Method for using neural network to forecast hypertension

Abstract

The invention relates to the technical field of hypertension prevalence forecasting preformed according to personal basic information and healthy information during the medical process, in particular to a method for using a neural network to forecast hypertension. The method for using the neural network to forecast the hypertension includes following steps: (1) finding out dangerous factors which influence the hypertension; (2) extracting health survey data which influences the hypertension; (3) confirming dangerous factors which really influences the hypertension; (4) collecting health information survey data of the dangerous factors which really influences the hypertension; (5) screening the data; (6) performing standardization processing on valid data; (7) building an MLP (multilayer perceptron) model of a BP (back propagation) neural network, and forecasting whether a person is suffered from the hypertension or not through the MLP model of the BP neural network; (8) comparing a forecasted result with an actual situation whether the person is suffered from the hypertension so as to obtain probability details in forecasting of the situation that the person is suffered from the hypertension and the other situation that the person is not suffered from the hypertension, performed through the method for using the neural network to forecast the hypertension. The method for using the neural network to forecast the hypertension provides a scientific basis for old people to prevent hypertension disease in advance, and enables the old people to early discover, early interfere and early cure the hypertension.

Description

technical field [0001] The invention relates to the technical field of hypertension prediction based on personal basic information and health information during medical treatment, in particular to a method for predicting hypertension using a neural network genetic algorithm. Background technique [0002] Hypertension is a major controllable chronic disease in the world, and has become the main cause of stroke, coronary heart disease and heart and kidney failure. At present, the prevalence of hypertension in my country is greater than 20%, with more than 200 million patients, and the incidence rate is increasing year by year. Therefore, the prevention and treatment of hypertension is a major problem in the field of population and health in my country. [0003] The efficacy of hypertension drugs is moving from group research to individual research, so an effective prediction model provides a scientific basis for people's drug treatment of hypertension, and also provides a rese...

AI Technical Summary

Problems solved by technology

At present, the model path for the prediction of hypertension is not yet clear, and some methods are immature

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