使用机器学习来识别乳腺癌幸存者的主观认知障碍语音标记
Amélie B Richard1,2, Alexandre Foncelle3, Sophie Jacquin-Courtois3,4
1Université Montpellier Paul-Valéry, Praxiling CNRS UMR5267, Route de Mende, 34199, Montpellier cedex 5, France. amelie.richard@univ-montp3.fr.
Journal of cancer survivorship : research and practice
|September 1, 2025
概括
在乳腺癌幸存者中,长时间的沉默可能表明与癌症相关的认知障碍 (CRCI). 语音分析提供了一种非侵入性方法来检测CRCI,补充主观评估.
科学领域:
- 神经科学
- 癌症学
- 语音病理学
背景情况:
- 与癌症相关的认知障碍 (CRCI) 影响了癌症幸存者,主观困难通常通过问卷进行识别.
- 对CRCI的客观神经心理测试不太常见,强调需要新的检测方法.
- 语音分析提供了一个潜在的客观方法来评估CRCI.
研究的目的:
- 识别能够检测癌症幸存者的语音标记.
- 评估语音特征在CRCI分类中的有效性.
主要方法:
- 44名乳腺癌幸存者和13名对照者讲述了一个故事.
- 半自动语音分析提取了14个特征, 用于机器学习模型.
- 通过使用FACT-Cog问卷进行CRCI评估,并对混因素进行心理评估.
主要成果:
- 语音与静音比率,平均静音暂停时间和平均填充暂停时间的结合最好地预测CRCI (ROC=0.74,准确率=73.7%).
- 贝叶斯模型表明,言语沉默与CRCI和报告的抑郁症 (HADS) 有关.
- 所有组的抑郁症得分都低于临床值.
结论:
- 在谈话期间长时间的沉默暂停可能意味着乳腺癌幸存者的CRCI.
- 语音分析是一种快速,生态,非侵入性的CRCI评估工具.
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