Breast cancer prediction using machine learning models

Zhiqi Li, Shirui Tian, Tain Ya, Zhenning Yang
{"title":"Breast cancer prediction using machine learning models","authors":"Zhiqi Li, Shirui Tian, Tain Ya, Zhenning Yang","doi":"10.1117/12.2672652","DOIUrl":null,"url":null,"abstract":"This paper is to predict the presence of recurrence for breast cancer patients by citing data. As a first step we will collect relevant data on breast cancer patients from the internet. Next, we will use decision trees in Scikit-learn to determine if there will be a recurrence of breast cancer in patients who have been cured. Through a series of calculations and predictions, the accuracy of our experimental model finally reaches 0.75 accuracy. These data can help us to accomplish our target prediction well.","PeriodicalId":290902,"journal":{"name":"International Conference on Mechatronics Engineering and Artificial Intelligence","volume":"331 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Mechatronics Engineering and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2672652","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

This paper is to predict the presence of recurrence for breast cancer patients by citing data. As a first step we will collect relevant data on breast cancer patients from the internet. Next, we will use decision trees in Scikit-learn to determine if there will be a recurrence of breast cancer in patients who have been cured. Through a series of calculations and predictions, the accuracy of our experimental model finally reaches 0.75 accuracy. These data can help us to accomplish our target prediction well.
使用机器学习模型预测乳腺癌
本文旨在通过引用数据预测乳腺癌患者是否存在复发。作为第一步,我们将从互联网上收集乳腺癌患者的相关数据。接下来,我们将使用Scikit-learn中的决策树来确定已经治愈的乳腺癌患者是否会复发。通过一系列的计算和预测,我们的实验模型的精度最终达到0.75的精度。这些数据可以帮助我们很好地完成目标预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信