Thyroid disease prediction modeling method based on association decision tree

A technology of thyroid disease and modeling method, applied in the field of thyroid disease prediction modeling based on association decision tree, which can solve problems such as less research, avoid costs, reduce the risk of cancer recurrence, improve robustness and generalization effect of ability

Pending Publication Date: 2020-08-04
JILIN UNIV
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Problems solved by technology

However, there are few studies on the prognosis of LNM in PTMC patients, especially the prognosis of LN

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  • Thyroid disease prediction modeling method based on association decision tree
  • Thyroid disease prediction modeling method based on association decision tree
  • Thyroid disease prediction modeling method based on association decision tree

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[0041] The present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work shall fall within the protection scope of the present invention.

[0042] Such as figure 1 As shown, the present invention provides a thyroid disease prediction modeling method based on an association decision tree, including:

[0043] 1) Obtain the medical information of the training sample PTMC patient, the medical information includes the patient's attributes, symptoms, and diagnosis results, and map the symptoms to an independent variable u=(u 1 ; U 2 ;...;U d ), and the diagnosis result is mapped to the dependent variable y∈{0,1};

[0044] In the present invention, by mapping the LNM (lymph node metastas...

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Abstract

The invention discloses a thyroid disease prediction modeling method based on an association decision tree. An associated decision tree MsaDtd algorithm is provided, composite features are fully utilized, and an original feature space is converted into a larger disease diagnosis feature space to predict the LNM of a PTMC patient; and fuzzy logic is introduced to process continuous attributes, so that the cost of generating a large number of frequent items is avoided, and the robustness and generalization ability of the model are improved. According to the method, a clinician can use information provided by the prediction model, a specific treatment scheme is adopted in the whole treatment process, and the clinician should take targeted intervention measures to patients prone to LNM, so that help is provided for reducing the risk of cancer recurrence.

Description

technical field [0001] The invention relates to the technical field of computer modeling, in particular to a thyroid disease prediction modeling method based on an association decision tree. Background technique [0002] Artificial intelligence (AI) has recently made great progress in applications such as autonomous driving, big data, pattern recognition, intelligent search, image understanding, automatic programming, robotics, and man-machine games, which have also inspired AI to some extent. Technology development and innovation. In recent years, with the increasing abundance of medical data and the rapid development of big data analysis methods, artificial intelligence has gradually been successfully applied in the medical field. Artificial intelligence uses complex algorithms to learn complex patterns from a large amount of medical data. The learning and The self-error-correcting ability helps to reduce the inevitable diagnostic errors in human clinical practice. [00...

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Application Information

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IPC IPC(8): G16H50/50
CPCG16H50/50
Inventor 梁世宁左祥麟史振坤张一嘉左万利
Owner JILIN UNIV
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