CNN BASED CHEST X-RAY CLASSIFICATION
Dr.Harish B G
, Mr. Chetan Kumar G S , Deekshith H M , Lavanya S L
Convolutional Neural Network (CNN), Chest X-ray, Deep Learning, Image Preprocessing, Machine Learning, Pneumonia detection.
India faces acute shortage of radiologists. As per NCBI, USA India has one radiologist per 1,00,000 people. In past two years we have seen unprecedented COVID-19 pandemic which has posed a huge burden on our health care infrastructure and health care professionals. The rural parts are hit worst struggling to provide lifesaving health care access causing millions of Indians to lose their lives. In this regard our project focuses on developing a web based application which may reduce the burden on health care professionals and help in timely diagnosis of chest x-ray findings without delays and with precision. This will help to treat patients with utmost care, can avoid unnecessary surgeries and save lives. In the recent years Artificial Intelligence (AI) empowered systems have proven to be dominant in all domains. Artificial Intelligence has attracted most of the researchers of the recent past. Artificial Intelligence which encompasses all the industries has been proven to be vital in Health care by helping healthcare professionals in taking decisions and also in diagnosis and detection of several critical ailments like cancers and others. In this project we have leveraged the transfer learning as benchmark to obtain the models for our task of classification. We have executed the experiment through the various standard models available retaining the similar experimental conditions and did the comparative analysis to evaluate them and to pick the best one among them. The results achieved show that Densenet-169 provided the best results with 95.56 percent validation accuracy which has been used for making predictions in the web application.
"CNN BASED CHEST X-RAY CLASSIFICATION", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 9, page no.332 - 339, September-2023, Available :https://ijsdr.org/papers/IJSDR2309055.pdf
Volume 8
Issue 9,
September-2023
Pages : 332 - 339
Paper Reg. ID: IJSDR_208528
Published Paper Id: IJSDR2309055
Downloads: 000347187
Research Area: Master of Computer Application
Country: chikkamagaluru, karnataka, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
