用于乳腺异常参数检测与评估的智能乳腺异常框架

A. P, Avinash Sharma, S. R. Kawale, S. P. Diwan, Dankan Gowda V
{"title":"用于乳腺异常参数检测与评估的智能乳腺异常框架","authors":"A. P, Avinash Sharma, S. R. Kawale, S. P. Diwan, Dankan Gowda V","doi":"10.1109/ICECAA55415.2022.9936206","DOIUrl":null,"url":null,"abstract":"Unlike the healthy cells in the breast tissue, cancerous breast cells are unwelcome and have strange properties. In both sexes, this will quickly expand and infiltrate adjacent tissue, leading to the formation of a tumour. Using the Intelligent-Breast Abnormality Detection (I-BAD) framework, many breast cancer parameters are evaluated in this article. It has already been shown that some indicators may be used for early detection of breast cancer. There is also discussion of the instruments and strategies that facilitate the monitoring of the selected breast health metrics. Classification methods that use machine learning to store and analyse data are also discussed. The suggested I-BAD framework’s process is then visually shown in clean drawings.","PeriodicalId":273850,"journal":{"name":"2022 International Conference on Edge Computing and Applications (ICECAA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Intelligent Breast Abnormality Framework for Detection and Evaluation of Breast Abnormal Parameters\",\"authors\":\"A. P, Avinash Sharma, S. R. Kawale, S. P. Diwan, Dankan Gowda V\",\"doi\":\"10.1109/ICECAA55415.2022.9936206\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Unlike the healthy cells in the breast tissue, cancerous breast cells are unwelcome and have strange properties. In both sexes, this will quickly expand and infiltrate adjacent tissue, leading to the formation of a tumour. Using the Intelligent-Breast Abnormality Detection (I-BAD) framework, many breast cancer parameters are evaluated in this article. It has already been shown that some indicators may be used for early detection of breast cancer. There is also discussion of the instruments and strategies that facilitate the monitoring of the selected breast health metrics. Classification methods that use machine learning to store and analyse data are also discussed. The suggested I-BAD framework’s process is then visually shown in clean drawings.\",\"PeriodicalId\":273850,\"journal\":{\"name\":\"2022 International Conference on Edge Computing and Applications (ICECAA)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Edge Computing and Applications (ICECAA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICECAA55415.2022.9936206\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Edge Computing and Applications (ICECAA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECAA55415.2022.9936206","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 24

摘要

与乳腺组织中的健康细胞不同,乳腺癌细胞不受欢迎,并且具有奇怪的特性。在两性中,这将迅速扩大并浸润邻近组织,导致肿瘤的形成。利用智能乳房异常检测(I-BAD)框架,本文评估了许多乳腺癌参数。已经有研究表明,一些指标可以用于乳腺癌的早期检测。还讨论了促进监测选定的乳房健康指标的手段和战略。还讨论了使用机器学习来存储和分析数据的分类方法。然后,建议的I-BAD框架的过程以清晰的图纸直观地显示出来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Breast Abnormality Framework for Detection and Evaluation of Breast Abnormal Parameters
Unlike the healthy cells in the breast tissue, cancerous breast cells are unwelcome and have strange properties. In both sexes, this will quickly expand and infiltrate adjacent tissue, leading to the formation of a tumour. Using the Intelligent-Breast Abnormality Detection (I-BAD) framework, many breast cancer parameters are evaluated in this article. It has already been shown that some indicators may be used for early detection of breast cancer. There is also discussion of the instruments and strategies that facilitate the monitoring of the selected breast health metrics. Classification methods that use machine learning to store and analyse data are also discussed. The suggested I-BAD framework’s process is then visually shown in clean drawings.
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