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Medical index missing data complementing method for patients with peptic ulcer

A technology for peptic ulcer and missing data, applied in the medical field, can solve problems such as only considering time series, and achieve the effect of increasing data accuracy

Active Publication Date: 2019-01-08
SUN YAT SEN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The shortcoming of this method is that it only considers the dimension of time series

Method used

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  • Medical index missing data complementing method for patients with peptic ulcer
  • Medical index missing data complementing method for patients with peptic ulcer
  • Medical index missing data complementing method for patients with peptic ulcer

Examples

Experimental program
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Embodiment 1

[0031] Such as figure 1 , figure 2 , image 3 As shown, a method for completing the missing data of medical indicators of peptic ulcer patients includes the following steps:

[0032] Step S1: read the measurement data of the ulcer patient,

[0033] Step S2: Preprocessing the collected data;

[0034] The main purpose of medical big data preprocessing is to reduce the impact of noisy data on the overall data. Noisy data includes the following types, errors in the entry process, outliers that deviate from most data, and data duplication caused by the merger of heterogeneous data sources.

[0035] In this example, the statistical method is used to detect numerical attributes, and the possible range interval of the attribute is considered to identify outliers, or clustering can be used to identify outliers. The outlier data are then mode corrected.

[0036] Step S201: time aligning the data

[0037] The time of each patient's visit is different. The principle of alignment is...

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PUM

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Abstract

The invention relates to a medical index missing data complementing method for patients with peptic ulcer. According to the method of the invention, an original sparse matrix is decomposed into the product of two matrices with a correlation relation; the drawbacks of a method which complements missing data with only one dimension considered in the prior art can be eliminated; not only is the dimension of correlation relationships between patients considered, but also the dimension of the correlation relationships between time series is considered; a matrix decomposition method is adopted to complement the missing data of the measurement indexes of the patients with peptic ulcer within one year; and therefore, the accuracy of data is improved, references can be provided for the clinical decision-making of doctors, the conditions of the patients can be timely monitored through completed medical data, and the cure rate of the patients can be improved.

Description

technical field [0001] The invention relates to the medical field, and more specifically, to a method for supplementing missing data of medical indicators of patients with peptic ulcer. Background technique [0002] The medical record records the patient's historical health data, including the patient's basic situation, each visit to the doctor, medication and treatment, etc. In the era of big data, rational mining of information hidden behind a large number of medical records can help doctors make clinical decisions. However, due to the different visit times of different patients and the specificity of each person's body in medical big data, medical indicators that change over time generally have the problem of missing data. Therefore, it is an important research direction to complete missing indicators in medical records, and many data completion algorithms have emerged. [0003] In 2013, Liu et al. proposed a tensor completion method for estimating missing values ​​in v...

Claims

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Application Information

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IPC IPC(8): G16H50/20G16H50/70
CPCG16H50/20G16H50/70
Inventor 贾晓玉马锦华
Owner SUN YAT SEN UNIV
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