Grand Challenge on Respiratory Sound Classification for SPRSound Dataset

作者：Qing Zhang, Jing Zhang, Jiajun Yuan, Huajie Huang, Yuhang Zhang, Changyan Chen, Jilei Lin, Baoqin Zhang, Gaomei Lv, Shuzhu Lin, Na Wang, Xin Liu, Mingyu Tang, Yahua Wang, Lu Liu, Hui Ma, Dan Xie, Lihua Wu, Haibo Yang, Shuhua Yuan, Mengjun Chen, Bingxue Zhang, Hongyuan Zhou, Jian Zhao, Yongfu Li, Yong Yin, Liebin Zhao, Guoxing Wang, Yong Lian · 年份：2023 · DOI：10.1109/biocas58349.2023.10388719 · 被引用次数：11 · 研究领域：Phonocardiography and Auscultation Techniques、Music and Audio Processing、Respiratory and Cough-Related Research

Globally, respiratory diseases are the leading cause of death, making it essential to develop an automatic respiratory sounds software to speed up diagnosis and reduce physician workload. A recent line of attempts have been proposed to predict accurately, but they have yet been able to provide a satisfactory generalization performance. In this contest, we invited the community to develop more accurate and generalized respiratory sound algorithms. A starter code is provided to standardize the submissions and lower the barrier. New testing set is prepared to evaluate the generalization performance of the submissions. Top 3 teams will present their work at IEEE BioCAS 2023 conference.