Model training method and device, computer equipment and storage medium

Abstract

The embodiment of the invention provides a model training method and device, computer equipment and a storage medium, and belongs to the technical field of artificial intelligence. Comprising the steps of obtaining multiple pieces of inquiry sample data and corresponding prescription sample data; performing prediction processing on the patient sample data and the dialogue sample data through a pre-training model to obtain prescription prediction data; calculating a first loss value according to the plurality of drug prediction data; constructing a drug co-occurrence matrix according to the multiple drug sample data, and calculating a second loss value; and training the pre-training model according to the first loss value and the second loss value to obtain a prescription recommendation model. According to the embodiment of the invention, the drug co-occurrence matrix is constructed through the prescription sample data, and the drug co-occurrence loss is added according to the drug co-occurrence matrix, so that not only is the correlation among a plurality of drugs considered, but also the problem that classifiers are increased along with the increase of the number of the drugs in the prescription recommendation model is avoided, and the training efficiency of the model is improved.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to a model training method and device, computer equipment, and storage media. Background technique [0002] In the task of prescription recommendation, there is usually a dependency relationship between multiple drugs in the prescription, for example, antipyretic patches and cough medicines are usually in the same prescription. Therefore, it is very important to effectively mine the correlation between drugs. Since prescriptions contain more than one drug, prescription recommendation is often converted into a multi-label classification task. However, as the number of drugs increases, the number of classifiers in the prescription recommendation model also increases, which affects the training efficiency of the model. Contents of the invention [0003] The main purpose of the embodiments of the present disclosure is to provide a model training method and device, com...

AI Technical Summary

Problems solved by technology

Since the number of drugs contained in the prescription is more than one, the prescription recommendation is often converted into a multi-label classification task, but as the number of drugs increases, the number of classifiers in the prescription recommendation model also increases, which affects the training efficiency of the model

Images