Volume 18, No. 6, 2021
A Survey On Lung Disease Diagnosis Using Deep Learning
Dr. G. HEREN CHELLAM
Abstract
The COVID-19 epidemic spread rapidly over the world in 2019, which led to a dangerous situation. The virus attacks the respiratory system, resulting in pneumonia along with additional symptoms including fever, dry cough, and exhaustion that can be misdiagnosed as tuberculosis, lung cancer, or pneumonia. Consequently, as COVID-19 can cause patient death, early detection is essential. Even yet, the poor quality of the air is causing many people to have respiratory issues. Numerous lung disorders require early detection and can be caused by a variety of factors, including pollution, changing environmental conditions, and undesired everyday behaviors like drinking and smoking. Deep learning approaches are more promising and effective areas that expand the machine learning domain and can improve medical care. This study looks at the diagnostic potential of different deep-learning algorithms for lung diseases. This paper's main objective is to use deep learning to show the different patterns in lung disease diagnoses and identify current problems.
Pages: 9397-9408
Keywords: The development of deep learning algorithms has completely changed the diagnostic landscape for lung disorders.