Human body index-stroke relationship analysis system based on machine learning interpretability

A technology of machine learning and relational analysis, applied in the field of disease prediction, which can solve the problem that new samples are meaningless

Active Publication Date: 2022-03-25
NANJING UNIV
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Problems solved by technology

Therefore, new samples generated by these two methods are sometimes meaningless

Method used

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[0029] Below in conjunction with accompanying drawing and specific embodiment, further illustrate the present invention, should be understood that these examples are only for illustrating the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various aspects of the present invention All modifications of the valence form fall within the scope defined by the appended claims of the present application.

[0030] In this embodiment, a human body indicator-stroke relationship analysis method based on machine learning interpretability is provided, as shown in Figure 1, including the following steps:

[0031] S10 Data collection and preprocessing: Obtain the physical index data of people who have suffered from stroke and those who have not suffered from stroke from the hospital. deal with.

[0032] S20 uses the processed labeled data and a machine learning algorithm to t...

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Abstract

The invention discloses a human body index-stroke relationship analysis system based on machine learning interpretability, including a data input module, a data preprocessing module, a machine learning module, a correlation analysis module, an index neighbor search module, and a new sample manufacturing module , The new sample prediction statistics module, through the correlation analysis of the attributes, when an attribute changes, the attributes related to it will also change, so that the generated new samples are closer to the actual situation, so as to study the prevalence of stroke The relationship with the change of the body index, the present invention can obtain the influence of the change of the body index on whether to suffer from stroke, which plays an important role in further research on the prevention of diseases.

Description

technical field [0001] The invention relates to the technical field of data processing and machine learning interpretability, in particular to a model-independent machine learning interpretability method and a disease prediction method. Background technique [0002] With the application and penetration of machine learning algorithms in various fields, the accuracy of the algorithms has been rising, especially the application of deep learning algorithms has further improved the accuracy of machine learning algorithms. However, people cannot fully grasp the working principle of machine learning algorithms, and many algorithms with high enough accuracy are still an unexplainable "black box" for us. [0003] In the medical field, under the background of today's smart medical care, it is of great significance to use machine learning algorithms to predict diseases for "unaffected", which can effectively reduce medical costs. However, in the medical field, the harm of algorithm er...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16H50/20G16H10/60G06N20/00G06K9/62
CPCG16H50/20G16H10/60G06N20/00G06F18/24143G06F18/2415
Inventor 张雷于凌霜罗翀张晓雯沈俊东余成王崇骏
Owner NANJING UNIV
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