Keratoconus causes the central cornea to bulge forward during the dise ase process,giving the cornea a conical shape,and leading to highly irregular myopia and astigmatism,causing damage of vision with different degrees.The disea se generally occurs in the adolescent period,in order to timely treat and to av oid serious lesions, it is of great signif icance to screen and distinguish keratoconus.In addition,clinical diagnosis of keratoconus is usually detected by co rneal topography,which can obtain morphological changes of the cornea,but ther e is a certain misdiagnosis rate.At present,it has been found that the change of mechanical properties of cornea is prior to morphology.Therefore,from the p erspective of corneal biomechanics,this paper proposed a model to distinguish k eratoconus based on multi-layer perceptron (MLP) neural network.Firstly,corneal visualization scheimpflug technology (Corvis -ST) was used to measure the biomechanical video of cornea,and corneal biomechanic al parameters were obtained as a data set,including normal cornea and keratocon us.Then,MLP neural network model was constructed for corneal biomechanical par ameter data sets,in which 70% data sets were used as training sets and 30% as t est sets.The results of training and testing on the datasets showed that the ac curacy of keratoconus differentiation was 97.6%.