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Artificial Intelligence in Dry Eye Disease: A Narrative Review.
Praveena P Nair1,2, Manjiri Keskar2, Pramod T Borghare3
1Ophthalmology, Mandsaur Institute of Ayurved Education and Research, Bhunyakhedi, IND.
Cureus
|October 25, 2024
Summary
Artificial intelligence (AI) offers promising solutions for diagnosing and managing dry eye disease (DED). Further research is needed to overcome limitations and fully integrate AI into clinical practice for improved patient outcomes.
Area of Science:
- Ophthalmology
- Medical Informatics
Background:
- Dry eye disease (DED) is a prevalent, multifactorial ocular condition with complex diagnosis and management.
- Diverse symptoms and underlying causes present clinical challenges in effectively treating DED.
Purpose of the Study:
- To explore the application of artificial intelligence (AI) in the diagnosis, treatment, and management of dry eye disease.
- To review AI-driven tools and their potential to enhance diagnostic accuracy and personalize patient care.
Main Methods:
- Narrative review of current literature on AI in dry eye disease.
- Examination of AI-driven tools including machine learning algorithms and imaging technologies.
Main Results:
- AI demonstrates potential in improving diagnostic accuracy and tailoring treatment strategies for DED.
- AI tools can analyze complex data for pattern recognition and predictive modeling in DED management.
Conclusions:
- AI shows significant promise for advancing the care of patients with dry eye disease.
- Addressing limitations such as clinical validation, data privacy, and ethical considerations is crucial for AI integration.
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