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- Title
MLDC: multi-lung disease classification using quantum classifier and artificial neural networks.
- Authors
Arora, Riya; Rao, G. V. Eswara; Banerjea, Shashwati; Rajitha, B.
- Abstract
Lung diseases are one of the most common diseases around the world. The risk of these diseases are more in under-developed and developing countries, where millions of people are battling with poverty and living in polluted air. Chest X-Ray images are helpful screening tool for lung disease detection. However, disease diagnosis requires expert medical professionals. Furthermore, in developing and under-developed nations, the doctor-to-patient ratio is comparatively poor. Deep learning algorithms have recently demonstrated promise in the analysis of medical images and the discovery of patterns. In this current work, we have proposed a model MLDC (Multi-Lung Disease Classification) to detect common lung diseases. It introduces a MLDC feature extraction model with two different new classifiers, considering ANN (an artificial neural network) and QC (a quantum classifier). In this proposed model, tests are performed on the LDD (Lung Disease Dataset), which includes COVID-19, pneumonia, tuberculosis, and a healthy person's lung from chest X-ray images. Our proposed model achieves an accuracy of 95.6% for MLDC-ANN and 97.5% for MLDC-QC at a lower computational cost.
- Subjects
ARTIFICIAL neural networks; DEEP learning; NOSOLOGY; MACHINE learning; LUNG diseases; IMAGE analysis
- Publication
Neural Computing & Applications, 2024, Vol 36, Issue 7, p3803
- ISSN
0941-0643
- Publication type
Article
- DOI
10.1007/s00521-023-09207-3