Machine Learning-Driven Lung Sound Analysis: Novel Methodology for Asthma Diagnosis
This machine learning-based algorithm provides accurate asthma diagnosis, even in patients with normal spirometry and clinical findings, offering a non-invasive and efficient diagnostic tool.
Authors
- Prabal Datta Barua (ORCID: https://orcid.org/0000-0001-5117-8333)
- Şengül Doğan (ORCID: https://orcid.org/0000-0001-9677-5684)
- Güntuğ Batıhan (ORCID: https://orcid.org/0000-0001-5258-2856)
- Mutlu Onur Güçsav (ORCID: https://orcid.org/0000-0003-2969-4766)
- Arif Metehan Yıldız (ORCID: https://orcid.org/0000-0003-0451-8600)
- Türker Tuncer (ORCID: https://orcid.org/0000-0002-5126-6445)
- Ihsan Topaloğlu (ORCID: https://orcid.org/0000-0003-4584-156X)
- Gulfem Ozduygu (ORCID: https://orcid.org/0000-0001-7490-3913)
- Cagri Atasoy (ORCID: https://orcid.org/0000-0001-6662-9600)
- Damla Serce
- Gulsah Inanc
Institutions
- Izmir University (TR)
- Ardahan University (TR)
- Kafkas University (TR)
- Fırat University (TR)
- University of Southern Queensland (AU)
- Ege University (TR)
- Sağlık Bilimleri Üniversitesi (TR)
Publication Details
- Journal
- Advances in respiratory medicine
- Published
- 2025-09-04
- DOI
- https://doi.org/10.3390/arm93050032
- Citations
- 1
- Primary Topic
- Phonocardiography and Auscultation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 1.52