Breast cancer chemotherapy regimen recommendation method based on weighted KNN

A recommendation method, breast cancer technology, applied in medical automated diagnosis, medical data mining, computer-aided medical procedures, etc., can solve the problems of no computer participation, low efficiency of medical resources, etc., and achieve the effect of improving the overall effect and efficiency

Inactive Publication Date: 2016-09-28
SHANGHAI JIAO TONG UNIV +1
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AI Technical Summary

Problems solved by technology

[0002] Early diagnosis and adjuvant treatment of breast cancer can significantly reduce the mortality rate of patients. However, at present, the formulation of adjuvant treatm

Method used

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  • Breast cancer chemotherapy regimen recommendation method based on weighted KNN
  • Breast cancer chemotherapy regimen recommendation method based on weighted KNN
  • Breast cancer chemotherapy regimen recommendation method based on weighted KNN

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Embodiment Construction

[0020] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0021] like figure 1 As shown, a kind of weighted KNN-based chemotherapy regimen recommendation method for breast cancer provided by the present invention comprises the following steps:

[0022] Step 1, input a new case p through an external device a =1 , a 2 ,...,a n >;

[0023] Step 2, calculate the new case p a =1 , a 2 ,...,a n > with the i-th case in the original case pool The sum of the distances between attributes with the same serial number Where δ(c) represents a binary function, whe...

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Abstract

The invention provides a breast cancer chemotherapy regimen recommendation method based on weighted KNN. The method comprises the following steps that new cases Pa=<a1,a2,...,an> are input; distances between the new cases Pa=<a1,a2,...,an> and all cases Pi=<x1, x2<2>,...,xn,y> in an original case cool are calculated; first k cases are selected from the original case pool according to the distances from small to large; a recommended therapeutic regimen is obtained through calculation. The breast cancer chemotherapy regimen recommendation method based on the weighted KNN has the following advantages that an intelligent recommendation algorithm is introduced in the decision-making process of a breast cancer auxiliary therapeutic regimen, and the efficiency of the whole course of discussion is improved; when the distance between two cases is calculated, the linear correlation is used in combination to serve as a weight of each attribute; in the process of selecting a final recommended regimen from the most similar results, the influences of the distances are considered, and therefore the recommended whole effect is improved.

Description

technical field [0001] The invention relates to a weighted KNN-based breast cancer chemotherapy scheme recommendation method. Background technique [0002] Early diagnosis and adjuvant treatment of breast cancer can significantly reduce the mortality rate of patients. However, at present, the formulation of adjuvant treatment plan after breast cancer surgery does not involve computers. Finally, the treatment plan is decided, and the whole process uses more medical resources and is not efficient. Contents of the invention [0003] Aiming at the deficiencies in the prior art, the purpose of the present invention is to provide a weighted KNN-based breast cancer chemotherapy scheme recommendation method based on dynamic programming that improves the deficiencies of the existing recommendation algorithms. [0004] In order to solve the above-mentioned technical problems, a kind of breast cancer chemotherapy scheme recommendation method based on weighted KNN provided by the pre...

Claims

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Application Information

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IPC IPC(8): G06F19/00
CPCG16H50/20G16H50/70
Inventor 曹健张棪沈坤炜陈小松朱思吉
Owner SHANGHAI JIAO TONG UNIV
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