Monsour Robert, Dutta Mudit, Mohamed Ahmed-Zayn, Borkowski Andrew, Viswanadhan Narayan A
University of South Florida Morsani College of Medicine, Tampa, Florida.
James A. Haley Veterans' Hospital, Tampa, Florida.
Fed Pract. 2022 Apr;39(Suppl 1):S14-S20. doi: 10.12788/fp.0231. Epub 2022 Apr 12.
Artificial intelligence (AI) in medicine has shown significant promise, particularly in neuroimaging. AI increases efficiency and reduces errors, making it a valuable resource for physicians. With the increasing amount of data processing and image interpretation required, the ability to use AI to augment and aid the radiologist could improve the quality of patient care.
AI can predict patient wait times, which may allow more efficient patient scheduling. Additionally, AI can save time for repeat magnetic resonance neuroimaging and reduce the time spent during imaging. AI has the ability to read computed tomography, magnetic resonance imaging, and positron emission tomography with reduced or without contrast without significant loss in sensitivity for detecting lesions. Neuroimaging does raise important ethical considerations and is subject to bias. It is vital that users understand the practical and ethical considerations of the technology.
The demonstrated applications of AI in neuroimaging are numerous and varied, and it is reasonable to assume that its implementation will increase as the technology matures. AI's use for detecting neurologic conditions holds promise in combatting ever increasing imaging volumes and providing timely diagnoses.
医学人工智能（AI）已展现出巨大潜力，尤其是在神经影像学领域。人工智能提高了效率并减少了错误，使其成为医生的宝贵资源。随着所需数据处理和图像解读量的增加，利用人工智能增强和辅助放射科医生的能力可能会提高患者护理质量。
人工智能可以预测患者等待时间，这可能有助于更高效地安排患者就诊。此外，人工智能可以节省重复进行磁共振神经成像的时间，并减少成像过程中花费的时间。人工智能能够读取计算机断层扫描、磁共振成像和正电子发射断层扫描图像，在使用或不使用造影剂的情况下，检测病变的敏感性不会显著降低。神经影像学确实引发了重要的伦理考量，且存在偏差。用户了解该技术的实际和伦理考量至关重要。
人工智能在神经影像学中的已证明应用众多且多样，并且可以合理地假设，随着技术的成熟，其应用将会增加。人工智能用于检测神经系统疾病有望应对不断增加的成像量并提供及时诊断。
