Latest developments of generative artificial intelligence and applications in ophthalmology

Area of Science:

• Ophthalmology
• Artificial Intelligence
• Medical Technology

Background:

• Generative artificial intelligence (AI) is rapidly transforming diverse fields, including medicine.
• Ophthalmology stands to benefit from AI's capabilities in data processing, documentation, patient communication, and clinical decision support.

Purpose of the Study:

• To review the development and integration of generative AI models in ophthalmology's clinical workflows and research.
• To identify the need for standardized assessment frameworks, robust evidence, and exploration of AI's multimodal potential.
• To address risks associated with AI in ophthalmology and propose a risk management framework.

Main Methods:

• Literature review focusing on generative AI applications in ophthalmology.
• Analysis of AI's potential benefits, including enhanced efficiency, accuracy, personalization, and innovation.
• Examination of risks such as data privacy, bias, adaptation challenges, and job displacement.

Main Results:

• Generative AI can streamline documentation, improve patient-doctor communication, aid decision-making, and simulate clinical trials in ophthalmology.
• A need exists for standardized assessment frameworks and exploration of multimodal AI capabilities.
• Identified risks include data privacy, bias, adaptation friction, over-reliance, and job replacement.

Conclusions:

• Generative AI holds transformative potential for enhancing patient care and operational efficiency in ophthalmology.
• A balanced approach to AI adoption is crucial, supported by a robust risk management framework.
• Further research and development are needed to fully realize AI's benefits while mitigating its risks in eye care.