| Diabetes is a metabolic disease,it is caused by insufficient insulin secretion in the human body.The sugar in the human body cannot be metabolized,leading to high blood sugar.In severe cases,sugar is detected in the urine,hence the name diabetes.In daily life,living conditions are getting better and better,people’s eating habits have changed,and diabetes is rich and the disease does not exist.People’s current diet is not only egg-milk meat,but also rich fruits and vegetables and various types of beverage desserts.For this reason,people’s daily intake of sugar has increased significantly,which has also led to an increase in the incidence of diabetes.The same is true for young people,due to the improvement of the quality of life,young people are growing up in “honey pots” because their parents’ control over the diet structure of teenagers is not very strict,and the self-control ability of teenagers is relatively poor.Sugar-based foods are extremely attractive to adolescents,leading to dietary intake of polysaccharides,which is one of the leading causes of the increasing number of younger diabetics.In addition,elderly patients with diabetes will be accompanied by potential complications,such as myocardial infarction,eye disease,etc.,which will put a greater burden on the patient’s body.Good regular eating habits and a healthy green lifestyle are the guarantees to maintain normal posture and maintain the normal functioning of the body.Under the influence of various factors,it is necessary to have an effective mechanism to supervise and warn,which will make people raise awareness of prevention.Therefore,the research and implementation of diabetes early warning system is of great significance.The prediction analysis result of the early warning system will give the user an important prompt in time,prompting people to adjust and change their living habits in time or go to the hospital for medical treatment for more specific examinations.In the course of this study,we consulted diabetes experts and collected a large number of diabetes symptom attributes using questionnaires.The random forest algorithm is used to analyze the corresponding data,and an early warning model is established,and the model is applied to the early warning system.The main research contents of this paper are as follows:1.Questionnaire survey conducted by Questionnaire Star,collecting more than one thousand pieces of data information,including information about the related attributes of diabetes and non-diabetes,and then analyzing and sorting the information and using it as a training sample.2.The data samples are divided into training set and test set according to the ratio of 3:7.The random forest algorithm is used to classify the training set and then test the test set to obtain the accuracy of the random forest algorithm classification,thus obtaining an early warning model,and then according to this model,a disease probability is obtained.3.Design and implement the diabetes early warning system,which mainly includes three parts.The first part is the user information registration and related personal information processing part;the second part is the system’s predictive analysis function,which analyzes the user’s disease probability;the third part is The system administrator has some basic management operations on user and user information.4.Perform tests on algorithm experiments and early warning systems to verify the effectiveness of the system.Using the diabetes warning system studied in this paper,users can predict the risk of diabetes at any time based on personal relevant indicator data,which can effectively improve the prevention awareness of potential patients with diabetes,and actively adjust and improve their living conditions through predictive analysis. |
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