Covid19 Detection using Machine Learning Models

About Our Project:

Millions of people are infected by the coronavirus disease 2019 (COVID-19) around the world. Within three months of its first report, it rapidly spread worldwide with thousands of deaths. Since that time, not only underdeveloped and developing countries, but also developed countries have suffered from insufficient medical resources and diagnoses. In this circumstance, researchers from medical and engineering fields have tried to develop automatic COVID-19 detection toolkits using machine learning (ML) techniques. The dataset is the fundamental element of any detection tool therefore, most of the ML-based COVID-19 detection research was conducted used chest x-ray and computed tomography (CT) image datasets. Our aims is to build a Machine Learning based system to detect covid19 using chest xray images efficiently and effectively. In our machine learning model we use mobileNet architecture to train a dataset with 648 chest xray images with 2 classes ‘Normal’ and ‘COVID’ and we achieve 97% of accuracy.

Project Member-

Mananjay Nath(200350007003)

Iftikar Ahmed(200350007002)

Himasmita Boro(200350007001)

Project Guide

Manjula Kalita, Assistant Professor


Fig- Predict the xray image positive or Negative