• G. Natarajan

Respiratory diseases can affect all structures and organs related to breathing, including the nasal cavity, pharynx (or pharynx), larynx, trachea (or trachea), bronchi and bronchioles, as well as lung tissue and respiratory muscles in the chest. In the proposed work, chest x-ray images are taken in which Histogram of Oriented Gradients and Local Binary Pattern are used for feature extraction, the extracted features are fed into Radial Basis Function Neural Network and Gaussian Mixture Model which was classified into normal, Pleural Effusion, Pneumonia and Tuberculosis. When comparing Histogram of Oriented Gradients with Radial Basis Function Neural Network gives the highest accuracy of 89. 83 %.

Radial Basis Function Neural Network (RBFNN), Histogram of Oriented Gradients (HOG), Local Binary Pattern (LBP).

"CLASSIFICATION OF RESPIRATORY TRACT DISEASES USING MACHINE LEARNING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 6, page no.c1-c16, June-2022, Available :http://www.jetir.org/papers/JETIR2206201.pdf

"CLASSIFICATION OF RESPIRATORY TRACT DISEASES USING MACHINE LEARNING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 6, page no. ppc1-c16, June-2022, Available at : http://www.jetir.org/papers/JETIR2206201.pdf