Method and device for classifying pregnancy state of user, electronic equipment and medium

Abstract

The invention discloses a method and device for classifying pregnancy state of a user, electronic equipment and a medium. In the application, the method includes: calling a sample data set of a gestational user from an antenatal examination data center, wherein the sample data comprises a gestational week value of the gestational user; continuously optimizing and training the decision tree model through a random forest algorithm to obtain a target prediction model; and acquiring physiological feature data of a to-be-detected user in the gestation period, and inputting the physiological feature data of the to-be-detected user in the gestation period into the target prediction model to obtain a gestation state classification result of the to-be-detected user in the gestation period. By applying the technical scheme of the invention, the Bagging type random forest integration algorithm can be obtained by combining and optimizing the decision tree model, so that the target prediction model capable of determining the pregnancy state classification can be generated for the user in the pregnancy period; therefore, the purpose of automatically judging the pregnancy state of the user in the gestation period according to the physiological feature data of the user in the gestation period can be achieved, and then corresponding processing can be conducted on the user in a targeted mode.

Description

technical field [0001] This application relates to data processing technology, especially a method, device, electronic equipment and medium for classifying the user's pregnancy status. Background technique [0002] With the development and wide application of communication technology, the application frequency and research depth of machine learning algorithms in the medical field are increasing rapidly. In particular, pregnancy status monitoring for users during pregnancy is a more characteristic category of machine learning algorithms. [0003] Furthermore, in the process of monitoring the user's pregnancy status during pregnancy, it is usually determined based on the user's characteristic data. Among them, for obtaining user characteristic data, in related technologies, useful information in massive data can be mined by using data mining, and by discovering the laws existing in user characteristic data and the interrelationships among them, it can be provided to decision ...

AI Technical Summary

Problems solved by technology

However, the mathematical mining challenges brought by disease data are huge. The disease data to be processed has a high dimensionality and complex data structure, which requires the model to have a stronger learning adaptability

Images