通过人工智能增强医学诊断:专注于呼吸系统疾病检测
Sachin Sharma1, Siddhant Pandey2, Dharmesh Shah3
1Department of Big Data Analytics, Adani Institute of Digital Technology Management, Gandhinagar, Gujarat, India.
概括
人工智能 (AI) 有助于通过听力听觉仪诊断呼吸系统疾病. 一个卷积神经网络实现了90%的准确性,为早期检测和改善医疗保健提供了一个新的工具.
科学领域:
- 医疗技术 医疗技术 医学技术
- 医疗保健中的人工智能
- 呼吸系统医学 呼吸系统医学
背景情况:
- 人工智能 (AI) 正在改变医学诊断和医疗保健提供.
- 智能系统提高医疗从业人员的绩效,减少工作量.
- 人工智能和深度学习显著提升了医学成像和音频分析.
研究的目的:
- 开发一个系统,利用电子耳语镜音频录制来预测呼吸系统疾病.
- 为了利用人工智能和深度学习进行早期和准确的呼吸道疾病诊断.
- 为医疗从业者创建一个支持工具,优化他们的表现.
主要方法:
- 一个卷积神经网络 (CNN) 在增强呼吸声数据库 (1428个音频文件) 上受训.
- 数据增强技术包括调度转移,时间延伸,噪声添加,掩盖,压缩和重新采样.
- 从单一音频文件中提取特征,为开发四层CNN模型提供了信息.
主要成果:
- 开发的CNN模型从音频数据中预测呼吸系统疾病的准确率达到90%.
- 使用CNN模型和Streamlit创建了一个软件工具,用于实际应用.
- 该系统展示了早期和准确诊断的潜力,帮助医疗从业者.
结论:
- 人工智能驱动的音频分析为呼吸系统疾病检测提供了一个有前途的方法.
- 开发的软件作为早期诊断的新工具,减少了医疗保健负担.
- 这项技术提高了医疗从业人员的表现,并通过改进诊断能力来优化患者护理.
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