Machine Learning Approaches for Identifying Abnormal Lung Sounds in Pulmonary Disorders

Authors

  • B. Akhila, Talari Akshaya, Pakam Bindhu Sai Madhavi, Vattigunta Lavanya, Shaik Habeeba

Keywords:

Abnormal Respiratory Sounds, Pulmonary Disease Detection, Machine Learning, Real Time Diagnosis, Telemedicine, Respiratory Sound Classification, Healthcare Automation

Abstract

Accurate detection of abnormal respiratory sounds is essential for the diagnosis and management of
pulmonary diseases such as asthma, chronic obstructive pulmonary disease (COPD), and pneumonia.
With the increasing demand for remote healthcare solutions

References

. Han, M.K et al. Chronic respiratory diseases: A global view. Lancet Respir. Med. 2020, 8, 531–533.

. Esteva, A et al. A guide to deep learning in healthcare. Nat. Med. 2019, 25, 24–29.

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Published

2025-04-15

How to Cite

B. Akhila, Talari Akshaya, Pakam Bindhu Sai Madhavi, Vattigunta Lavanya, Shaik Habeeba. (2025). Machine Learning Approaches for Identifying Abnormal Lung Sounds in Pulmonary Disorders . Journal of Computational Analysis and Applications (JoCAAA), 34(4), 1288–1294. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/3126

Issue

Vol. 34 No. 4 (2025): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.