Diabetes data processing and analysis system based on machine learning

Through machine learning technology, the trend and seasonal terms of blood glucose timing data of diabetic patients are decomposed, normal indicators are calculated and reference data are screened, which solves the problem of insufficient reference data in the prior art and achieves more accurate treatment plan assistance.

CN118969314BActive Publication Date: 2024-12-10QIANJIANGYUE HEALTH IND (GUANGZHOU) CO LTD
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Patent Information

Application Number
CN202411441072.X
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-10-16
Publication Date
2024-12-10
Estimated Expiration
2044-10-16

AI Technical Summary

Technical Problem

When screening reference data for diabetic patients, the reference data is not referenced only based on whether the blood sugar level is normal, and it is impossible to effectively assist doctors in formulating personalized treatment plans, which are greatly affected by individual differences and data indicators.

Method used

Using a machine learning-based diabetes data processing and analysis system, we can obtain blood glucose timing data, decompose trend items and seasonal items, calculate initial and final normal indicators, and classify and screen medical record sample data based on these indicators, and build a reference database to assist in treatment. Plan formulation.

Benefits of technology

It improves the reference value of the screened reference data, can more accurately reflect the normal situation and reference value of the medical record sample data, and helps doctors formulate more targeted treatment plans.

✦ Generated by Eureka AI based on patent content.

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Abstract

The present invention relates to the field of medical data processing technology, and in particular to a diabetes data processing and analysis system based on machine learning. The system includes: a diabetes data acquisition module, which is used to obtain medical record sample data of diabetic patients; a normal index analysis module, which is used to analyze the change trend and fluctuation of blood sugar time series data in each medical record sample data, and accurately quantify the final normal index of each medical record sample data in combination with numerical characteristics; a reference database construction module, which is used to classify all medical record sample data based on multiple parameters in the medical record sample data, and in each category, based on the above-mentioned acquired final normal index, select medical record sample data with high normality and high reference value, so as to construct a reference database. The present invention can accurately screen medical record sample data with high reference value, so that the constructed reference database can more accurately assist doctors in formulating treatment plans.
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Citation Information

Patent Citations

  • Diabetes digital health management system based on big data and artificial intelligence

    CN115274140A

  • Diabetes risk assessment system

    CN118737447A