Establishment method of severe spinal cord injury prognosis prediction model

A spinal cord injury and prediction model technology, applied in medical data mining, medical automated diagnosis, medical informatics, etc., can solve problems such as the inability to give prognostic probability, and achieve the effect of assisting in judging probability

Active Publication Date: 2021-06-18
THE THIRD AFFILIATED HOSPITAL OF SUN YAT SEN UNIV +1
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  • Claims
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Problems solved by technology

However, it is often impossible to give an objective and quantifiable prognost

Method used

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  • Establishment method of severe spinal cord injury prognosis prediction model
  • Establishment method of severe spinal cord injury prognosis prediction model
  • Establishment method of severe spinal cord injury prognosis prediction model

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Embodiment Construction

[0026] The present invention is a method for constructing a novel prognosis prediction model based on clinical data of patients with severe spinal cord injury.

[0027] The method for establishing the prognosis prediction model of severe spinal cord injury of the present invention is to provide a novel prognosis prediction model constructed based on clinical data of patients with severe spinal cord injury, comprising the following steps:

[0028](1) Include clinical characteristics of patients with potential predictive value: demographic information includes race, gender, age, body mass index, type of admission, type of ICU, source of admission, length of ICU, length of hospitalization after discharge from ICU, etc.; vital signs include respiratory rate , heart rate, systolic and diastolic blood pressure, mean arterial pressure; laboratory data including white blood cell count, red blood cell count RBC, platelet count, basophils, eosinophils, neutrophils, lymphocytes, monocytes...

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Abstract

The invention discloses a method for establishing a severe spinal cord injury prognosis prediction model, and the method is characterized by comprising the following steps: extracting clinical data of cases of patients diagnosed as spinal cord injury: 1) incorporating the following clinical characteristics; 2) preprocessing the clinical features: processing missing data through different filling methods according to the types of the clinical features; 3) incorporating an algorithm combination of a feature selection method and a machine learning classification algorithm, wherein the feature selection method is used for screening clinical features with significant prediction values, and the selected clinical features are used for training the machine learning classification algorithm; 4) selecting the algorithm combination with the maximum area AUC under the micro average curve from the prediction performance of the algorithm combination in the step 3) in the training data set, and integrating the algorithm combination by using a stacking method to obtain a prediction model. The invention has accurate and objective performance for predicting the prognosis of the patient with severe spinal cord injury.

Description

technical field [0001] The invention relates to a method for establishing a prediction model for the prognosis of severe spinal cord injury. Background technique [0002] Patients with spinal cord injury are often admitted to the intensive care unit (ICU) due to major trauma or serious complications, so their prognosis is of great concern to clinicians and patients' families. However, how to accurately predict the prognosis of severe spinal cord injury is a clinical problem. Clinically, doctors often judge the prognosis of patients based on experience to formulate a diagnosis and treatment plan. However, it is often impossible to give an objective and quantifiable probability of prognosis when explaining the patient's condition to the patient's family. Therefore, an accurate and objective system for predicting the prognosis of patients with severe spinal cord injury is needed to assist clinicians, and how to establish a prediction model for this system for predicting the p...

Claims

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Application Information

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IPC IPC(8): G16H50/20G16H50/70
CPCG16H50/20G16H50/70Y02A90/10
Inventor 范国鑫刘华清戎利民庞卯刘斌张良明黄桂芳韩蓝青
Owner THE THIRD AFFILIATED HOSPITAL OF SUN YAT SEN UNIV
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