Cerebral apoplexy attack risk prediction system and device and storage medium

Abstract

The invention discloses a cerebral apoplexy attack risk prediction system. The system comprises a data acquisition unit, a preprocessing unit, a feature screening unit, a model establishing unit and a model prediction unit, wherein the data acquisition unit is used for acquiring health data information of a target crowd and performing desensitization processing; the preprocessing unit is used for performing standardized processing on basic data information of the target crowd and marking a cerebral apoplexy risk category; the feature screening unit is used for screening cerebral apoplexy feature data based on an IV value analysis method to obtain feature data with relatively high model prediction value, and forming a data set; the model establishing unit is used for training data by utilizing an Adaboost enhanced learning method based on logistic regression and establishing a fusion model; and the model prediction unit is used for predicting to-be-tested sample data through the fusion model to obtain the cerebral apoplexy risk category. According to the system, accurate analysis of the cerebral apoplexy risk category is realized based on the health data information of the target crowd, so that the attack risk prediction efficiency can be improved.

Description

technical field [0001] The invention belongs to the technical field of health management, and in particular relates to a stroke risk prediction system, equipment and a storage medium. Background technique [0002] "Cerebral stroke", also known as "stroke", is an acute cerebrovascular disease that seriously threatens human life and health. Stroke is often characterized by high morbidity, high mortality, and high disability rate. Especially for the elderly, it will cause serious death or leave different degrees of disability, which is extremely troublesome for patients and their families. [0003] At present, the medical community believes that the prevention of stroke is the best preventive measure. However, in the current existing technology, risk prediction is only performed unilaterally from clinical symptoms, which leads to the inability to achieve the goal of accurate identification and early prevention and treatment. The use of a stroke risk prediction model can be us...

AI Technical Summary

Problems solved by technology

However, in the current existing technology, risk prediction is only performed unilaterally from clinical symptoms, which leads to the inability to achieve the goal of accurate identification and early prevention and treatment

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