人工智能
任务(项目管理)
医学
计算机科学
机器学习
医学物理学
系统工程
工程类
作者
Abhinav K. Jha,Kyle J. Myers,Nancy A. Obuchowski,Ziping Liu,Md Ashequr Rahman,Babak Saboury,Arman Rahmim,Barry A. Siegel
出处
期刊:Pet Clinics
[Elsevier]
日期:2021-09-15
卷期号:16 (4): 493-511
被引量:31
标识
DOI:10.1016/j.cpet.2021.06.013
摘要
Artificial intelligence-based methods are showing promise in medical imaging applications. There is substantial interest in clinical translation of these methods, requiring that they be evaluated rigorously. We lay out a framework for objective task-based evaluation of artificial intelligence methods. We provide a list of available tools to conduct this evaluation. We outline the important role of physicians in conducting these evaluation studies. The examples in this article are proposed in the context of PET scans with a focus on evaluating neural network-based methods. However, the framework is also applicable to evaluate other medical imaging modalities and other types of artificial intelligence methods.
科研通智能强力驱动
Strongly Powered by AbleSci AI