Creating virtual doctors by deploying the deep learning model for identifying pneumonia disease using chest-Xray

Archana Tamizharasan; Akhilaa Akhilaa; Yashwant Singh Chouhan; Makhan Kumbhkar; Yashwardhan Singh

doi:10.53730/ijhs.v6nS2.8354

Authors

Archana Tamizharasan
archana.tamizharasan@gmail.com
Assistant Professor (Sr), School of Computer science and engineering, VIT University, Vellore, Tamilnadu, India
Akhilaa Assistant Professor, Department of Information Science and Engineering, CMR Institute of Technology, Bengaluru, Karnataka, India
Yashwant Singh Chouhan Director, Department of Computer Science and Elex, Christian Eminent College, Indore, Madhya Pradesh, India
Makhan Kumbhkar Assistant Professor, Department of Computer Science and Elex, Christian Eminent College, Indore, Madhya Pradesh, India
Yashwardhan Singh Student, Department of Computer Science, Christian Eminent College, Indore, Madhya Pradesh, India

Keywords:

pneumonia, web development, virtual doctor, neural network, image processing, CNN

Abstract

Pneumonia is a lung infection that is caused due to viruses, bacteria, and fungus. Pneumonia is a type of disease that can be cured if it was founded in its early stages. The website designed using this research acts as a virtual doctor and identifies the presence of pneumonia. This is done with the help of the Deep Learning (DL) method named the Convolutional Neural Network (CNN). A dataset consisting of both normal and pneumonia affected images is collected and it is used to train, test, and validate the DL model. The images are the X-ray images of the chest of the human being. Along with the model, a website is designed using HTML. This website provides the result of whether the image uploaded is pneumonia-affected or not using the DL model. The model is then trained again and again to achieve higher accuracy. The model is then integrated with the website and it acts as a virtual doctor. This website can reduce the risk of pneumonia to reach a critical stage.

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