How does artificial intelligence in radiology improve efficiency and health outcomes?

被引：0
作者：
Kicky G. van Leeuwen
Maarten de Rooij
Steven Schalekamp
Bram van Ginneken
Matthieu J. C. M. Rutten
机构：
[1] Radboud University Medical Center,Department of Medical Imaging
[2] Jeroen Bosch Hospital,Department of Radiology
来源：
Pediatric Radiology | 2022年 / 52卷
关键词：
Artificial intelligence; Pediatrics; Evidence-based practice; Impact analysis; Innovation; Radiology; Value-based health care;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Since the introduction of artificial intelligence (AI) in radiology, the promise has been that it will improve health care and reduce costs. Has AI been able to fulfill that promise? We describe six clinical objectives that can be supported by AI: a more efficient workflow, shortened reading time, a reduction of dose and contrast agents, earlier detection of disease, improved diagnostic accuracy and more personalized diagnostics. We provide examples of use cases including the available scientific evidence for its impact based on a hierarchical model of efficacy. We conclude that the market is still maturing and little is known about the contribution of AI to clinical practice. More real-world monitoring of AI in clinical practice is expected to aid in determining the value of AI and making informed decisions on development, procurement and reimbursement.
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收藏
页码：2087 / 2093
页数：6
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