Open AccessLung Disease Detection Using CNN
Author(s) -
V. Sowmya
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.35595
Subject(s) - pneumonia , classifier (uml) , convolutional neural network , computer science , artificial intelligence , covid-19 , bacterial pneumonia , disease , lung , medicine , pattern recognition (psychology) , infectious disease (medical specialty) , pathology
Covid Pneumonia is a life-threatening bacterial disease in humans that affects one or both lungs and is caused by the bacteria Streptococcus pneumonia. Also known as Covid-19, this is a respiratory illness that was first discovered in Wuhan, China. Expert radiotherapists must evaluate chest X-rays used to diagnose pneumonia. As a result, establishing an autonomous system for detecting pneumonia would be advantageous for treating the condition quickly, especially in distant places. The statistical results show that using pre trained CNN models and supervised classifier algorithms to analyse chest X-ray pictures, specifically to diagnose Pneumonia, can be highly advantageous. By constructing certain convolution neural network designs, we are developing a classifier model that accurately predicts if a person has covid or pneumonia.