|
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016 open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15 |
Imp Links for Author
Imp Links for Reviewer
Research Area
Subscribe IJSDR
Visitor Counter
Copyright Infringement Claims
Indexing Partner
|
Published Paper Details
|
|
| Paper Title: | CNN BASED CHEST X-RAY CLASSIFICATION |
| Authors Name: | Dr.Harish B G , Mr. Chetan Kumar G S , Deekshith H M , Lavanya S L |
| Unique Id: | IJSDR2309055 |
| Published In: | Volume 8 Issue 9, September-2023 |
| Abstract: | 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. |
| Keywords: | Convolutional Neural Network (CNN), Chest X-ray, Deep Learning, Image Preprocessing, Machine Learning, Pneumonia detection. |
| Cite Article: | "CNN BASED CHEST X-RAY CLASSIFICATION", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.8, Issue 9, page no.332 - 339, September-2023, Available :http://www.ijsdr.org/papers/IJSDR2309055.pdf |
| Downloads: | 000251441 |
| Publication Details: | Published Paper ID: IJSDR2309055 Registration ID:208528 Published In: Volume 8 Issue 9, September-2023 DOI (Digital Object Identifier): Page No: 332 - 339 Publisher: IJSDR | www.ijsdr.org ISSN Number: 2455-2631 |
|
Click Here to Download This Article |
|
| Article Preview | |
|
|
|
Major Indexing from www.ijsdr.org
| Google Scholar | ResearcherID Thomson Reuters | Mendeley : reference manager | Academia.edu |
| arXiv.org : cornell university library | Research Gate | CiteSeerX | DOAJ : Directory of Open Access Journals |
| DRJI | Index Copernicus International | Scribd | DocStoc |
Track Paper
Important Links
Conference Proposal
ISSN
 |
 |
DOI (A digital object identifier)
  Providing A digital object identifier by DOI How to GET DOI and Hard Copy Related |
Open Access License Policy
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
|
 |
 |
 |
Social Media
Indexing Partner |
|||
| Copyright © 2023 - All Rights Reserved - IJSDR | |||
Facebook Twitter Instagram LinkedIn