The Future of Artificial Intelligence in Clinical Radiology: Savior or False Hope?
作者信息
Zaharchuk Greg, Mei Janet
出版信息
AJNR Am J Neuroradiol. 2024 Dec 9;45(12):1838-1844. doi: 10.3174/ajnr.A8550.
Abstract
摘要
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本文引用的文献
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Deep Learning to Detect Intracranial Hemorrhage in a National Teleradiology Program and the Impact on Interpretation Time.深度学习在全国远程放射学计划中检测颅内出血及其对解释时间的影响。
Radiol Artif Intell. 2024 Sep;6(5):e240067. doi: 10.1148/ryai.240067.
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Developing, Purchasing, Implementing and Monitoring AI Tools in Radiology: Practical Considerations. A Multi-Society Statement from the ACR, CAR, ESR, RANZCR and RSNA.在放射科中开发、购买、实施和监测人工智能工具：实用考虑因素。ACR、CAR、ESR、RANZCR 和 RSNA 的多学会声明。
Radiol Artif Intell. 2024 Jan;6(1):e230513. doi: 10.1148/ryai.230513.
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Effect of Provider Type on Overutilization of CT Angiograms of the Head and Neck for Patients Presenting to the Emergency Department with Nonfocal Neurologic Symptoms.就诊于急诊科且以非局灶性神经系统症状为主的患者，其头部和颈部 CT 血管造影过度使用与提供者类型的关系。
J Am Coll Radiol. 2024 Jun;21(6):890-895. doi: 10.1016/j.jacr.2023.08.042. Epub 2023 Sep 16.
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