在ARDS中肺部成像和人工智能
Davide Chiumello1,2,3, Silvia Coppola2, Giulia Catozzi1
1Department of Health Sciences, University of Milan, 20122 Milan, Italy.
Journal of clinical medicine
|January 23, 2024
概括
人工智能 (AI) 增强了使用肺成像的急性呼吸困扰综合征 (ARDS) 诊断. 人工智能有助于评估ARDS风险,气泡膜招募和患者结果,改善临床决策.
科学领域:
- 放射学 放射学是一门学科.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 急性呼吸窘迫综合征 (ARDS) 是一种严重的肺部疾病,需要准确的诊断和监测.
- 肺部成像,特别是计算机断层扫描 (CT) 和超声波,对于评估ARDS特征至关重要.
- 传统方法有局限性,需要先进的分析工具.
研究的目的:
- 审查人工智能 (AI) 在分析肺部CT和ARDS超声波方面的当前应用.
- 探索人工智能在预测ARDS风险,测量气泡膜招募和确定患者预后方面的作用.
- 总结AI在ARDS管理中提高诊断准确度和临床工作流程的潜力.
主要方法:
- 一个叙事审查十八个检索的研究,专注于AI在ARDS成像.
- 分析AI在计算机断层扫描 (CT) 和超声波中用于ARDS评估中的应用.
- 综合有关AI在风险评估,诊断和结果预测中的实用性的发现.
主要成果:
- 人工智能在评估ARDS风险,量化膜征集和确定替代诊断方面显示出潜力.
- 人工智能辅助肺部成像可以改善对ARDS患者机械和形态特征的评估.
- 人工智能工具在预测患者的结果和增强诊断能力方面表现有前途.
结论:
- 人工智能具有显著的潜力,可以增强ARDS诊断和管理中的临床决策.
- 人工智能可以提高ARDS肺部成像分析的准确性和效率.
- 医生监督仍然至关重要,人工智能作为临床团队的支持工具.
关键词:
在 ARDS 中,ARDS 是指 ARDS 的类型.在 COVID-19 疫情中,这就是为什么CTCTCTCTCT这就是LUS LUS.人工智能的人工智能是人工智能.深度学习是一种深度学习.肺部成像 肺部成像机器学习是机器学习.更多相关视频
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