[A lung sound classification model with a spatial and channel reconstruction convolutional module].
The accuracy, sensitivity, specificity and F1 score of the proposed method reached 85.68%, 93.55%, 86.79% and 90.51%, respectively, demonstrating its good performance in classification tasks in the ICBHI2017 lung sound database, especially for distinguishing normal from abnormal lung sounds.
Authors
- Nong Ye (ORCID: https://orcid.org/0000-0001-8977-4501)
- Jialin Jiang (ORCID: https://orcid.org/0000-0002-3955-1016)
- Chaozhong Wu (ORCID: https://orcid.org/0000-0003-3338-0436)
Institutions
- Lanzhou Jiaotong University (CN)
Publication Details
- Journal
- PubMed
- Published
- 2024-09-20
- DOI
- https://doi.org/10.12122/j.issn.1673-4254.2024.09.12
- Primary Topic
- Phonocardiography and Auscultation Techniques
- Type
- article