Abstract: This application describes a medical image classification method, a model training method, and a server. The medical image classification method includes: obtaining, by a device, a medical image data set. The device includes a memory storing instructions and a processor in communication with the memory. The method includes performing, by the device, quality analysis on the medical image data set, to extract feature information of a medical image in the medical image data set; and classifying, by the device, the medical image data set based on the feature information and by using a pre-trained deep learning network for performing anomaly detection and classification, to obtain a classification result.

Abstract: A user input in a source language is received. A set of contextual data is received. The user input is encoded into a user input feature vector. The set of contextual data is encoded into a context feature vector. The user input feature vector and the context feature vector are used to generate a fusion vector. An adaptive neural network is trained to identify a second context feature vector, based on the fusion vector. A second user input in the source language is received for translation into a target language. The adaptive neural network is used to determine, based on the second context feature vector, a second user input feature vector. The second user input feature vector is decoded, based on the source language and the target language, into a target language output. A user is notified of the target language output.

Abstract: This invention discloses a medicinal composition includes a non-coding RNA molecule and an antibody targeting a tumor antigen for preventing and/or treating cancer. This invention uses the synergistic combination of a non-coding RNA molecule or its functional variant or homologue, and an antibody targeting a tumor antigen to prevent and/or treat cancer, thereby providing a novel and effective method in preventing and/or treating various cancers.

Abstract: The present invention relates to methods and compositions for the treatment of psychiatric disorders such as treatment-resistant depression (TRD) with KCNQ (also known as Kv7) channel openers. Also disclosed is a method of inducing or enhancing resilience in a patient by administration of a KCNQ channel opener, such as ezogabine.