新兴的人工智能辅助诊断和治疗缺血性中风和血管封闭的管理方法:全面的审查
G A U R I Parvathy1, B A L A K R I S H N A N Kamaraj2, B I K I K U M A R Sah3
1TBILISI STATE MEDICAL UNIVERSITY, GEORGIA.
World neurosurgery: X
|March 21, 2024
概括
人工智能 (AI) 在使用机器学习 (ML) 诊断大血管封闭 (LVO) 卒中方面显示出强大的潜力. 虽然对诊断有效,但人工智能是有效的.
科学领域:
- 神经学 神经学
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 大血管封闭性 (LVO) 卒中需要快速诊断和治疗以获得最佳结果.
- 人工智能 (AI),特别是机器学习 (ML),为改善LVO中风管理提供了潜力.
- 目前在LVO中风中的AI应用正在评估其有效性和未来的潜力.
研究的目的:
- 在LVO中风中全面审查AI的当前状态.
- 评估AI在诊断,患者选择和结果预测方面的有效性.
- 确定AI在LVO中风管理中的局限性和未来方向.
主要方法:
- 在PubMed,Embase和Scopus数据库中进行了广泛的文献搜索.
- 通过标题和摘要对研究进行选,不包括重复复制.
- 包含/排除标准应用于最终分析的全文论文.
主要成果:
- 在计算机断层扫描上,ML方法在识别LVO方面表现出很高的准确性.
- 人工智能用于血栓切除术患者选择的应用目前有限.
- ML算法可以合理地预测临床和血管学结果.
- 人工智能在急性中风诊断和治疗方面表现有前途.
结论:
- 人工智能,特别是ML,对LVO中风诊断和急性治疗具有前景.
- 目前在LVO中风管理和预测中的AI实用性受到限制.
- 需要进一步的研究来开发人工智能应用程序用于LVO中风的临床决策.
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