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使用基于心电图的人工智能在肉瘤中预测对环素化疗的耐受性.

Jack B Korleski1, Regina M Koch1, Thanh P Ho2

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人工智能启用心电图 (AI-ECG) 在监测化疗患者方面表现有前途. AI-ECG准确预测了低射出分数 (EF),并可能有助于评估治疗期间的化疗耐受性.

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科学领域:

  • 心脏病学 心脏病学
  • 在瘤学瘤学.
  • 人工智能的人工智能

背景情况:

  • 抗环素化疗可以引起心脏毒性,需要进行心脏监测.
  • 评估化疗耐受性和心脏功能对于患者管理至关重要.

研究的目的:

  • 评估人工智能支持心电图 (AI-ECG) 在评估抗环素化疗耐受性的有用性.
  • 为了确定AI-ECG是否可以预测心脏功能,并监测化疗期间的变化.

主要方法:

  • 分析了接受 antracycline 化疗与治疗前心电图的成年肉瘤患者.
  • 人工智能-心电图 (AI-ECG) 预测年龄和喷射率 (EF);与化疗耐受性相关的变化.
  • 测量了AI-ECG用于预测低EF (<50%或<35%) 的灵敏度和特异性.

主要成果:

  • AI-ECG准确地确定了EF低的患者 (100%的灵敏度,EF的94%特异性<50%).
  • 一个趋势表明,随着AI-ECG衰老的增加,剂量减少更高 (OR 5.13,P=.32).
  • 两名治疗后EF降低的患者显示AI-ECG低EF预测显著增加.

结论:

  • 在ECG上的AI-ECG预测可以监测在环素化疗期间EF降低.
  • 建议进行进一步的研究,以验证AI-ECG衰老作为化疗耐受性的标志物.