人工智能技术在癌症检测中的应用

Darshan Patel, Yash Shah, Nisarg Thakkar, Kush Shah, Manan Shah
{"title":"人工智能技术在癌症检测中的应用","authors":"Darshan Patel,&nbsp;Yash Shah,&nbsp;Nisarg Thakkar,&nbsp;Kush Shah,&nbsp;Manan Shah","doi":"10.1007/s41133-019-0024-3","DOIUrl":null,"url":null,"abstract":"<div><p>Diseases like cancer have been termed as chronic fatal disease because of its deadly nature. The reason why cancer is termed as fatal is cancer progresses faster, and in most of the cases, these cells are detected at an advance stage. It is found that early detection of cancer is the key to lower death rate. In this study, overviews of applying AI technology for diagnosis of three types of cancer, breast, lung and liver, have been demonstrated. Various studies are reviewed for the different types of systems which are used for early detection of cancer. Automated or computer-aided systems with AI are considered as they provide a perfect fit to process a large dataset with accuracy and efficiency in detecting cancer. Diagnosis and treatment can be carried out with the help of these systems. Breast, lung and liver cancer studies have shown that some of these systems provide accurate precision in diagnosis and thus can solve the problem if these systems are implemented. However, these systems have to face a lot of hurdles to be implemented on a large scale. Image preprocessing, data management and other technology also need enhancement to be compatible with AI and machine learning algorithms to be implemented. Considering the experimental results, this study shows there is no doubt that the AI-implemented neural networks would be the future in cancer diagnosis and treatment.</p></div>","PeriodicalId":100147,"journal":{"name":"Augmented Human Research","volume":"5 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s41133-019-0024-3","citationCount":"51","resultStr":"{\"title\":\"Implementation of Artificial Intelligence Techniques for Cancer Detection\",\"authors\":\"Darshan Patel,&nbsp;Yash Shah,&nbsp;Nisarg Thakkar,&nbsp;Kush Shah,&nbsp;Manan Shah\",\"doi\":\"10.1007/s41133-019-0024-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Diseases like cancer have been termed as chronic fatal disease because of its deadly nature. The reason why cancer is termed as fatal is cancer progresses faster, and in most of the cases, these cells are detected at an advance stage. It is found that early detection of cancer is the key to lower death rate. In this study, overviews of applying AI technology for diagnosis of three types of cancer, breast, lung and liver, have been demonstrated. Various studies are reviewed for the different types of systems which are used for early detection of cancer. Automated or computer-aided systems with AI are considered as they provide a perfect fit to process a large dataset with accuracy and efficiency in detecting cancer. Diagnosis and treatment can be carried out with the help of these systems. Breast, lung and liver cancer studies have shown that some of these systems provide accurate precision in diagnosis and thus can solve the problem if these systems are implemented. However, these systems have to face a lot of hurdles to be implemented on a large scale. Image preprocessing, data management and other technology also need enhancement to be compatible with AI and machine learning algorithms to be implemented. Considering the experimental results, this study shows there is no doubt that the AI-implemented neural networks would be the future in cancer diagnosis and treatment.</p></div>\",\"PeriodicalId\":100147,\"journal\":{\"name\":\"Augmented Human Research\",\"volume\":\"5 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1007/s41133-019-0024-3\",\"citationCount\":\"51\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Augmented Human Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s41133-019-0024-3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Augmented Human Research","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s41133-019-0024-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 51

摘要

像癌症这样的疾病由于其致命性而被称为慢性致命疾病。癌症之所以被称为致命,是因为癌症进展更快,而且在大多数情况下,这些细胞是在晚期检测到的。发现早期发现癌症是降低死亡率的关键。本研究综述了人工智能技术在乳腺癌、肺癌和肝癌三种癌症诊断中的应用。综述了用于癌症早期检测的不同类型的系统的各种研究。具有人工智能的自动化或计算机辅助系统被认为是完美的,因为它们提供了处理大型数据集的精确性和效率,可以检测癌症。诊断和治疗可以在这些系统的帮助下进行。乳腺癌、肺癌和肝癌癌症研究表明,其中一些系统在诊断中提供了准确的精度,因此如果实施这些系统,可以解决问题。然而,这些系统要大规模实施,必须面临许多障碍。图像预处理、数据管理等技术也需要增强,才能与人工智能和机器学习算法兼容。考虑到实验结果,本研究表明,AI实现的神经网络无疑将是癌症诊断和治疗的未来。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Implementation of Artificial Intelligence Techniques for Cancer Detection

Diseases like cancer have been termed as chronic fatal disease because of its deadly nature. The reason why cancer is termed as fatal is cancer progresses faster, and in most of the cases, these cells are detected at an advance stage. It is found that early detection of cancer is the key to lower death rate. In this study, overviews of applying AI technology for diagnosis of three types of cancer, breast, lung and liver, have been demonstrated. Various studies are reviewed for the different types of systems which are used for early detection of cancer. Automated or computer-aided systems with AI are considered as they provide a perfect fit to process a large dataset with accuracy and efficiency in detecting cancer. Diagnosis and treatment can be carried out with the help of these systems. Breast, lung and liver cancer studies have shown that some of these systems provide accurate precision in diagnosis and thus can solve the problem if these systems are implemented. However, these systems have to face a lot of hurdles to be implemented on a large scale. Image preprocessing, data management and other technology also need enhancement to be compatible with AI and machine learning algorithms to be implemented. Considering the experimental results, this study shows there is no doubt that the AI-implemented neural networks would be the future in cancer diagnosis and treatment.

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
期刊最新文献
Haptic Gamer Suit for Enhancing VR Games Experience Retraction Note: Application on Virtual Reality for Enhanced Education Learning, Military Training and Sports The Impact of Transferring Embodiment and Work Efficiency Between Natural Body and Modular Body Systems Smart Life Saver Jacket: A New Jacket to Support CPR Operation Unraveling the Ethical Conundrum of Artificial Intelligence: A Synthesis of Literature and Case Studies
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1