{"title":"Detection of Pneumonia Using Deep Learning","authors":"Nishant Borkar, Atharva Zararia, Riddhi Gangbhoj, Prashant Kumar, Vaishnavi Bhaiyya","doi":"10.47164/ijngc.v14i1.1023","DOIUrl":null,"url":null,"abstract":"The main idea of the research paper is to detect pneumonia from the patient’s chest x- rays. Pneumonia is the infection that causes inflammation of the air sacs in one or both the lungs. The air sacs are filled with purulent material (pus) causing breath shortness, cough, fever, chills.A variety of bacteria, viruses, and fungi can cause pneumonia. In this paper, we used machine learning algorithms to process x-ray images to determine whether or not the patient has pneumonia. This Experiment focusses on the use of deep learning algorithms with VGG16 pre-processing, keras and adams in order to build a model with high accuracy.","PeriodicalId":42021,"journal":{"name":"International Journal of Next-Generation Computing","volume":"33 1","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Next-Generation Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.47164/ijngc.v14i1.1023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The main idea of the research paper is to detect pneumonia from the patient’s chest x- rays. Pneumonia is the infection that causes inflammation of the air sacs in one or both the lungs. The air sacs are filled with purulent material (pus) causing breath shortness, cough, fever, chills.A variety of bacteria, viruses, and fungi can cause pneumonia. In this paper, we used machine learning algorithms to process x-ray images to determine whether or not the patient has pneumonia. This Experiment focusses on the use of deep learning algorithms with VGG16 pre-processing, keras and adams in order to build a model with high accuracy.