Developing a Web Application for Enhanced Analysis of Respiratory Sounds, with a Particular Emphasis on Clustering

This paper merges bioinformatics and medical engineering to enhance respiratory health research. We developed a web application for processing and analyzing respiratory sound time-series data. Ou development demonstrates promising results in various tasks and highlights the potential of unsupervised learning methods like k-means for future advancements in health informatics. The application offers a novel interface for comprehensive respiratory sound analysis. The source code for the DigitaLung WebApp is available on Github.