Method for auxiliary diagnosis of liver cancer by means of combined detection of tumor markers based on artificial neural network

An artificial neural network and joint detection technology is applied in the field of auxiliary diagnosis of liver cancer based on the joint detection of tumor markers based on artificial neural network. Effects of misdiagnosis, positive rate increase, accuracy rate and positive rate increase

Inactive Publication Date: 2017-08-08
中国人民解放军第一五九医院
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Problems solved by technology

[0004] 1) The serological indicator that is widely used in clinical practice is alpha-fetoprotein. It is generally believed that when its content is greater than 400 μg/L, it may indicate the existence of liver cancer, and the possibility of liver cancer should be highly suspected, but its diagnostic sensitivity and specificity are limited.
[0005] 2), detection techniques such as ultrasound, computerized X-ray tomography, magnetic resonance imaging, digital subtrac...

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  • Method for auxiliary diagnosis of liver cancer by means of combined detection of tumor markers based on artificial neural network
  • Method for auxiliary diagnosis of liver cancer by means of combined detection of tumor markers based on artificial neural network
  • Method for auxiliary diagnosis of liver cancer by means of combined detection of tumor markers based on artificial neural network

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Embodiment Construction

[0027] Such as figure 1 As shown, the present invention describes a method for auxiliary diagnosis of liver cancer based on the joint detection of artificial neural network tumor markers, comprising the following steps:

[0028] 1. Collect blood samples from patients;

[0029] Specimens were collected in 3 groups (liver cancer group, benign liver disease group and normal control group). Serum samples were collected from the 159 Central Hospital of the Chinese People's Liberation Army and the First Affiliated Hospital of Zhengzhou University from outpatients, inpatients and physical examiners. All liver cancer patients and patients with benign diseases were diagnosed by pathology, and normal people were checked by the physical examination department.

[0030] (1) Serum samples from 50 patients with liver cancer, including 41 males and 9 females, aged 25 to 83 years, with an average age of (55.72±12.69) years. There were 42 cases of primary liver cancer and 8 cases of secondar...

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Abstract

The invention discloses a method for auxiliary diagnosis of liver cancer by means of combined detection of tumor markers based on an artificial neural network. The method comprises the following steps: collecting a blood sample of a patient; adopting a chemiluminesent immunoassay kit to respectively measure the contents of alpha fetoprotein (AFP), carcino-embryonic antigen (CEA) and carbohydrate antigen 125 (CA125) in serum; measuring the level of sialic acid (SA) in the serum by applying a visible spectrophotometry; measuring the level of Ca in the serum by using an azo arsenic III end-point method; carrying out descriptive statistical analysis on all data by using statistics, and taking diagnostic sensitivity, specificity, accuracy, a positive predictive value and a negative predictive value as evaluation indexes; adopting a back-propagation neural network algorithm to obtain a trained model; using the trained model to predict a corresponding test set. The method provided by the invention is high in accuracy rate and can be used for well distinguishing the liver cancer, benign and normal, thus having good popularization and application prospects.

Description

technical field [0001] The invention belongs to the technical field of liver cancer detection, and in particular relates to a method for auxiliary diagnosis of liver cancer based on artificial neural network combined detection of tumor markers. Background technique [0002] Primary liver cancer is one of the most common malignant tumors in my country, with high morbidity and mortality, and most of them are primary hepatocellular carcinoma. The main reason is that there are many hepatitis B patients in my country, and most primary liver cancers develop on the basis of chronic hepatitis such as hepatitis B or C. At present, people's consensus on primary liver cancer is early detection, early diagnosis and early treatment. [0003] At present, there are mainly the following detection methods: [0004] 1) The serological indicator that is widely used in clinical practice is alpha-fetoprotein. It is generally believed that when its content is greater than 400 μg / L, it may indic...

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Application Information

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IPC IPC(8): G01N33/574G01N21/31G01N21/78G06N3/08
CPCG01N33/57438G01N21/31G01N21/78G01N33/574G01N33/57473G01N2800/085G06N3/084
Inventor 白雪峰程荣花胡青霍坚管潇潇王海伟曾芳杨晓莎雷刚
Owner 中国人民解放军第一五九医院
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