Preprandial insulin dosage individualized decision-making system based on Gaussian process

A Gaussian process and decision-making system technology, which can be used in medical data mining, computer-aided medical procedures, and promoting communication between doctors or patients. Reduce the risk of hypoglycemia and improve the effect of postprandial blood sugar

Active Publication Date: 2020-12-25
BEIJING INSTITUTE OF TECHNOLOGYGY
View PDF6 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although the patent uses the historical data of insulin infusion to adjust the dose of insulin at meal time, it ignores the data of blood glucose monitoring, and it is dif...

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Preprandial insulin dosage individualized decision-making system based on Gaussian process
  • Preprandial insulin dosage individualized decision-making system based on Gaussian process
  • Preprandial insulin dosage individualized decision-making system based on Gaussian process

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0049] In order to enable those skilled in the art to better understand the solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0050] Such as figure 1 As shown, a Gaussian process-based individualized decision-making system for preprandial insulin dosage includes an individualized model learning module, a risk-sensitive control module, a Bayesian optimization module, and a safety constraint module; meanwhile, each parameter in the present invention is based on FDA certification Determined by UVA / Padova T1DM glucose metabolism simulator simulation.

[0051] The individualized model learning module uses a Gaussian process to learn the blood glucose metabolism rules of diabetic patients, and obtains a postprandial blood glucose prediction model.

[0052] The risk sensitive control module is used ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a preprandial insulin dosage individualized decision-making system based on a Gaussian process. The system utilizes an artificial intelligence method to mine information contained in patient blood glucose monitoring and insulin infusion data at the same time, establishes a postprandial blood glucose prediction model conforming to a human body metabolism rule, utilizes a risksensitive optimization control thought to determine the risk sensitivity coefficient in an individualized mode, and uses a Bayesian optimization method to solve the optimization problem, so the safeand effective preprandial insulin dosage can still be determined even under the condition that deviation exists in model prediction, and postprandial blood glucose management is improved. Therefore, in order to improve postprandial blood glucose management, the preprandial insulin dosage individualized decision-making system based on Gaussian process learning risk sensitive control is designed byutilizing historical data of a patient, the system fully excavates information of historical data of blood glucose metabolism of the patient, and the postprandial blood glucose prediction model is established, so subsequent postprandial blood sugar control or postprandial high and low blood sugar early warning can be conveniently implemented.

Description

technical field [0001] The invention belongs to the technical field of Gaussian process and risk-sensitive control, and in particular relates to an individualized decision-making system for preprandial insulin dosage based on Gaussian process. Background technique [0002] Insulin and glucagon work together to maintain normal blood sugar levels in the body. Diabetes mellitus results from defective insulin secretion or impaired biological action. Type 1 diabetes occurs when insulin is not secreted at all, and type 2 diabetes occurs when insufficient insulin is secreted. Both type 1 and type 2 diabetes 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 ...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G16H50/50G16H50/70G16H80/00G06K9/62G06F17/16
CPCG16H50/50G16H50/70G06F17/16G16H80/00G06F18/29G06F18/214
Inventor 史大威蔡德恒陈婧王军政
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap