Application of Semi-Supervised Deep Learning to ...
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Application of Semi-Supervised Deep Learning to ...
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Application of Semi-Supervised Deep Learning to Lung Sound Analysis Daniel Chamberlain, Member, IEEE, Rahul Kodgule, Daniela Ganelin, Vivek Miglani, and Richard Ribón Fletcher, Member, IEEE Abstract— The analysis of lung sounds, collected through auscultation, is a fundamental component of pulmonary disease diagnostics for primary care and general patient monitoring for telemedicine. Despite advances in computation and algorithms, the goal of automated lung sound identification and classification has remained elusive. Over the past 40 years, published work in this field has demonstrated only limited success in identifying lung sounds, with most published studies using only a small numbers of patients (typically N
