医疗成像和放射学云技术的经济和环境成本 人工智能 人工智能
Florence X Doo1, Pranav Kulkarni2, Eliot L Siegel3
1University of Maryland Medical Intelligent Imaging (UM2ii) Center, Department of Radiology and Nuclear Medicine, University of Maryland, Baltimore, Maryland.
Journal of the American College of Radiology : JACR
|December 10, 2023
概括
人工智能正在改变放射学,需要云计算解决方案来实现先进的计算. 云采用为放射信息学提供了成本节约和环境效益,尽管存在整合挑战.
科学领域:
- 医学成像和信息学 医学成像和信息学
- 医疗保健中的人工智能
- 云计算应用程序 云计算应用程序
背景情况:
- 放射学面临着由人工智能 (AI) 推动的技术革命,包括大型语言模型.
- 目前的非云计算信息系统往往缺乏人工智能所需的强大的计算和存储.
- 向云技术的过渡为放射学带来了机遇和挑战.
研究的目的:
- 探索云计算的潜力,以解决放射学不断变化的技术需求.
- 分析在放射学中采用云的经济和环境影响.
- 在云集成过程中,为放射信息学领导者确定关键考虑因素.
主要方法:
- 对人工智能和放射信息学当前趋势的审查.
- 分析云基础设施与本地解决方案的经济效益.
- 评估云数据中心对环境的影响.
- 识别医疗保健中云迁移的挑战和最佳实践.
主要成果:
- 云技术通过降低硬件所有权和维护费用,提供了具有成本效益的战略.
- 云数据中心的优化能源消耗可以减少放射学的环境足迹.
- 主要挑战包括架构选择,定价,数据安全,服务协议,培训和互操作性.
结论:
- 云计算是放射信息学未来的可行和潜在的有益解决方案.
- 战略规划对于应对云集成的复杂性至关重要,确保安全性和互操作性.
- 采用云解决方案对于放射学来说至关重要,以利用数据驱动工具并推进AI集成.
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