Li Li, Kunhong Xiao, Xianwen Shang, Wenyi Hu, Mayinuer Yusufu, Ruiye Chen, Yujie Wang, Jiahao Liu, Taichen Lai, Linling Guo, Jing Zou, Peter van Wijngaarden, Zongyuan Ge, Mingguang He, Zhuoting Zhu
Meibomian gland dysfunction (MGD) is increasingly recognized as a critical contributor to evaporative dry eye, significantly impacting visual quality. With a global prevalence estimated at 35.8%, it presents substantial challenges for clinicians. Conventional manual evaluation techniques for MGD face limitations characterized by inefficiencies, high subjectivity, limited big data processing capabilities, and a dearth of quantitative analytical tools. With rapidly advancing artificial intelligence (AI) technique revolutionizing ophthalmology, studies are now leveraging sophisticated AI methodologies, including computer vision, unsupervised learning, and supervised learning, to facilitate comprehensive analyses of meibomian gland (MG) evaluations...
July 16, 2024: Survey of Ophthalmology