• RITU GILL
• Ms ARCHANA ROHILLA
• Mr.Yash Dhankhar

The purpose of this project is to create a completely automated system for diagnosing lung illnesses through chest x-rays. Users and professional diagnostic centres will be able to submit chest radiographs (x-rays) and get precise predictions based on them. Chest radiography is critical for illness diagnosis. "Chest X-ray (CXR) radiography may be utilised as a first-line triage procedure for patients with pneumonia who do not have COVID-19." However, the similarity between the characteristics of COVID-19 CXR pictures and pneumonia caused by other diseases complicates radiologists' differential diagnosis. We predicted that machine learning-based classifiers could consistently discriminate COVID-19 patients' CXR pictures from those with other types of pneumonia. We utilised a dimensionality reduction technique to create a collection of optimum features from CXR pictures in order to develop an efficient machine learning classifier capable of accurately and sensitively discriminating COVID-19 instances from non-COVID-19 cases. We successfully built our classifier using a very modest dataset of CXR pictures by using global characteristics from the whole set of CXR images. We suggest that our COVID-Classifier, in combination with other tests, be utilised to optimise hospital resource allocation via fast triage of non-COVID-19 patients.

Lung, Disease, Xray Image, covid 19

"LUNG DISEASE DETECTION USING X RAYS IN COVID-19 VICTIMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 9, page no.b727-b732, September-2021, Available :http://www.jetir.org/papers/JETIR2109188.pdf

"LUNG DISEASE DETECTION USING X RAYS IN COVID-19 VICTIMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 9, page no. ppb727-b732, September-2021, Available at : http://www.jetir.org/papers/JETIR2109188.pdf