Virufy

Virufy数据集是由Virufy AI研究组和加州大学旧金山分校医学院合作创建，旨在通过收集全球智能手机录制的咳嗽音频样本，开发一种基于AI的COVID-19检测方法。该数据集包含2748条来自世界各地的咳嗽音频，用于训练和验证COVID-19检测模型。创建过程中，数据集通过智能手机应用收集，确保了数据的多样性和广泛性。该数据集主要应用于开发和测试COVID-19的AI检测算法，旨在解决快速、低成本的COVID-19检测需求，特别适用于资源有限地区。

The Virufy Dataset was collaboratively developed by the Virufy AI Research Group and the School of Medicine, University of California, San Francisco. It aims to create an AI-based COVID-19 detection method by collecting cough audio samples recorded by smartphones across the globe. This dataset contains 2,748 cough audio samples from all over the world, which are utilized for training and validating COVID-19 detection models. During the dataset construction, the data was collected via smartphone applications, ensuring the diversity and broad representativeness of the samples. This dataset is primarily applied to develop and test AI-based COVID-19 detection algorithms, with the goal of addressing the demand for rapid and low-cost COVID-19 testing, and is particularly suitable for resource-limited regions.