Intelligent hospital guide method and system integrated based on multi-source knowledge graphs

Abstract

The invention belongs to the computer application field, and discloses an intelligent hospital guide method and system integrated based on multi-source knowledge graphs, for solving the problem of accurate hospital guide of a patient. The intelligent hospital guide method includes the steps: constructing a symptom-disease-department knowledge graph; collecting user symptom description informationand gender and age group information; identifying a symptom set and a patient pre-judging disease set in the user symptom description information through an entity identification and symptom normalization process; calculating the symptom set of the user through an improved TF-IDF algorithm to obtain a possible disease set of the user and the weight of each disease; calculating to obtain the weightof a recommended department by fusing the disease weight and the disease-department correlation degree by utilizing the disease set which the user possibly suffers from, the weight of each disease and the symptom-disease-department knowledge graph; and determining recommended department according to the rank of the department weights.

Description

technical field [0001] The invention belongs to the field of medical information processing, and more specifically, relates to an intelligent diagnosis guidance method based on the fusion of multi-source knowledge graphs. Background technique [0002] Before patients go to the hospital to see a doctor, they often don't know which department they should go to. Usually, the relevant information of seeing a doctor is obtained by searching the hospitals and departments related to one's own disease through the Internet. However, due to the different settings of departments in each hospital and the unreliability of information in the network, patients may choose the wrong hospital and department, and even become victims of false medical advertisements. Therefore, from the perspective of patients, they need accurate and efficient guidance services, which can not only reduce the phenomenon of wrong number registration, save the time of patients visiting a doctor, but also relieve t...

AI Technical Summary

Problems solved by technology

[0004] The following problems cannot be solved in the prior art: (1) The main complaint of the patient may be a statement of the disease, how to effectively identify the symptom information or the disease predicted by the user from the statement (2) How to choose the most suitable hospital and advantageous departments

However, this method is only based on the medical literature database and does not use clinical medical data, so the selected departments are inconsistent with the real situation, and it is impossible to obtain the most suitable hospital and advantageous departments

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