优化语音样本数量和录制设置用于预测2型糖尿病:回顾性研究
Atousa Assadi1, Jessica Oreskovic1, Jaycee Kaufman1
1Klick Applied Sciences, 175 Bloor St East, North Tower, 3rd floor, Toronto, ON, M4W3R8, Canada, 1 6472068717.
JMIR biomedical engineering
|June 27, 2025
概括
优化语音录音对2型糖尿病 (T2DM) 的诊断需要最多6个样本. 在前两天内收集记录可以提高诊断的准确性,减少患者的负担.
科学领域:
- 生物医学工程 生物医学工程
- 语音科学 语言科学
- 医学诊断 医学诊断 医学诊断
背景情况:
- 来自语音的声学生物标志物为诊断2型糖尿病 (T2DM) 提供了一种非侵入性方法.
- 目前存在关于语音录制的最佳数量和时间表,以准确诊断T2DM的知识差距.
研究的目的:
- 为了确定T2DM诊断的理想数量的语音样本.
- 建立最佳的记录时间表 (频率和时间),以最大限度地提高诊断效率并最大限度地降低患者负担.
主要方法:
- 分析了78名成年人的5035个语音录音 (39名患有T2DM).
- 在各种记录条件下对基于语音的T2DM诊断模型的评估.
- 使用细分线性回归和肯德尔相关性的统计分析 (P<.05显著性).
主要成果:
- 模型的准确性提高了6个语音记录,而1个.
- 男性的精度从59.61%增加到65.02%,女性从65.55%增加到69.43%.
- 在前两天内收集记录,获得更高的准确性 (73.95%的女性,85.48%的男性).
结论:
- 可以建立最佳语音录音设置,以平衡诊断准确性和患者便利性.
- 这项研究为使用语音生物标志物进行有效的T2DM查提供了框架.
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