Deep Learning Techniques for Detection of COPD

Bys: Vijarania, Meenu and Gupta, Swati

Deep COPD, an innovative deep learning approach for accurate detection of Chronic Obstructive Pulmonary Disease (COPD) using respiratory sound analysis. The proposed approach utilizes a Convolutional Neural Network (CNN) model trained on a respiratory sound database containing wheezes, crackles, and both crackles and wheezes. To overcome the challenge of a small dataset, innovative techniques such as device-specific fine-tuning, concatenation-based augmentation, blank region clipping, and smart padding are employed. These techniques enable efficient utilization of the dataset, resulting in an impressive accuracy of 90% to 95%.

• Format: Paperback
• Language: English
• ISBN: 620746527X
• ISBN13: 9786207465279
• Release Date: February 2024
• Publisher: LAP Lambert Academic Publishing
• Length: 52 Pages
• Weight: 0.20 lbs.
• Dimensions: 0.1" x 6.0" x 9.0"