The model shows transformative potential for smart vision in the healthcare sector.