Open AccessDetection of Pneumonia using ML & DL in Python
Author(s) -
Arjun Sharma,
Monika Negi,
Ankush Goyal,
Rachna Jain,
Preeti Nagrath
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1022/1/012066
Subject(s) - python (programming language) , pneumonia , confusion , confusion matrix , medicine , atelectasis , radiography , convolutional neural network , lung , covid-19 , respiratory system , radiology , computer science , artificial intelligence , psychology , psychoanalysis , operating system , disease , infectious disease (medical specialty)
Pneumonia is form of a respiratory infection that affects the lungs. In these acute respiratory diseases, human lungs which are made up of small sacs called alveoli which in air in normal and healthy people but in pneumonia these alveoli get filled with fluid or “pus” one of the major step of phenomena detection and treatment is getting the chest X-ray of the (CXR). Chest X-ray is a major tool in treating pneumonia, as well as many decisions taken by doctor are dependent on the chest X-ray. Our project is about detection of Pneumonia by chest X-ray using Convolutional Neural Network. This paper written by us is an efficient approach towards classifying chest X- rays into pneumonia and no pneumonia X-rays. We have taken this approach as the most used radiography method produces errors. So, we have used CNN and batch normalization from keras to develop this model, and calculated accuracy using confusion matrix. We were successful in doing so with the help of “Python” and “OpenCV”, both of which are freely available and are open source tools and can be used by anyone. Pneumonia day, states that by the year 2030, 11 million children who are under the age of 5 year.