An obstetrical special disease associated index mining method based on an electronic health record

Abstract

The invention relates to an obstetrical special disease association index mining method based on an electronic health record. The method comprises the steps of constructing a basic information database, performing disease classification data association, performing data preprocessing, performing sampling to obtain a sample set, constructing a sub-feature screener, constructing a combined screenerand performing association index inspection. The method has the advantages that on the basis of mass electronic health record data, association index mining is carried out, and resource input is low;2, by means of a machine learning method, high-dimensional indexes are automatically analyzed, and a more comprehensive associated index set can be quickly mined; 3, a process-based association indexmining system can be established for the obstetrical special diseases, and the system is easy to popularize in different medical institutions. Therefore, the method provided by the invention is a powerful supplement of a traditional method, on one hand, researchers can be assisted in knowledge discovery, and time and manpower are saved, and on the other hand, a basis can be provided for early prevention and treatment of obstetrical diseases.

Description

technical field [0001] The invention relates to a method for mining associated indicators of obstetrical diseases based on electronic health records, and belongs to the technical field of knowledge discovery methods for obstetrical diseases. Background technique [0002] In recent years, the incidence of patients with obstetric diseases in my country has gradually increased. Clinically, more and more elderly women have seen a significant increase in the incidence of biochemical pregnancy, spontaneous abortion, embryo stop development, birth defects, gestational diabetes, and gestational hypertension. trend, which seriously affects the health of pregnant women and hinders the normal development of the fetus. Obstetrical diseases, especially gestational diabetes, gestational hypertension and other diseases, have large individual differences in diagnosis, the cause of the disease is still unclear, and there is no effective cure. Once the disease occurs, it will bring many advers...

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Problems solved by technology

However, this method has many problems

First of all, this method is difficult and long-term in data collection, and requires high experimental resources; secondly, the experimental design is highly dependent on the clinical experience of the experimenter, so there will be uneven experimental design. If the experimental ideas are wrong, not only will cause The great waste of resources may also lead to wrong conclusions and cause greater harm; thirdly, due to resource constraints, usually the variables that can be evaluated in an experimental design process are limited, and the associated indicators that can be explored are also less

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