The Advancement of ChatGPT in Ophthalmology
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Keywords

CHATGPT; ophthalmology; deep learning; large language model; artificial intelligence

Categories

How to Cite

Zeng, Y., Wu, shinan, & Shao, Y. (2024). The Advancement of ChatGPT in Ophthalmology. American Journal of Translational Medicine, 8(1), 28–35. Retrieved from https://journals3.publicknowledgeproject.org/index.php/ajtm/article/view/3040

Abstract

The advent of large language models such as ChatGPT, indicative of the early stages of artificial general intelligence (AGI), underscores their potential in transforming health care. These models promise to enhance patient care, broaden healthcare access, and streamline clinical decisions. However, their integration into healthcare systems must be meticulously managed to address risks such as inaccurate medical advice, patient privacy breaches, the creation of misleading references and images, and students’ overdependence on AGI for medical education. Crucial to this integration is the implementation of stringent supervision and regulatory measures. These will ensure AGI’s safe and beneficial use in ophthalmology and other medical fields. By continually refining its limitations and leveraging its strengths, AGI can be used to significantly improve patient care in ophthalmology. It can also aid in effectively summarizing medical knowledge and optimizing healthcare processes, thereby offering widespread societal benefits. This careful approach ensures that AGI’s revolutionary capabilities are harnessed responsibly, maintaining a balance between technological advancement and patient safety.

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