前列腺癌治疗方式与合并症的相关性分析

Yi-Ting Lin, Mingchih Chen, Yen-Chun Huang
{"title":"前列腺癌治疗方式与合并症的相关性分析","authors":"Yi-Ting Lin, Mingchih Chen, Yen-Chun Huang","doi":"10.1145/3340037.3340070","DOIUrl":null,"url":null,"abstract":"Prostate cancer is a common cancer treated with multi-modality. The combinations of modalities are numerous and complex. Clinical practice guidelines and rules have already been proven in many studies. However, the hypotheses of these studies came from physicians' and experts' experiences and observation. Association analysis, as an importance component of data mining, has been proved to be helpful for us to discover rules from big medical databases. We believe association analysis is able to help us to discover new rules between comorbidities and modalities in subjects of prostate cancer, so that employed it to analyze prostate cancer dataset derived from million people file of NHIRD. We successfully found six rules and rule 1,2,3,5,6 could be well explained with known knowledge and literatures, which were \"Young prostate cancer patient who were spared from definite treatment tend to be spared from HT.\", \"TRUS is associated with younger age group, while TURP is associated with older Age.\", \"RT is associated with HT.\", \"CT is highly associated with RT.\", \"Hemiplegia, cerebrovascular disease, moderate to severe renal disease, diabetes with end organ damage is associated with TURP. Patients with TURP are associated with more comorbidity.\" We also discovered rule 4: \"Younger patients who received HT is highly associated with previous RP.\", which are still hypothesis and deserve our validation.","PeriodicalId":340774,"journal":{"name":"Proceedings of the 3rd International Conference on Medical and Health Informatics","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Association Analysis Among Treatment Modalities and Comorbidity for Prostate Cancer\",\"authors\":\"Yi-Ting Lin, Mingchih Chen, Yen-Chun Huang\",\"doi\":\"10.1145/3340037.3340070\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Prostate cancer is a common cancer treated with multi-modality. The combinations of modalities are numerous and complex. Clinical practice guidelines and rules have already been proven in many studies. However, the hypotheses of these studies came from physicians' and experts' experiences and observation. Association analysis, as an importance component of data mining, has been proved to be helpful for us to discover rules from big medical databases. We believe association analysis is able to help us to discover new rules between comorbidities and modalities in subjects of prostate cancer, so that employed it to analyze prostate cancer dataset derived from million people file of NHIRD. We successfully found six rules and rule 1,2,3,5,6 could be well explained with known knowledge and literatures, which were \\\"Young prostate cancer patient who were spared from definite treatment tend to be spared from HT.\\\", \\\"TRUS is associated with younger age group, while TURP is associated with older Age.\\\", \\\"RT is associated with HT.\\\", \\\"CT is highly associated with RT.\\\", \\\"Hemiplegia, cerebrovascular disease, moderate to severe renal disease, diabetes with end organ damage is associated with TURP. Patients with TURP are associated with more comorbidity.\\\" We also discovered rule 4: \\\"Younger patients who received HT is highly associated with previous RP.\\\", which are still hypothesis and deserve our validation.\",\"PeriodicalId\":340774,\"journal\":{\"name\":\"Proceedings of the 3rd International Conference on Medical and Health Informatics\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 3rd International Conference on Medical and Health Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3340037.3340070\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 3rd International Conference on Medical and Health Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3340037.3340070","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

前列腺癌是一种多模式治疗的常见癌症。模式的组合是众多和复杂的。临床实践指南和规则已经在许多研究中得到证实。然而,这些研究的假设来自于医生和专家的经验和观察。关联分析作为数据挖掘的一个重要组成部分,已被证明有助于我们从大型医学数据库中发现规则。我们认为关联分析能够帮助我们发现前列腺癌患者合并症和方式之间的新规律,因此我们将其用于分析来自NHIRD百万人档案的前列腺癌数据。我们成功发现了6条规则,其中规则1、2、3、5、6可以用已知的知识和文献很好地解释规则1、2、3、5、6,即“年轻的前列腺癌患者没有接受明确的治疗往往会避免HT”、“TRUS与年龄较小相关,而TURP与年龄较大相关”、“RT与HT相关”、“CT与RT高度相关”、“偏瘫、脑血管疾病、中重度肾脏疾病、糖尿病伴终末器官损伤与TURP相关。TURP患者有更多的合并症。”我们还发现了规则4:“接受过HT的年轻患者与既往RP高度相关”,这仍然是假设,值得我们验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Association Analysis Among Treatment Modalities and Comorbidity for Prostate Cancer
Prostate cancer is a common cancer treated with multi-modality. The combinations of modalities are numerous and complex. Clinical practice guidelines and rules have already been proven in many studies. However, the hypotheses of these studies came from physicians' and experts' experiences and observation. Association analysis, as an importance component of data mining, has been proved to be helpful for us to discover rules from big medical databases. We believe association analysis is able to help us to discover new rules between comorbidities and modalities in subjects of prostate cancer, so that employed it to analyze prostate cancer dataset derived from million people file of NHIRD. We successfully found six rules and rule 1,2,3,5,6 could be well explained with known knowledge and literatures, which were "Young prostate cancer patient who were spared from definite treatment tend to be spared from HT.", "TRUS is associated with younger age group, while TURP is associated with older Age.", "RT is associated with HT.", "CT is highly associated with RT.", "Hemiplegia, cerebrovascular disease, moderate to severe renal disease, diabetes with end organ damage is associated with TURP. Patients with TURP are associated with more comorbidity." We also discovered rule 4: "Younger patients who received HT is highly associated with previous RP.", which are still hypothesis and deserve our validation.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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:481959085
Book学术官方微信