Abstract: An information recommendation method, an apparatus, a device, and a medium based on embedding table compression are provided. The method includes: determining, based on a preset compression ratio, to-be-compressed features and non-compressed features in a to-be-compressed embedding table of a recommendation model, generating a similarity index matrix based on a similarity between the to-be-compressed features and the uncompressed features; generating an index dictionary based on the similarity index matrix; substituting a first feature mapping dictionary based on the index dictionary to generate a second feature mapping dictionary, wherein the first feature mapping dictionary is generated based on a data set; and acquiring to-be-recommended data, replacing features in the to-be-recommended data according to the second feature mapping dictionary, inputting replaced features into the recommendation model, and outputting a prediction result.

Abstract: A method and a system for simulating magnetic resonance echo-planar imaging artifacts. Firstly, for K-space artifacts, K-space data are restored through normal magnetic resonance images, and the K-space data are modified pertinently, and then images with artifacts are reconstructed; for susceptibility artifacts, a susceptibility model is constructed through normal magnetic resonance images, and the magnetic field distribution is reconstructed, and then the images with distortion artifacts are reconstructed. According to the present disclosure, a large number of artifact data sets with different artifact types and artifact degrees can be quickly created through a small number of normal images, thus laying a foundation for the research of identifying artifacts, eliminating or weakening artifacts.

Abstract: An information recommendation method, an apparatus, a device, and a medium based on embedding table compression are provided. The method includes: determining, based on a preset compression ratio, to-be-compressed features and non-compressed features in a to-be-compressed embedding table of a recommendation model, generating a similarity index matrix based on a similarity between the to-be-compressed features and the uncompressed features; generating an index dictionary based on the similarity index matrix; substituting a first feature mapping dictionary based on the index dictionary to generate a second feature mapping dictionary, wherein the first feature mapping dictionary is generated based on a data set; and acquiring to-be-recommended data, replacing features in the to-be-recommended data according to the second feature mapping dictionary, inputting replaced features into the recommendation model, and outputting a prediction result.

Abstract: A method and a system for simulating magnetic resonance echo-planar imaging artifacts. Firstly, for K-space artifacts, K-space data are restored through normal magnetic resonance images, and the K-space data are modified pertinently, and then images with artifacts are reconstructed; for susceptibility artifacts, a susceptibility model is constructed through normal magnetic resonance images, and the magnetic field distribution is reconstructed, and then the images with distortion artifacts are reconstructed. According to the present disclosure, a large number of artifact data sets with different artifact types and artifact degrees can be quickly created through a small number of normal images, thus laying a foundation for the research of identifying artifacts, eliminating or weakening artifacts.