Radiomics, machine learning, and, more generally, artificial intelligence (AI) provide unique tools to improve the performances of nuclear medicine in all aspects. They may help rationalise the operational organisation of imaging departments, optimise resource allocations, and improve image quality while decreasing radiation exposure and maintaining qualitative accuracy. There is already convincing data that show AI detection, and interpretation algorithms can perform with equal or higher diagnostic accuracy in various specific indications than experts in the field. Preliminary data strongly suggest that AI will be able to process imaging data and information well beyond what is visible to the human eye, and it will be able to integrate features to provide signatures that may further drive personalised medicine. As exciting as these prospects are, they currently remain essentially projects with a long way to go before full validation and routine clinical implementation. AI uses a language that is totally unfamiliar to nuclear medicine physicians, who have not been trained to manage the highly complex concepts that rely primarily on mathematics, computer sciences, and engineering. Nuclear medicine physicians are mostly familiar with biology, pharmacology, and physics, yet, considering the disruptive nature of AI in medicine, we need to start acquiring the knowledge that will keep us in the position of being actors and not merely witnesses of the wonders developed by other stakeholders in front of our incredulous eyes. This will allow us to remain a useful and valid interface between the image, the data, and the patients and free us to pursue other, one might say nobler tasks, such as treating, caring and communicating with our patients or conducting research and development.

中文翻译：

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以医师为中心的影像学解释正在消失-为什么我应该成为核医学医师？

放射学，机器学习以及更广泛的人工智能（AI）提供了独特的工具来改善核医学在各个方面的性能。它们可能有助于合理化成像部门的运营组织，优化资源分配并提高图像质量，同时减少辐射暴露并保持定性准确性。已经有令人信服的数据显示了AI检测，并且解释算法在各种特定适应症中的表现或等同或高于本领域的专家，都可以提供等同或更高的诊断精度。初步数据强烈表明，人工智能将能够处理超出人眼可见范围的成像数据和信息，并且它将能够集成功能以提供可能进一步推动个性化医学的签名。这些前景令人兴奋，目前，它们在充分验证和常规临床实施之前仍是一个很长的路要走的项目。AI使用的语言是核医学医师完全不熟悉的语言，他们没有受过训练来管理主要依赖于数学，计算机科学和工程学的高度复杂的概念。核医学医师大多熟悉生物学，药理学和物理学，但是，考虑到AI在医学中的破坏性，我们需要开始获取知识，这将使我们成为行动者，而不仅仅是见证奇迹的发展在我们不可思议的眼神面前被其他利益相关者。这将使我们能够在图像，数据和患者之间保持一种有用且有效的界面，并使我们有更多的精力去追求其他任务，也许有人会说这是一项艰巨的任务，