Intelligent Imaging: Anatomy of Machine Learning and Deep Learning

G. Currie
{"title":"Intelligent Imaging: Anatomy of Machine Learning and Deep Learning","authors":"G. Currie","doi":"10.2967/jnmt.119.232470","DOIUrl":null,"url":null,"abstract":"The emergence of artificial intelligence (AI) in nuclear medicine and radiology has been accompanied by AI commentators and experts predicting that AI would make radiologists, in particular, extinct. More realistic perspectives suggest significant changes will occur in medical practice. There is no escaping the disruptive technology associated with AI, neural networks, and deep learning, the most significant perhaps since the early days of Roentgen, Becquerel, and Curie. AI is an omen, but it need not be foreshadowing a negative event; rather, it is heralding great opportunity. The key to sustainability lies not in resisting AI but in having a deep understanding and exploiting the capabilities of AI in nuclear medicine while mastering those capabilities unique to the human resources.","PeriodicalId":22799,"journal":{"name":"The Journal of Nuclear Medicine Technology","volume":"1 1","pages":"273 - 281"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"33","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Nuclear Medicine Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2967/jnmt.119.232470","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 33

Abstract

The emergence of artificial intelligence (AI) in nuclear medicine and radiology has been accompanied by AI commentators and experts predicting that AI would make radiologists, in particular, extinct. More realistic perspectives suggest significant changes will occur in medical practice. There is no escaping the disruptive technology associated with AI, neural networks, and deep learning, the most significant perhaps since the early days of Roentgen, Becquerel, and Curie. AI is an omen, but it need not be foreshadowing a negative event; rather, it is heralding great opportunity. The key to sustainability lies not in resisting AI but in having a deep understanding and exploiting the capabilities of AI in nuclear medicine while mastering those capabilities unique to the human resources.
智能成像:剖析机器学习和深度学习
随着人工智能(AI)在核医学和放射学领域的出现,人工智能评论员和专家们预测,人工智能将使放射科医生尤其是放射科医生灭绝。更现实的观点表明,医疗实践将发生重大变化。与人工智能、神经网络和深度学习相关的颠覆性技术是不可避免的,这可能是伦琴、贝克勒尔和居里夫人早期以来最重要的技术。人工智能是一种预兆,但它不一定预示着负面事件;相反,它预示着巨大的机遇。可持续发展的关键不在于抵制人工智能,而在于深刻理解和利用人工智能在核医学领域的能力,同时掌握人力资源特有的能力。
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:481959085
Book学术官方微信