Preprandial insulin dosage learning optimization decision-making system assisted by expert experience

Abstract

The invention provides a preprandial insulin dosage learning optimization decision-making system assisted by expert experience. According to the system, artificial intelligence and expert experience methods are combined, information contained in patient blood sugar monitoring and insulin infusion data is mined at the same time, a safe and effective preprandial insulin dosage can still be determined based on historical data under the condition of few samples, the postprandial blood sugar management is improved, and meanwhile, the system is endowed with abilities of continuous adaptive learning and decision-making performance improvement. Therefore, in order to improve postprandial blood glucose management and utilize a small amount of patient historical data, an expert decision-making assisted preprandial insulin dose individualized learning decision-making system is designed, a model prediction evaluation method is introduced into the system, system decision errors under the condition of few samples are effectively avoided, and the blood glucose metabolism rule of the patient is continuously learned; and meanwhile, an iterative updating thought is further introduced, a postprandial blood sugar management target is determined in a self-adaptive mode, and safe and effective preprandial insulin doses can be rapidly determined under the condition that few samples are used for diabetic patients under different illness conditions.

Description

technical field [0001] The invention belongs to the field of preprandial insulin dose decision-making, in particular to a preprandial insulin dose learning optimization decision-making system assisted by expert experience. Background technique [0002] Insulin and glucagon work together to maintain normal blood sugar levels in the body. Diabetes is caused by defective insulin secretion or impaired biological action. It is mainly divided into type 1 and type 2 diabetes. It can lead to acute symptoms such as hypoglycemia, as well as serious long-term complications such as cardiovascular disease and chronic kidney disease. According to statistics from the International Diabetes Federation in 2017, the number of patients in my country reached 114.4 million, making it the largest in the world. With the improvement of modern living standards in our country and the acceleration of the pace of life, diabetes is slowly becoming younger. At the same time, my country has a large popu...

AI Technical Summary

Problems solved by technology

However, the system requires a large amount of sample data when establishing a blood sugar prediction model in the early stage, which is not suitable for the dosage adjustment optimization problem when the patient is hospitalized for a short period of time or when the sample is small in the early stage. At the same time, the system does not give how to make the model self-learning and continuous learning The method of regulating the blood sugar of patients enables the system to transition from a small-sample situation to a multi-sample situation, continuously improving decision-making performance

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