Neural network-based medical department recommendation method and device

Abstract

The invention relates to the field of intelligent decision, and discloses a neural network-based medical department recommendation method. The method comprises the following steps: receiving inquiry data input by users, and performing feature extraction on the inquiry data to obtain feature inquiry data; identifying disease tags of the feature inquiry data by using a tag classification network of a disease entity detection model, and identifying disease entities of the disease tags by using an entity regression network of the disease entity detection model to obtain first disease entities; searching second disease entities matched with the feature inquiry data from an inquiry database; selecting disease entities with the same disease type from the first disease entities and the second disease entities to obtain target disease entities; and matching the target disease entities with medical departments in a medical department library, and recommending the successfully matched medical departments to the users. In addition, the invention also provides a neural network-based medical department recommendation device, electronic equipment and a storage medium. The recommendation accuracy of the medical departments can be improved.

Description

technical field [0001] The present application relates to the field of intelligent decision-making, and in particular to a neural network-based medical department recommendation method, device, electronic equipment, and computer-readable storage medium. Background technique [0002] With the continuous development and improvement of artificial intelligence technology, it has greatly enriched and facilitated people's daily life. At present, in the medical field, many hospitals are equipped with machines that include intelligent guidance services. The purpose is to use the Internet technology platform and machine learning, The statistical learning method realizes the online intelligent guidance function in a data-driven way, and recommends departments to patients, so as to maximize the subjective initiative of the patients, so that they can effectively and accurately find the medical services they need. [0003] At present, department recommendation is usually implemented by a...

AI Technical Summary

Problems solved by technology

[0003] At present, department recommendation is usually implemented by a rule-based recommendation method, that is, an intelligent guidance machine or program guides the consultation information of a patient step by step, thereby outputting the corresponding department. However, such a recommendation method is easily affected by the intelligent guidance system. Influenced by the rules set by the diagnostic machine or program, that is, users describe their own physical conditions according to the steps set by the intelligent diagnostic machine or program, and it is easy to ignore the physical data not involved in the intelligent diagnostic machine or program, which will affect the recommendation of the department the accuracy of

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