IEEE Trans Biomed Eng. 2023 Jul;70(7):2215-2226. doi: 10.1109/TBME.2023.3239372. Epub 2023 Jun 19.
Community-Acquired Pneumonia (CAP) is a significant cause of child mortality globally, due to the lack of ubiquitous monitoring methods. Clinically, the wireless stethoscope can be a promising solution since lung sounds with crackles and tachypnea are considered as the typical symptoms of CAP. In this paper, we carried out a multi-center clinical trial in four hospitals to investigate the feasibility of using a wireless stethoscope for children CAP diagnosis and prognosis. The trial collects both the left and right lung sounds from children with CAP at the time of diagnosis, improvement, and recovery. A bilateral pulmonary audio-auxiliary model (BPAM) is proposed for lung sound analysis. It learns the underlying pathological paradigm for the CAP classification by mining the contextual information of audio while preserving the structured information of breathing cycle. The clinical validation shows that the specificity and sensitivity of BPAM are over 92% in both the CAP diagnosis and prognosis for the subject-dependent experiment, over 50% in CAP diagnosis and 39% in CAP prognosis for the subject-independent experiment. Almost all benchmarked methods have improved performance by fusing left and right lung sounds, indicating the direction of hardware design and algorithmic improvement.
社区获得性肺炎（CAP）是全球儿童死亡的一个重要原因，这是由于缺乏普遍的监测方法。在临床上，无线听诊器是一种很有前途的解决方案，因为有爆裂音和呼吸急促的肺部声音被认为是 CAP 的典型症状。在本文中，我们在四所医院进行了一项多中心临床试验，以研究使用无线听诊器诊断和预测儿童 CAP 的可行性。该试验在诊断、改善和恢复时从患有 CAP 的儿童身上同时收集左右肺部声音。我们提出了一种双侧肺部音频辅助模型（BPAM），用于肺部声音分析。它通过挖掘音频的上下文信息来学习 CAP 分类的潜在病理模式，同时保留呼吸周期的结构化信息。临床验证表明，BPAM 在主体相关实验中的 CAP 诊断和预后特异性和敏感性均超过 92%，在主体独立实验中的 CAP 诊断和预后特异性和敏感性分别超过 50%和 39%。几乎所有经过基准测试的方法通过融合左右肺部声音都提高了性能，这表明了硬件设计和算法改进的方向。
