Enhanced Lung Disease Classification Using CALMNet: A Hybrid CNN-LSTM-TimeDistributed Model for Respiratory Sound Analysis
Lung diseases, such as asthma, pneumonia, and chronic obstructive pulmonary disease (COPD), pose considerable global health issues, making early diagnosis essential for effective treatment. Traditional diagnostic techniques for these ailments, especially auscultation using a stethoscope, are subject...
Saved in:
| Main Authors: | Reshma Sreejith, R.Kanesaraj Ramasamy, Wan-Noorshahida Mohd-Isa, Junaidi Abdullah |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11086531/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Corrigendum: Abnormal respiratory sounds classification using deep CNN through artificial noise addition
by: Rizwana Zulfiqar, et al.
Published: (2025-01-01) -
Using Cough Sounds for the Recognition of Multiclass Respiratory Diseases With Artificial Intelligence: A Review
by: Peng-Fei Zhang, et al.
Published: (2025-01-01) -
CycleGuardian: a framework for automatic respiratory sound classification based on improved deep clustering and contrastive learning
by: Yun Chu, et al.
Published: (2025-03-01) -
Hybrid Dual-Input Model for Respiratory Sound Classification With Mel Spectrogram and Waveform
by: Fan Wang, et al.
Published: (2025-01-01) -
Determination of the Sound Intensity Vector Field from Synchronized Sound Pressure Waveforms
by: Witold Mickiewicz, et al.
Published: (2024-12-01)