Abstract
The diagnosis of keratoconus is closely related to artificial intelligence. Machine learning is the core of artificial intelligence, machine learning models combined with corneal information are effective supplements in keratoconus diagnosis and provide decision support. These artificial intelligence systems can bring efficiency, reduce artificial misjudgment and effectively reduce manpower costs. In this paper, by summarizing the previous machine learning models that assisted the diagnosis of keratoconus, we may help researchers understand the relevant knowledge in the field of intelligent diagnosis of keratoconus, which is of great significance for further machine learning research.
Published Version
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Schedule a callMore From: [Zhonghua yan ke za zhi] Chinese journal of ophthalmology
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