通过深度学习帮助初学者临床医生获得有限的回声心电图:一个随机对照试验
Andre Kumar1, Evan Baum1, Caitlin Parmer-Chow1
1Department of Medicine, Stanford University School of Medicine, 300 Pasteur Drive, Stanford, CA 95401, United States.
Biology methods & protocols
|November 21, 2025
概括
深度学习 (DL) 超声波设备显着加快了心声回声图的采集速度,并改善了临床医生没有先前超声波培训的图像质量. 这项技术提高了诊断成像能力,使非专家能够获得有用的心脏图像.
科学领域:
- 医疗成像医学成像
- 人工智能在医学中的应用
- 心脏病学 心脏病学
背景情况:
- 全球超声波仪短缺限制了及时的超声波诊断.
- 深度学习 (DL) 提供了改善非专业人士图像获取的潜力.
- 在资源有限的环境中,对关键诊断成像的访问有限.
研究的目的:
- 评估是否支持DL的设备增强了内科医生在没有事先心脏超声波培训的情况下获得多视图有限回声心脏图的能力.
- 评估DL对扫描时间和图像质量的影响.
主要方法:
- 单中心随机对照试验,对38名内科住院医生进行了两周的随机对照试验.
- 参与者使用了带有或没有DL实时指导的便携式超声波设备.
- 主要结果:总获取时间;次要结果:图像质量和参与者的态度.
主要成果:
- 配备DL的设备显著减少了总扫描时间 (152s vs. 266s,P < 0.001).
- DL组获得了优异的图像质量 (修改后的RACE分数为15比11,P=0.034).
- 在具有挑战性的观点中,表现改善最为显著.
结论:
- 深度学习增强的超声波设备显著提高了初学者使用心声回声图的获取速度和图像质量.
- 增强DL超声波可以解决诊断成像缺陷,使非专家能够获得临床上有用的心脏图像.
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