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Artificial intelligence in retinal imaging: current status and future prospects.

Katharina A Heger1, Sebastian M Waldstein1

  • 1Department of Ophthalmology, Landesklinikum Mistelbach-Gaenserndorf, Mistelbach, Austria.

Expert Review of Medical Devices
|December 13, 2023
PubMed
Summary

Artificial intelligence (AI) offers a solution to challenges in retinology, aiding in identifying patients needing treatment and planning individualized therapies. AI in retinal imaging promises to enhance ophthalmic care by supporting clinicians, not replacing them.

Keywords:
Age-related macular degeneration (AMD)Ophthalmologyartificial intelligence (AI)deep learning (DL)diabetic retinopathy (DR)fundus photographyoptical coherence tomography (OCT)retinal imaging

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Area of Science:

  • Ophthalmology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • The global population is growing and aging, leading to increased prevalence of vision-threatening retinal diseases.
  • Current retinology faces challenges in patient identification, comprehensive screening, and personalized therapy planning.
  • High-quality ophthalmic care requires innovative solutions like artificial intelligence (AI).

Purpose of the Study:

  • To review current and future applications of AI in retinal imaging.
  • To focus on AI's role in diabetic retinopathy and age-related macular degeneration.
  • To explain AI principles in disease screening, grading, therapy planning, and outcome prediction.

Main Methods:

  • Literature review of AI applications in retinal imaging.
  • Analysis of AI's use in specific retinal diseases like diabetic retinopathy and AMD.
  • Explanation of AI principles for clinical applications.

Main Results:

  • AI has demonstrated significant accomplishments in retinal imaging.
  • AI implementation is poised to transform ophthalmic healthcare.
  • AI supports individualized treatment goals in ophthalmology.

Conclusions:

  • AI in retinal imaging is a promising solution for improving ophthalmic care.
  • AI tools will support clinicians, enhancing efficiency and accuracy.
  • The integration of AI moves towards personalized treatment strategies in ophthalmology.