Intelligent Imaging: Anatomy of Machine Learning and Deep Learning
Intelligent Imaging: Anatomy of Machine Learning and Deep Learning
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DOI：
10.2967/jnmt.119.232470
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发表时间：
2019-12-01
影响因子：
1.3
通讯作者：
Currie, Geoff
中科院分区：
文献类型：
--
作者：
Currie, Geoff
随着人工智能（AI）在核医学和放射学领域的出现，AI评论员和专家预测，AI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无法逃避的，这可能是自伦琴、贝克勒尔和居里早期以来最重要的技术。人工智能是一个预兆，但它不一定预示着一个负面事件;相反，它预示着一个巨大的机会。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中的能力，同时掌握人力资源所特有的能力。
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.