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Primary liver cancer staging model training method

A primary liver cancer, model training technology, applied in character and pattern recognition, instruments, computer parts and other directions, can solve the problems of unsatisfactory model performance and other problems, and achieve the effect of simple acquisition, low price and easy realization

Pending Publication Date: 2020-10-16
SHANGHAI INST OF TECH
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, although the screening method based on clinical test data is patient-friendly, easy to sample, cheap and easy to combine algorithms, the performance of existing models is not satisfactory

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  • Primary liver cancer staging model training method
  • Primary liver cancer staging model training method
  • Primary liver cancer staging model training method

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Embodiment Construction

[0053] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0054] Such as figure 1 As shown, the present invention provides a method for training a primary liver cancer staging model, comprising:

[0055] (a) Perform data preprocessing on the obtained clinical test data of patients with known stages of liver cancer to obtain preprocessed data;

[0056] (b) dividing the preprocessed data to obtain a training data set and a testing data set;

[0057] (c) mapping the training data set into a training set image, and mapping the testing data set into a test set image;

[0058] (d) primary liver cancer staging model based on the image training data of the training set;

[0059] (e) Evaluate and verify the performance of the primary liver cancer staging model based on the test set image data....

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Abstract

The invention provides a primary liver cancer staging model training method, which adopts clinical examination data of a liver cancer patient and utilizes a deep learning algorithm to establish a liver cancer patient staged network model, and comprises the following steps of: (a) performing data preprocessing on obtained clinical examination data; (b) dividing a preprocessed data set; (c) mappingthe processed data into an image; (d) training a network model according to the divided data set; and (e) evaluating and verifying the performance of a staging model. The staging model determines thestage of the primary liver cancer patient by using clinical examination data, so that a decisive opportunity is created for successfully curing liver cancer, and the purposes of enhancing the clinicalcurative effect of the patient and improving the survival rate of the patient are achieved.

Description

technical field [0001] The invention relates to a training method for a staging model of primary liver cancer. Background technique [0002] Primary liver cancer ranks fifth among common malignant tumors in the world, and ranks third in the death rate of tumor patients. At present, the most powerful and effective treatment is surgical resection or liver transplantation. Among them, surgical resection can make the 5-year survival rate of early liver cancer reach 60-70%. However, because the early symptoms of liver cancer are not obvious and the causes of the disease are complicated, about 2 / 3 of the patients with liver cancer are in the middle and late stages when they are first diagnosed, and they lose the opportunity for surgical treatment, making the overall 5-year survival rate still less than 40%. [0003] In recent years, the use of deep learning network models to identify liver cancer based on liver CT image data is particularly common. This is because CT images have ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/217G06F18/214
Inventor 曹国刚李梦雪朱信玉王一杰刘顺堃毛红东孔德卿
Owner SHANGHAI INST OF TECH