Method for establishing bleeding risk predicting model of acute coronary syndrome after interventional therapy

A technology for coronary syndrome and interventional therapy, applied in computational models, medical simulations, computer-aided medical procedures, etc., can solve problems such as overestimation of bleeding, and achieve the effect of facilitating observation and reducing the incidence of bleeding

Pending Publication Date: 2019-10-22
上海派兰数据科技有限公司
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AI Technical Summary

Benefits of technology

This technology helps gather important data about people at hospitals that have had heart attacks or strokes while undergoing cardiovascular procedures such as angioplasty surgery. By doing this analysis it can help healthcare providers make informed recommendations based upon these factors, potentially improving their chances of survival without unnecessary treatments.

Problems solved by technology

This patented describes two different ways to treat acute symptoms associated with blockages in blood vessels called stenosis/stenosis. One way involves surgery while another approach uses drugs like calcium channel blocking agents such as clodronate sodium or warfarine also known as platelets. Both techniques help prevent damage during medical procedures on vulnerable plaque deposits inside these tiny holes causing further complications.

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  • Method for establishing bleeding risk predicting model of acute coronary syndrome after interventional therapy

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Embodiment Construction

[0018] In order to further understand the content, features and effects of the present invention, the following examples are given, and detailed descriptions are given below with reference to the accompanying drawings.

[0019] Please refer to figure 1 , the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0020] refer to figure 1 As shown, the method for establishing a bleeding risk prediction model for acute coronary syndrome after interventional therapy includes the following steps:

[0021] S1. Collect data from the hospital electronic medical record system;

[0022] S2. Screen patients with acute coronary syndrome undergoing percutaneous coronary intervention, and extract required patient information;

[0023] S3. Apply machine learning methods to establish a prediction model for short-term and long-term bleeding risks of patients after surgery;

[0024] S4. Evaluate the prediction value of each mo...

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Abstract

The invention discloses a method for establishing a bleeding risk predicting model of an acute coronary syndrome after an interventional therapy, wherein the method belongs to the field of risk predicting. The method comprises the following steps of S1, collecting data from a hospital electronic medical record system; S2, screening the acute coronary syndrome patient of percutaneous coronary intervention, and extracting the required patient information; S3, applying a machine learning method for establishing patient postoperative short-and-long-term bleeding risk predicting models; and S4, evaluating the prediction value of each model, and selecting an optimal predicting model. Through retrospectively collecting the information of the acute coronary syndrome patient in the hospital electronic medical record system, collection is completely performed on the information of the acute coronary syndrome patient. Furthermore through multiple models in which machine learning is applied, the model which uses the patient information for predicting the bleeding risk is established, thereby realizing certain meaning in guiding clinical treatment decision and reducing bleeding incidence rate.

Description

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Claims

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Application Information

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Owner 上海派兰数据科技有限公司
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