人工智能对急性肺栓塞风险分层:临床需求的观点,扩展工具包和前进途径
Stanislav Henkin1, Damon Houghton1, Andetta Hunsaker2
1Gonda Vascular Center, Mayo Clinic, Rochester, Minnesota.
The American journal of cardiology
|May 28, 2025
概括
人工智能 (AI) 在诊断和分层肺栓塞 (PE) 风险方面表现有前途,但它对患者结果和临床工作流程的影响需要进一步调查. 当前的人工智能工具在PE识别方面没有超过放射科医生的准确性.
科学领域:
- 心脏病学 心脏病学
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 肺栓塞 (PE) 管理创新并没有像预期的那样降低死亡率.
- 不同质的PE表现和当前的风险分层限制有助于低于最佳的结果.
- 人工智能 (AI) 正在心血管医学中出现,包括PE诊断和风险分层.
研究的目的:
- 批判性地审查基于人工智能的急性PE诊断和风险分层的战略.
- 讨论AI在推进PE护理中的潜在整合.
- 探索AI在改善短期和长期PE结果中的作用.
主要方法:
- 在PE诊断中对AI应用的文献评估.
- 在急性PE中对AI进行风险分层的审查.
- 分析AI对临床工作流程和患者结果的潜在影响.
主要成果:
- 人工智能可以利用心电图和临床因素帮助预测PE的存在,从而减少诊断时间.
- 人工智能可以帮助区分急性和慢性PE.
- 目前的AI系统在PE识别方面显示了与放射科医生相似的准确性.
结论:
- 人工智能为PE诊断和风险分层提供了潜在的好处.
- 需要进一步的研究来确定AI对临床工作流程和患者结果的影响.
- 人工智能整合可能会推动PE管理领域的发展,以改善患者的治疗结果.
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