Abstract: A neural-network-based-implemented ophthalmologic intelligent consultation method includes: performing correction filtering on a consultation voice of a patient, framing the voice into a consultation voice frame sequence, generating a consultation text corresponding to the consultation voice frame sequence based on phoneme recognition and phoneme transcoding, and extracting an ophthalmologically-described disease; performing gray-level filtering, primary picture segmentation, and size equalization operation on an eye picture set of the to-be-diagnosed patient to acquire a standard eyeball picture group; extracting eye white features, pupil features and blood vessel features from the standard eyeball picture group, performing lesion feature analysis on the eye white features, the pupil features and the blood vessel features to acquire an ophthalmologically-observed disease, and based on the ophthalmologically-observed disease and the ophthalmologically-described disease, generating a consultation result.