斯瓦萨人工智能平台使用咳声音查COVID-19:一个横截面研究
Padmalatha Pentakota1, Gowrisree Rudraraju2, Narayana Rao Sripada3
1Andhra Medical College, Visakhapatnam, India.
Scientific reports
|October 25, 2023
概括
一个新的AI平台Swaasa使用咳的声音和症状来查COVID-19. 这种人工智能工具显示出作为一种具有成本效益的方法,用于早期发现疾病和减少传播的承诺.
科学领域:
- 医疗技术 医疗技术 医学技术
- 人工智能的人工智能
- 公共卫生 公共卫生
背景情况:
- 由于COVID-19的流行,需要有效的查方法.
- 人工智能 (AI) 提供了在疾病检测中分析听觉数据的潜力.
- 目前的选方法可能是昂贵的,需要技术专长.
研究的目的:
- 开发和验证Swaasa AI平台用于COVID-19查.
- 通过咳的声音和症状来评估AI在检测COVID-19中的有效性.
- 为初步COVID-19查提供一个具有成本效益的远程监测工具.
主要方法:
- 收集了234名COVID-19疑似患者的咳数据.
- 使用卷积神经网络 (CNN) 和前人工神经网络 (FFANN) 算法.
- 两种模型的结合输出用于疾病概率预测.
主要成果:
- 临床验证显示75.54%的准确性,95.45%的敏感性和73.46%的特异性用于COVID-19检测.
- 对183名受试者的试点测试产生了70.73%的积极预测值.
- 斯瓦萨平台在识别可能的COVID-19病例方面展示了潜力.
结论:
- 斯瓦萨人工智能平台显示出作为COVID-19初步查工具的潜力.
- 这种人工智能驱动的方法可以帮助控制疾病的传播.
- 斯瓦萨为早期COVID-19检测提供了一种具有成本效益和可访问性的替代方案.
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