心声回声学中的人工智能:趋势,热点和未来方向
Qi Guo1, Jiafu Ma2, Hongzhe Zhang3
1Department of Special Services The 960th Hospital of the PLA Joint Logistics Support Force, Jinan, China.
International journal of surgery (London, England)
|November 17, 2025
概括
人工智能 (AI) 正在迅速推进心声回声学,提高诊断准确性和自动化工作流程. 研究重点是针对心力衰竭等疾病的AI驱动分析,深度学习显示出显著的潜力.
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:
- 人工智能 (AI) 正在改变心声回声学,提高诊断准确性和自动化工作流程.
- 在心声回声学中,操作者依赖的变异性是人工智能集成所应对的关键挑战.
- 目前对人工智能对心声回声学影响的系统分析有限.
研究的目的:
- 系统地分析图书统计趋势和AI在心声回声学中的研究格局.
- 识别人工智能心声学研究中的关键贡献者,机构和国家.
- 绘制该领域研究主题和关键词的演变图.
主要方法:
- 从科学网络数据库 (2019-2024) 中对1,296篇出版物的图书法分析.
- 使用R套图书表数据分析,包括年度趋势,作者/机构/国家贡献和关键词演变.
- 检查了出版物输出,引用趋势和随着时间的推移的主题转变.
主要成果:
- 出版物从45篇 (2019年) 迅速增长到302篇 (2024年),引用量在2019年达到峰值.
- 美国和中国在出版量方面处于领先地位;梅奥诊所和哈佛大学是领先的机构.
- 主要研究领域包括人工智能驱动的心脏参数量化,病理检测,诊断,分类和心力衰竭.
- 主题演变显示了从结构异常研究向深度学习应用的转变.
结论:
- 人工智能在心声回声学中的整合正在迅速推进,以加速的出版率为证.
- 研究热点包括自动图像分析,诊断分类,预后预测和工作流的优化.
- 深度学习模型在减少操作员依赖和提高诊断精度方面表现有前途.
- 未来的研究重点是数据标准化,完全自动化的诊断管道,以及提高人工智能系统的临床可靠性.
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