Medication decision support method and device based on graphic state machine

Abstract

The invention provides a medication decision support method and device based on a graphic state machine. The method comprises the steps of: acquiring a medication consultation statement of the user; extracting a symptom information entity, an allergy information entity and a disease information entity in the medication consultation statement through word segmentation and semantic recognition; forming a graph state machine set which is high in response speed to a target event through three independent graph state machines; analyzing the incidence degree information in the medication consultation statement of the user by using a neural network model and an emotion word segmentation dictionary, and comparing the incidence degree information with the incidence degree information spoken by the user to obtain a corrected value of the incidence degree; removing excessive judgment or underestimated judgment, caused by user emotion factors, on the incidence degree through the correction value, and obtaining accurate incidence degree information; and achieving medication decision support aiming at accurate incidence degree information through the medication decision support device. According to the invention, intelligent judgment on the incidence degree irrelevant to the individual cognitive level of the patient can be realized, and the medication accuracy is improved.

Description

technical field [0001] The invention relates to the field of rational drug use, and more specifically relates to a graph state machine-based drug decision support method and device. Background technique [0002] Drugs refer to substances that are used to prevent, treat, and diagnose human diseases, purposefully regulate human physiological functions, and specify indications or functional indications, usage, and dosage, including Chinese medicinal materials, Chinese herbal pieces, Chinese patent medicines, and chemical raw materials. And its preparations, antibiotics, biochemical drugs, radiopharmaceuticals, serum, vaccines, blood products and diagnostic drugs, etc. As we all know, the application of medicines has played a positive role in improving the health of the people, but it must also be recognized that medicines have two sides. Among them, various factors such as the method of use, quantity, and time of medicines determine their therapeutic effects to a large extent. ...

AI Technical Summary

Problems solved by technology

However, this decision support method is based on the "clinical rational drug use standard database", which is a static database structure, and there may be a slow response (stuck) problem in the actual use process; in addition, the patent method includes a variety of discrimination units , the composition is complicated, and a lot of information will pop up on the doctor's order interface. Too much information will easily interfere with the doctor's judgment, and it is not suitable for the public to distinguish and use

On the other hand, the existing decision support methods for clinical rational drug use use group-level evidence in the form of a static database and provide a probability-based level of evidence, which is likely to cause multiple homogeneous patients to recommend a drug regimen, and lacks the need for individual patients. level intelligence assessment

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