A medical imagery analysis method, comprising: obtaining a predefined local disease history image set, and using said disease history image set to train a pre-constructed deep learning network model so as to obtain a disease recognition model (S1); constructing a distillation loss function on the basis of the disease recognition model and a pre-constructed initial diagnostic model (S2); using the distillation loss function to perform distillation training on the initial diagnosis model and obtain a first diagnosis model (S3); with respect to a predefined diagnosis target, training said first diagnosis model and performing output adjustments to obtain a target diagnosis model (S4); when a medical image to be analyzed is received, using said target diagnosis model to analyze said received medical image and obtain an analysis result (S5). The data of the training model may be stored in a blockchain. Further provided are a medical imagery analysis apparatus, an electronic device and a computer-readable storage medium. Resource consumption for computing models for medical imagery analysis may be reduced.
MEDICAL IMAGERY ANALYSIS METHOD, APPARATUS, ELECTRONIC DEVICE AND READABLE STORAGE MEDIUM