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Training method of early warning model of primary liver cancer

A primary liver cancer, early warning technology, applied in the direction of character and pattern recognition, instruments, computer components, etc., can solve the problems of expensive, unsuitable for wide-scale universal screening, high false negatives, etc., to achieve cheap, Improved scope of application, easy-to-achieve effects

Active Publication Date: 2020-04-10
SHANGHAI INST OF TECH
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Problems solved by technology

[0005] Medical imaging and case examination are currently commonly used detection methods for liver cancer, but due to their high cost and high false negative characteristics, they are not suitable for large-scale universal screening

Method used

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  • Training method of early warning model of primary liver cancer
  • Training method of early warning model of primary liver cancer
  • Training method of early warning model of primary liver cancer

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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] like figure 1 As shown, the present invention provides a kind of training method of the early warning model of primary liver cancer, comprising:

[0055] Step a, performing data preprocessing on the obtained clinical test data;

[0056] Step b, performing data set division on the preprocessed data;

[0057] Step c, training a classification model for early warning of primary liver cancer according to the divided data sets;

[0058] Step d, evaluating and verifying the performance of the classification model.

[0059] Here, the screening and classification model of the present invention can use clinical test data, combined with actual clinical requirements, select the threshold through the performance index curve of the o...

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Abstract

The invention provides a training method of the early warning model of primary liver cancer. According to the training method, a primary liver cancer early screening model is established by utilizinga machine learning algorithm on the basis of clinical examination data. The method comprises the following steps that: (a) carrying out data preprocessing on the obtained clinical examination data; (b) carrying out data set division on a preprocessed data set; (c) training a model according to divided data sets; and (d) evaluating and verifying the performance of the classification model. According to the screening model, the clinical examination data are utilized; on the basis of actual clinical requirements, a threshold value is selected through the performance index curve of the optimizedmodel so as to perform test verification, so that primary liver cancer clinical early warning can be carried out; conditions are provided for the early successful diagnosis of liver cancer; and the life quality of a patient is improved.

Description

technical field [0001] The invention relates to a training method for an early warning model of primary liver cancer. Background technique [0002] In the early stage of primary liver cancer (PLC), there are no obvious clinical symptoms, and about 2 / 3 of the patients with liver cancer are already in the middle and late stages when they are first diagnosed, and the opportunity for treatment has been missed. Early detection, early diagnosis, and early treatment of liver cancer are considered to be the main way for patients to obtain long-term survival. [0003] In recent years, the continuous accumulation and development of medical data and artificial intelligence have provided powerful resources and means for early screening of PLC. Among them, the application of image-based artificial intelligence methods in the recognition and prediction of liver cancer is relatively common. Moreover, many domestic researchers use biomarkers to study liver cancer screening. [0004] For ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62
CPCG06V2201/031G06F18/24
Inventor 曹国刚李梦雪高春芳房萌曹聪王孜怡
Owner SHANGHAI INST OF TECH
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