Department of Public Health, Ege University, Izmir, Turkey.
Institute of Ophthalmology, University College London, London, UK.
Br J Ophthalmol. 2024 Sep 20;108(10):1335-1340. doi: 10.1136/bjo-2024-325458.
The rapid advancements in generative artificial intelligence are set to significantly influence the medical sector, particularly ophthalmology. Generative adversarial networks and diffusion models enable the creation of synthetic images, aiding the development of deep learning models tailored for specific imaging tasks. Additionally, the advent of multimodal foundational models, capable of generating images, text and videos, presents a broad spectrum of applications within ophthalmology. These range from enhancing diagnostic accuracy to improving patient education and training healthcare professionals. Despite the promising potential, this area of technology is still in its infancy, and there are several challenges to be addressed, including data bias, safety concerns and the practical implementation of these technologies in clinical settings.
生成式人工智能的快速发展将对医疗领域产生重大影响，特别是眼科领域。生成对抗网络和扩散模型能够创建合成图像，有助于开发针对特定成像任务的深度学习模型。此外，多模态基础模型的出现，能够生成图像、文本和视频，为眼科领域带来了广泛的应用。这些应用包括提高诊断准确性、改善患者教育和培训医疗保健专业人员。尽管这项技术具有广阔的前景，但它仍处于起步阶段，还有一些挑战需要解决，包括数据偏差、安全问题以及在临床环境中实际实施这些技术。
