Large Language Models In Ophthalmology

By improving digital eye care and eliminating clinical workflow bottlenecks, generative AI and large language models are changing ophthalmology. ChatGPT, a chatbot based on large language models (LLMs) and GPT-3.5 families, has been acclaimed for its capacity to hold human-like conversations and deliver complex answers to various issues. LLM technology has several medical applications, including virtual consultations, appointment scheduling, clinical memo writing, treatment recommendations, and assisting patients in self-organizing and managing their health information. Because of expanding and aging populations, the substantial reliance on tertiary-level health care in ophthalmology is becoming unsustainable. LLM technology can potentially improve the patient experience in eye care while optimizing physician care delivery. However, difficulties sometimes accompany innovation, such as over-referral by primary-care services, extended waiting lists for appointments, confusing routes from the patient’s perspective, and patients lingering in the care of tertiary institutions forever. LLMs can address or reduce these difficulties by improving the patient experience and optimizing physician care delivery.

LLMs show significant promise in ophthalmology, providing radical ways to improve clinical operations and care paradigms. However, researchers must address fundamental concerns about their robustness and reliability before integrating these models into existing healthcare systems. Although we remain optimistic about LLMs, drawing parallels with other digital ophthalmology tools such as telemedicine and ocular photo-based deep learning, researchers emphasize the critical importance of accuracy assessment, governance, and the implementation of protective measures when integrating them into clinical and care settings.

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