Abstract: The invention relates to an artificial intelligence cataract analysis system, including a pattern recognition module for recognizing a photo mode of an input eye image, wherein the photo mode is divided according to the slit width of the illuminating slit during photographing of the eye image and/or whether a mydriatic treatment is carried out; a preliminary analysis module used for selecting a corresponding deep learning model for eye different photo modes, analyzing the characteristics of lens in the eye image by using a deep learning model, and further performing classification in combination with cause and severity degree of a disease. The invention can perform cataract intelligent analysis on eye images with different photo modes by using deep learning models, so that the analysis accuracy is improved.

Abstract: The invention relates to an artificial intelligence eye disease screening service method and a system, in which the method includes acquiring the ophthalmic examination data of a user, in which the ophthalmic examination data is obtained by a technician in a primary hospital through an ophthalmic examination on the user; performing the artificial intelligence screening on the ophthalmic examination data to obtain a screening result; determining whether the screening result is normal or not; generating an ophthalmic examination report if the screening result is normal; and uploading the ophthalmic examination data to ophthalmologists of the superior hospitals for review and generating an ophthalmic examination report according to the review if the screening result is abnormal. The invention can partly balance the ophthalmic resources between collaborative primary hospitals and superior hospitals, and achieve a large-scale and highly efficient eye disease screening with wide coverage.

Abstract: The invention relates to an artificial intelligence cataract analysis system, including a pattern recognition module for recognizing a photo mode of an input eye image, wherein the photo mode is divided according to the slit width of the illuminating slit during photographing of the eye image and/or whether a mydriatic treatment is carried out; a preliminary analysis module used for selecting a corresponding deep learning model for eye different photo modes, analyzing the characteristics of lens in the eye image by using a deep learning model, and further performing classification in combination with cause and severity degree of a disease. The invention can perform cataract intelligent analysis on eye images with different photo modes by using deep learning models, so that the analysis accuracy is improved.