In this study

artificial intelligence aided diagnosis system of fundus images was applied to clinical teaching of ophthalmology to explore its role in improving the teaching quality. Taking the clinical teaching of diabetic retinopathy as an example

we analyzed the specific steps

effects and improvement strategies. The results revealed that the course could be more interesting and impressing by using the typical cases provided by the artificial intelligence aided diagnosis system of fundus images. In the meanwhile

this system provided the excellent chances for ophthalmology postgraduates to exercise after class

which deepened their understanding of knowledge and enhanced their learning enthusiasm. The application effect has been affirmed and recognized by students.