Attribute characteristic reducing method of ECG body concept

Abstract

The invention provides an attribute characteristic reducing method of an ECG body concept. An ECG signal diagnosis body in a medical field is used as a researching object. Through hierarchical weighting matched relation mapping, the invention provides the attribute characteristic reducing method based on an inclusion degree and an information entropy model. The method mainly comprises three stepsof S1, performing body concept attribute meaning importance marking based on a rough membership degree model; S2, performing weighting interval concept grid modeling based on the concept information entropy; and S3, performing concept attribute characteristic adaptive reducing based on hierarchical redundancy. The attribute characteristic reducing method has advantages of effectively improving body concept grade meaning information combining accuracy in an ECG signal diagnosis field, improving quality of a combined medical clinical diagnosis field database, and reducing computing scale required for large-scale mining of the meaning information in a medical field.

Description

technical field [0001] The invention belongs to the technical field of medical semantic network, knowledge grid computing and retrieval, and specifically relates to a method for reducing the attribute characteristics of the ECG ontology concept. Background technique [0002] ECG signal is one of the biosignals used in clinical heart disease diagnosis, which can comprehensively reflect the body surface characteristics of cardiac activity, and has received more and more attention from relevant scholars. ECG signals are affected by factors such as diagnostic criteria for heart disease and differences in disease types, which makes the ECG vary greatly among individuals. The diagnosis of related diseases mainly depends on the subjective judgment of doctors, resulting in inconsistent judgment standards for abnormal ECG signals and misdiagnosis. The rate is higher. [0003] With the rapid development of technologies such as network communication and cloud storage, automatic analys...

AI Technical Summary

Problems solved by technology

The construction of the ECG ontology in the medical field depends on the ECG database in the field. The existing databases cannot directly obtain the implicit and valuable conceptual attributes from the massive ECG data, resulting in the emergence of ECG databases in the same field. Diversity and conflicts make interoperability between knowledge bases in the domain impossible

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