对人工智能对心脏病学心电图的影响进行系统审查
Oluwafemi Ayotunde Oke1, Nadire Cavus1
1Department of Computer Information Systems, Near East University, Nicosia 99138, Cyprus; Computer Information Systems Research and Technology Centre, Turkey.
International journal of medical informatics
|December 14, 2024
概括
人工智能 (AI),机器学习 (ML) 和深度学习 (DL) 显著改善了对心脏病的电心图 (ECG) 分析. 这些人工智能技术提高了诊断的准确性和速度,有助于早期检测和个性化治疗,以获得更好的患者结果.
科学领域:
- 心脏病学 心脏病学
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 正通过提高效率和洞察力产生来改变行业.
- 在心脏病学中,人工智能,机器学习 (ML) 和深度学习 (DL) 显示出改善心电图 (ECG) 分析的前景.
- 人工智能在心电图分析中的整合可以提高诊断准确度,减少诊断时间.
研究的目的:
- 系统地审查AI,ML和DL在ECG分析中的整合.
- 探索人工智能驱动的心电图分析对心脏病学预测诊断和治疗支持的影响.
主要方法:
- 系统的文献审查遵循PRISMA 2020框架.
- 搜索了四个高影响力数据库,搜索了2014年至2024年间发表的研究.
- 包括英语文章,重点关注心脏健康的心电图分析中的AI应用.
主要成果:
- 46项研究符合纳入标准,使用各种AI模型 (CNN,RNN,混合).
- 人工智能模型应用于心电图数据,以检测和预测心律不整,心肌梗塞和心力衰竭等疾病.
- 人工智能驱动的心电图分析显示了诊断准确度的提高以及对早期诊断和个性化治疗的大量支持.
结论:
- 人工智能技术,特别是ML和DL,正在推进基于心电图的心脏病诊断.
- 这些技术提高了准确性,减少了诊断时间,并支持及时干预和个性化患者护理.
- 进一步的研究对于完善算法和临床整合心脏病学中人工智能工具至关重要,以改善患者的治疗结果.
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