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Prediction method for clinical prognosis of liver cancer patient based on machine learning

A technology of machine learning and prediction methods, applied in machine learning, instrumentation, informatics, etc.

Inactive Publication Date: 2021-07-23
BEIJING IMMUPEUTICS MEDICINE TECH LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, there is no general consensus on the best prognostic model, so new methods are needed to predict the clinical prognosis and recurrence of HCC patients

Method used

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  • Prediction method for clinical prognosis of liver cancer patient based on machine learning
  • Prediction method for clinical prognosis of liver cancer patient based on machine learning
  • Prediction method for clinical prognosis of liver cancer patient based on machine learning

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Embodiment Construction

[0024] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with specific embodiments of the present invention and corresponding drawings. Apparently, the described embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0025] The technical solutions provided by various embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0026] According to an embodiment of the present invention, a method for predicting the clinical prognosis of liver cancer patients based on machine learning is provided. First, a certain number ...

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Abstract

The invention discloses a prediction method for clinical prognosis of a liver cancer patient based on machine learning. The method comprises the following steps: collecting corresponding sample data of hepatocellular carcinoma according to predetermined prediction characteristics; sorting the prediction features according to the sample data, and selecting part of the prediction features according to a sorting result; determining candidate prediction features related to the total survival rate from the selected prediction features by using a proportional risk regression model; and using a gradient enhanced survival classifier to select 20 optimal prediction features from the candidate prediction features as survival prediction factors to construct a liver cancer patient prognosis survival model. According to the invention, the HCC-related high-death-risk patients can be effectively identified.

Description

technical field [0001] The invention relates to liver cancer survival analysis technology, in particular to a method for predicting clinical prognosis of liver cancer patients based on machine learning. Background technique [0002] Liver cancer accounts for 8.2% of all cancer deaths worldwide. Major risk factors for hepatocellular carcinoma (HCC) include hepatitis B virus (HBV) or hepatitis C virus (HCV) infection and alcoholic or nonalcoholic liver disease. The clinical efficacy of patients with HCC largely depends on tumor burden, treatment modality, and liver function. A number of staging systems and predictive / prognostic models have been developed to assess liver functional reserve. [0003] To date, several staging systems have been used to predict the clinical efficacy of different approaches in HCC patients. In addition, liver function parameters, including Child-Pugh grading system, albumin and bilirubin levels, international normalized ratio (INR) and alkaline p...

Claims

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Application Information

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IPC IPC(8): G16H50/30G16H50/70G06N20/00
CPCG16H50/30G16H50/70G06N20/00
Inventor 张恒辉王修芳任树成宋瑾
Owner BEIJING IMMUPEUTICS MEDICINE TECH LTD
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