Performance analysis of deep learning algorithms for classifying chronic obstructive pulmonary disease

COPD detection using machine learning

Authors

  • Pinal J. Patel Government Engineering College, Gandhinagar
  • Dhanashree Yevle Government Engineering College, Gandhinagar
  • Daksha Diwan Government Engineering College, Gandhinagar
  • Shashi Ranga Government Engineering College, Valsad
  • Kinjal Gandhi ITM(SLS) Baroda University, Vadodara
  • Samay Dumasia Government Engineering College, Gandhinagar
  • Rutu Nayak Government Engineering College, Gandhinagar

Keywords:

Respiratory diseases, COPD, Machine Learning, Deep Learning, Algorithms

Abstract

Nowadays, Deep learning (DL) and machine learning (ML) play a vital role in furnishing solutions to the medical problems. Owing to their accurate and timely forecasting models and results, ML and DL algorithms are being embraced by the medical professionals for early detection and prompt treatment of different diseases. The respiratory diseases like Chronic Obstructive Pulmonary Disease (COPD) are emerging and need an early diagnosis. The major methods for diagnosing COPD involve expensive and unsuitable spirometer and imaging equipment. In this paper, an analysis of cough sound of the patients and identification of COPD severity levels using ML and DL algorithms has been reported. The study includes experiments conducted using Librosa library and used CNN, RNN, LSTM, and MLP algorithms for detecting COPD severity levels.

URN:NBN:sciencein.jist.2024.v12.745

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Author Biographies

  • Pinal J. Patel, Government Engineering College, Gandhinagar

    Computer Engineering Department

  • Dhanashree Yevle, Government Engineering College, Gandhinagar

    Computer Engineering Department

  • Daksha Diwan, Government Engineering College, Gandhinagar

    Mathematics

  • Shashi Ranga, Government Engineering College, Valsad

    Chemical Engineering Department

  • Kinjal Gandhi, ITM(SLS) Baroda University, Vadodara

    Computer Science Engineering Department

  • Samay Dumasia, Government Engineering College, Gandhinagar

    Computer Engineering Department

  • Rutu Nayak, Government Engineering College, Gandhinagar

    Biomedical Engineering

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Published

2023-10-28

Issue

Section

Computer Sciences and Mathematics

URN

How to Cite

Patel, P. J., Yevle, D., Diwan, D., Ranga, S., Gandhi, K., Dumasia, S., & Nayak, R. (2023). Performance analysis of deep learning algorithms for classifying chronic obstructive pulmonary disease. Journal of Integrated Science and Technology, 12(2), 745. https://pubs.thesciencein.org/journal/index.php/jist/article/view/a745

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