Intelligent inquiry method and device

Abstract

The invention discloses an intelligent inquiry method and device, and the method comprises the steps: selecting a disease distinguishing symptom from the related symptoms of a candidate disease when the accuracy of the selected candidate disease does not meet a preset confirmation condition, wherein the disease distinguishing symptom is a symptom capable of distinguishing at least two types of candidate diseases; and taking the disease distinguishing symptom as the next inquiry symptom to be displayed to the user, and determining a diagnosis result according to the received description information of the user for the disease distinguishing symptom. According to the invention, on the basis of accurately obtaining the diagnosis result, the number of interactions with the user is reduced, thediagnosis efficiency is improved, and the diagnosis accuracy is not lost.

Description

technical field [0001] The invention relates to the technical field of computer processing of medical information, in particular to an intelligent consultation method and device. Background technique [0002] In recent years, in order to improve the efficiency of disease diagnosis and reduce the workload of doctors, some smart devices for triage and guidance have emerged as the times require. Common triage guidance smart devices generally ask the user multiple symptom questions to collect the user's symptom information, and compare the collected symptom information with the symptom characteristics of each disease, so as to diagnose the disease that the user may suffer from. However, the intelligent triage and guidance method in the prior art usually needs to keep asking the user until the preset termination threshold condition of a specific disease is triggered. On the one hand, this method leads to too many rounds of human-computer interaction, The diagnosis efficiency is ...

AI Technical Summary

Problems solved by technology

However, the intelligent triage and guidance method in the prior art usually needs to keep asking the user until the preset termination threshold condition of a specific disease is triggered. On the one hand, this method leads to too many rounds of human-computer interaction, The diagnosis efficiency is not high, and the user experience is poor. On the other hand, due to the different symptoms and characteristics of the disease, there are inconsistencies in the symptom information experienced by the user, which leads to unstable diagnosis and affects the follow-up treatment of users.

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