人工智能和机器学习在心脏骤停预测和管理中的应用:综合性审查
Sarah Aqel1, Sebawe Syaj2, Ayah Al-Bzour2
1Medical Research Center, Hamad Medical Corporation, Doha, Qatar. Saqel1@hamad.qa.
Current cardiology reports
|October 4, 2023
概括
人工智能 (AI) 和机器学习 (ML) 正在推动心肺复苏 (CPR) 的成功预测. 这些技术有望改善心脏骤停和医院前紧急护理的结果.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
- 计算生物学 计算生物学
背景情况:
- 突然心脏骤停 (SCA) 仍然是全球主要的死亡原因,存活率低.
- 目前的医院前急救护理系统在预测和预防SCA方面面临着挑战.
- 人工智能和机器学习在医疗保健中的整合正在各个领域迅速扩大.
研究的目的:
- 审查人工智能和机器学习的最新进展,以预测心肺复苏 (CPR) 的成功.
- 了解AI和ML在医学诊断,统计和精准医学中的作用.
- 探索AI和ML在管理突然心脏骤停 (SCA) 结果中的应用,特别是在医院前的环境中.
主要方法:
- 对人工智能和机器学习预测模型对心肺复苏成功的最新进展的文献综述.
- 分析AI和ML在医疗保健中的应用,包括医学诊断和精准医学.
- 探索ML算法来预测医院外心脏骤停 (OHCA) 的结果,并与自动化外部除器 (AED) 进行集成.
主要成果:
- 人工智能和机器学习越来越多地用于放射学和人口健康,用于疾病风险预测.
- ML算法在预测COVID-19患者的结果和识别OHCA方面显示出潜力.
- 人工智能与AED相结合可能会改善心脏骤停期间检测可震动节律的功能.
结论:
- 人工智能和机器学习对彻底改变SCA预测和管理具有重大前景.
- 这些技术可以提高生存率和更有效的医疗干预措施.
- 在临床电生理学中采用AI和ML工具为应对SCA挑战提供了乐观的希望.
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