A Novel Approach for Chronic Obstructive Pulmonary Disease Diagnosis with TensorFlow-Based Image Analysis

Authors

  • Krishna Kant Agrawal Professor, School of Computing Science and Engineering, Galgotias University, Greater Noida, India
  • Ashwini S. R. Assistant Professor, Dept. Of Electronics and Telecommunication Engineering, J N N College of Engineering, Shimoga, Karnataka, India
  • Sakuldeep Singh Associate. Professor (Dept. Of Computer Science & Engineering) Sanskriti University Chhata Mathura .U.P
  • Rashmi Saini Assistant professor, Computer science and Engineering, G. B. Pant Institute of Engineering and Technology, Pauri Garhwal, Uttarakhand
  • Gurwinder Singh Associate Professor,Department of AIT-CSE, Chandigarh University, Punjab, India.
  • Vikas Lamba Chitkara University Institute of Engineering and Technology, Chitkara University,Punjab, India.
  • Nitesh Singh Bhati Assistant Professor,School of Computing Science and Engineering, Galgotias University, Greater Noida, India

Keywords:

Chronic Obstructive Pulmonary Disease (COPD), Image processing, TensorFlow-based CNNs, User-friendly interface, Expert systems

Abstract

This paper introduces an innovative approach to Chronic Obstructive Pulmonary Disease (COPD) detection through image processing, complemented by a user-friendly web application. Leveraging TensorFlow-based CNNs, the proposed system facilitates comprehensive chest X-ray analysis. The Accuracy, precision Recall and F1 score of the proposed architecture are respectively, 94.29, 93.58, 90.47 and 91.22. The workflow involves dataset loading, preprocessing, and iterative model fine-tuning. Crucially, the web application's interface enables seamless image uploads, result displays, and collaborative discussions among healthcare professionals. By merging advanced image processing techniques with accessibility, this work envisions a future where COPD detection is not only technologically sophisticated but also user-centric, promoting effective collaboration in healthcare settings.

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References

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Published

24.03.2024

How to Cite

Agrawal, K. K. ., S. R., A. ., Singh, S. ., Saini, R. ., Singh, G. ., Lamba, V. ., & Bhati, N. S. . (2024). A Novel Approach for Chronic Obstructive Pulmonary Disease Diagnosis with TensorFlow-Based Image Analysis. International Journal of Intelligent Systems and Applications in Engineering, 12(20s), 713–719. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5234

Issue

Vol. 12 No. 20s (2024)

Section

Research Article

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