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Method for predicting ICU duration after aortic dissection cardiac surgery

A technique for aortic dissection, heart surgery

Pending Publication Date: 2020-11-06
THE FIRST AFFILIATED HOSPITAL OF JINAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

These traditional medical scoring methods can evaluate the patient's condition to a certain extent, but the scoring system is rigid and the degree of personalization is low, and it is impossible to predict the postoperative ICU duration of the patient

Method used

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  • Method for predicting ICU duration after aortic dissection cardiac surgery
  • Method for predicting ICU duration after aortic dissection cardiac surgery
  • Method for predicting ICU duration after aortic dissection cardiac surgery

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Embodiment Construction

[0032] In order to have a clearer understanding of the technical features, purposes and effects of the present invention, the specific implementation manners of the present invention will now be described in detail with reference to the accompanying drawings.

[0033] refer to figure 1 , the present invention provides a method for predicting ICU duration after cardiac surgery for aortic dissection, comprising:

[0034] Obtain ICU data from the ICU database after cardiac surgery for aortic dissection, and perform data preprocessing; wherein, the preprocessing methods include at least dummy variable processing, data cleaning, and missing filling processing;

[0035] Based on the kendall correlation coefficient, feature extraction is performed on the preprocessed ICU data, and the features whose correlation coefficient value is higher than the preset threshold are selected;

[0036] Build a machine learning model, and train the built machine learning model based on the extracted...

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Abstract

The invention relates to a method for predicting ICU duration after aortic dissection cardiac surgery. The method comprises the following steps: acquiring ICU data from an ICU database after aortic dissection cardiac surgery, and preprocessing the data; on the basis of a kendall correlation coefficient, carrying out feature extraction on the preprocessed ICU data, and taking features with the correlation coefficient value higher than a preset threshold value; constructing a machine learning model, and training the constructed machine learning model based on the extracted ICU data features; after training is completed, predicting the ICU duration of the patient through real-time ICU data after the aortic dissection cardiac surgery. Through the method, the ICU duration of the patient after the arterial dissection cardiac surgery can be predicted, the mastery degree of the patient and family members on the illness state and the recovery process is improved; meanwhile, a powerful support can be provided for medical personnel to prepare a medical plan.

Description

technical field [0001] The invention relates to the technical field of machine learning, and more specifically, to a method for predicting ICU duration after heart surgery for aortic dissection. Background technique [0002] The Intensive Care Unit (ICU) of a hospital is a place where critically ill patients are densely ill, their conditions are changeable, and there are many crises. A small delay in ICU treatment will greatly increase the risk of death of the patient. In the early stages of these threatening situations, some unusual vital signs appear, along with common complications. The current medical ICU treatment methods mainly rely on the experience of doctors and the accumulation of knowledge in related fields, which makes the work efficiency and quality of diagnosis and treatment not high. Currently in the field of patient condition monitoring and evaluation, there are many scoring systems using medical knowledge for various medical conditions. For example, the o...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/2458G06F16/215G06K9/62G16H50/30
CPCG06F16/2462G06F16/215G16H50/30G06F18/24155
Inventor 张水兴陈秋颖张斌金哲方进
Owner THE FIRST AFFILIATED HOSPITAL OF JINAN UNIV
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