Brain Tumor Imaging: Applications of Artificial Intelligence.
Brain Tumor Imaging: Applications of Artificial Intelligence.
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DOI：
10.1053/j.sult.2022.02.005
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发表时间：
2022-04
期刊：
影响因子：
--
通讯作者：
Payabvash S
中科院分区：
文献类型：
--
作者：
Afridi M;Jain A;Aboian M;Payabvash S
人工智能已经成为一个热门的研究领域，目标是将其整合到临床决策过程中。越来越多的预测模型正在利用机器学习来使用，其中包括被称为放射性特征的计算机提取的定量成像特征，以及深度学习系统。这一点在脑肿瘤成像中尤其如此，人工智能已被提出用于表征、区分和预测。我们回顾了当前关于基于机器学习和基于深度学习的人工智能在神经肿瘤学中的潜在应用的文献，因为它与脑瘤分子分类、分化和治疗反应有关。虽然有很有希望的证据支持人工智能在神经肿瘤学中的使用，但在将其引入常规临床决策方案之前，仍需要在更大、多中心的规模上进行更多的研究，以及简化和标准化的图像处理工作流程。
Artificial intelligence has become a popular field of research with goals of integrating it into the clinical decision-making process. A growing number of predictive models are being employed utilizing machine learning that includes quantitative, computer-extracted imaging features known as radiomic features, and deep learning systems. This is especially true in brain-tumor imaging where artificial intelligence has been proposed to characterize, differentiate, and prognostication. We reviewed current literature regarding the potential uses of machine learning-based, and deep learning-based artificial intelligence in neuro-oncology as it pertains to brain tumor molecular classification, differentiation, and treatment response. While there is promising evidence supporting the use of artificial intelligence in neuro-oncology, there are still more investigations needed on a larger, multi-center scale along with a streamlined and standardized image processing workflow prior to its introduction in routine clinical decision-making protocol.
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