Dietary scheme reactivity prediction model, modeling method and electronic equipment

Abstract

The invention discloses a dietary scheme reactivity prediction model, a modeling method and electronic equipment. The modeling method of the dietary scheme reactivity prediction model comprises the following steps: S101, collecting training data and carrying out preprocessing, wherein the step of collecting the training data and preprocessing the training data comprises the substeps: collecting indexes of a metabolic disease patient and dietary information data; obtaining a dietary scheme effect by evaluating the indexes of the metabolic disease patient; and screening out remarkable influencefactors by analyzing the effect of the dietary scheme; S102, setting a training parameter of the XGBoost; S103, with the significant influence factors and the dietary information data as input of themodel and the dietary scheme effect as output of the model, training the model by adopting a ten-fold cross validation method based on an XGBoost algorithm; and S104, performing prediction by using the model trained in the step S103. The established prediction model can assist a doctor in forming a more effective diet scheme, and the diet intervention effect is improved.

Description

technical field [0001] The invention relates to the fields of biomedical engineering technology and nutrition and health, in particular to a predictive model and a modeling method for the reactivity of a meal plan. Background technique [0002] The role of diet in the prevention and treatment of metabolic diseases cannot be ignored. Studies have shown that proper diet can improve blood sugar, blood pressure and blood lipids in metabolic diseases. However, the current dietary plan prescribed by doctors has the following problems: [0003] (1) The effect of the dietary plan is uncontrollable. Before prescribing the dietary plan, the doctor only knows that the dietary plan can improve the patient's metabolic condition, but it is not clear to what extent the dietary plan can improve. [0004] (2) The current dietary plan cannot be targeted. For patients with the same disease, the dietary plan prescribed by the doctor may be the same, but due to the differences in other conditio...

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Problems solved by technology

[0003] (1) The effect of the dietary plan is uncontrollable. Before prescribing the dietary plan, the doctor only knows that the dietary plan can improve the patient's metabolic condition, but it is not clear to what extent the dietary plan can improve

[0004] (2) The current dietary plan cannot be targeted. For patients with the same disease, the dietary plan prescribed by the doctor may be the same, but due to the differences in other conditions of the individual, the actual effect is different. With the same dietary regimen, some patients improve very well and some patients improve poorly

[0005] (3) The dietary plan is too extensive. According to the guidelines, doctors prescribe which foods users should eat and which foods they should not eat, and fail to quantify more dietary information of patients, such as fat, carbohydrates, sugar, caffeine, alcohol and other indicators and evaluate the impact of these dietary information on the intervention effect

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