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Chronic disease recurrence prediction method, device and computer equipment based on xgboost model

A chronic disease and model technology, which is applied in the field of chronic disease recurrence prediction based on the xgboost model, can solve problems such as low accuracy of calculation results, achieve the effect of solving unbalanced distribution and improving accuracy

Active Publication Date: 2021-10-01
THE FIRST AFFILIATED HOSPITAL OF GUANGZHOU MEDICAL UNIV (GUANGZHOU RESPIRATORY CENT) +1
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Problems solved by technology

[0005] Based on this, it is necessary to address the technical problem of low accuracy of calculation results in the above-mentioned chronic disease recurrence prediction method, and provide a chronic disease recurrence prediction method, device, computer equipment and storage medium based on the xgboost model that can reasonably solve the above technical problems

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  • Chronic disease recurrence prediction method, device and computer equipment based on xgboost model
  • Chronic disease recurrence prediction method, device and computer equipment based on xgboost model
  • Chronic disease recurrence prediction method, device and computer equipment based on xgboost model

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[0045] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.

[0046] It should be noted that the prediction model chooses xgboost (Extreme Gradient Boosting). The main algorithm idea is to train a base learner with initial samples, and adjust the sample distribution according to the learning performance, so that samples with poor performance get more attention, and then Continuously iteratively train the next base learner with samples after adjusting the distribution until the number of base learners reaches the specified number.

[0047] In one embodiment, such as figure 1 As shown, a chronic disease recurrence prediction method ba...

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Abstract

The present application relates to a chronic disease recurrence prediction method, device and computer equipment based on the xgboost model. The method includes: acquiring the diagnostic data to be tested; the diagnostic data to be tested includes time of admission and discharge; according to the time of admission and discharge, using the diagnostic data to be tested as a model training sample; using the model training sample to train the The xgboost model is used to obtain a trained model; the trained model is used to predict the recurrence of chronic diseases on the diagnostic data to be tested. Through the adoption of this scheme, the problem of unbalanced distribution of training samples can be solved, thereby improving the accuracy of chronic disease recurrence prediction results.

Description

technical field [0001] The present application relates to the field of disease prevention and control, in particular to a chronic disease recurrence prediction method, device, computer equipment and storage medium based on the xgboost model. Background technique [0002] Chronic obstructive pulmonary disease (COPD), referred to as COPD, has always been a chronic obstructive disease that is difficult to cure. According to statistics, in 2015, an estimated 3.17 million people died of COPD worldwide, accounting for 5% of the world's mortality rate in the same year; there were 251 million cases of COPD in the world in 2016, and the impact of COPD on human life The threat can no longer be ignored. [0003] In order to improve this situation, more and more scholars and medical institutions have begun to pay attention to the prediction of the recurrence of the chronic disease within one year, so as to prevent the aggravation of the disease. However, the existing methods for predi...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16H50/30
CPCG16H50/30
Inventor 郑劲平陈一君梁振宇李菁张冬莹罗俊宇
Owner THE FIRST AFFILIATED HOSPITAL OF GUANGZHOU MEDICAL UNIV (GUANGZHOU RESPIRATORY CENT)
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