Medical information classification method and apparatus based on classification model and computer equipment

Abstract

The invention discloses a medical information classification method and apparatus based on a classification model, computer equipment and a storage medium. The method comprises the steps of acquiringspecified medical information of a specified object; inputting the specified medical information into a first disease prediction architecture in a preset disease classification model to obtain a firstpredicted disease; inputting the first prediction disease into a selection connection layer, and acquiring a specified second disease prediction architecture selected by the selection connection layer; inputting the first predicted disease and the specified medical information into the specified second disease prediction architecture to obtain a second predicted disease; mapping the specified medical information, the first predicted disease and the second predicted disease into a disease classification vector; calculating the value of a distance between a standard classification vector and the disease classification vector; and if the distance value is smaller than a preset distance threshold, classifying the specified medical information into a specified category. Therefore, classification accuracy is improved.

Description

technical field [0001] The present application relates to the computer field, in particular to a classification model-based medical information classification method, device, computer equipment and storage medium. Background technique [0002] Classification of medical information benefits the field of medical analysis and related fields, among others. The current classification of medical information only focuses on the data at the current time, and it is a technical solution to predict medical information and then classify it. However, only using the data at the current time as the classification standard has a low data utilization rate, because the classification is rough and accurate classification cannot be achieved. Therefore, when it is necessary to call (for example, medical data needs to be called when medical resources are allocated), due to inaccurate classification, it is easy to cause biased data call, which will adversely affect the final result. Therefore, t...

AI Technical Summary

Problems solved by technology

However, only the data at the current time is used as the classification standard, and the data utilization rate is low, because the classification is rough and accurate classification cannot be achieved

Therefore, when it is necessary to call (for example, medical data needs to be called when medical resources are allocated), due to inaccurate classification, it is easy to cause biased data call, which will adversely affect the final result

Therefore, the accuracy of the classification scheme of medical information of traditional technology needs to be improved

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