Gastric cancer disease risk detection device based on big data analysis technology
A technology of disease risk and analysis technology, applied in the field of gastric cancer disease risk detection devices, can solve the problems of no device for directly detecting the risk of gastric cancer, inability to effectively detect the risk of gastric cancer, and low detection rate of early diagnosis of gastric cancer, etc. The effect of improving efficiency, improving accuracy, and improving detection speed
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Embodiment 1
[0042] see figure 1 A gastric cancer disease risk detection device based on big data analysis technology mainly includes a data acquisition module, a database, a data preprocessing module, a feature extraction module, a risk assessment module and a computer readable medium.
[0043] The data collection module obtains the basic data of the tester and stores it in the disease risk data set of the database.
[0044] The data acquisition module is interconnected with the hospital information device and / or the tester's terminal through the communication network, so as to obtain the basic data of the tester.
[0045] The basic data of the tester mainly include height, age, weight, gender, daily diet, living environment, lifestyle, living habits, psychological emotions, past medical history, family history of malignant tumors and the risk assessment level of the tester for cancer prevention data. Numerically mark psychological emotions such as irritability, happiness, and sadness. ...
Embodiment 2
[0079] A gastric cancer disease risk detection device based on big data analysis technology, mainly including a data collection module, a database, a data preprocessing module, a feature extraction module and a risk assessment module.
[0080] The data collection module obtains the basic data of the tester and stores it in the disease risk data set of the database.
[0081] The database stores a data preprocessing module, a feature extraction module and a risk assessment module.
[0082] The data preprocessing module preprocesses the disease risk data set to obtain the preprocessed disease risk data sample unit x 1 ,...,x n , and sent to the feature extraction module.
[0083] The feature extraction module uses the nearest neighbor component analysis method to extract the disease risk data unit x 1 ,...,x n features, so as to establish a gastric cancer risk feature data set T={(x 1 ,y 1 ),...,(x n ,y n )}, and sent to the risk assessment module.
[0084] The risk asse...
Embodiment 3
[0086] A gastric cancer disease risk detection device based on big data analysis technology, the main structure is the same as that shown in Embodiment 2, wherein the data acquisition module is interconnected with the hospital information device and / or the tester terminal through the communication network, so as to obtain the basic information of the tester. data.
[0087] The basic data of the tester mainly include height, age, weight, gender, daily diet, living environment, past medical history, family history of malignant tumors, and the tester's cancer risk assessment level data.
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