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Artificial intelligence in individualized retinal disease management.

Zi-Ran Zhang1,2, Jia-Jun Li1,2, Ke-Ran Li1,2

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|August 19, 2024
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This summary is machine-generated.

Artificial intelligence (AI) enhances retinal disease diagnosis and treatment by analyzing diverse data. This review highlights AI

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Area of Science:

  • Ophthalmology
  • Medical Informatics
  • Computer Science

Background:

  • Artificial intelligence (AI) is increasingly vital for intelligent data analysis.
  • AI demonstrates significant efficacy in ophthalmology for retinal disease identification, diagnosis, and classification.
  • AI enables comprehensive mapping of retinal diseases for personalized clinical prediction and treatment.

Purpose of the Study:

  • To review recent advancements in AI for predicting and guiding the clinical diagnosis and treatment of retinal diseases.
  • To provide ophthalmologists with precise, individualized, and high-quality treatment strategies.
  • To optimize treatment outcomes through AI-driven insights.

Main Methods:

  • Review of current AI research in ophthalmology.
  • Analysis of various input data methods (tabular, textual, image-based) used in AI models.
  • Examination of combined analyses of multiple data types to enhance accuracy and reliability.

Main Results:

  • AI facilitates individualized prediction of prognosis, risk, and progression for retinal diseases.
  • AI supports the development of tailored interventional therapies.
  • Integration of diverse data sources improves the accuracy and dependability of AI-driven results.

Conclusions:

  • AI is a powerful tool for advancing the diagnosis and treatment of retinal diseases.
  • AI-driven approaches offer personalized medicine strategies in ophthalmology.
  • This review synthesizes key findings to guide future AI applications in retinal care.