COVID-19 DETECTION ANDROID APP BASED ON CHEST X-Rays & CT SCANS - Basantwani, Nitin; Ashish Kumar; Sumit Gangwar; Ashish Olkha; Prince prijwal; Gauri Mathur (INFOCOMP Journal of Computer Science, 2021)
The Covid-19 app based on Chest X-rays & CT scans is an integration of Machine learning and android. Our group developed an android application that uses an ML model and predicts if the image captured or uploaded by the user of a Chest X-rays or a CT scan has Covid19. The main tools used for the development of this project were android studio & Firebase for android app development, Jupyter notebook & google Colab as a code editor along with google drive to fetch the data. The main Libraries used for training ML models were Tensorflow, Keras and the method used was Transfer Learning with the help of InceptionV3 pre-trained model on the Imagenet dataset In coping and fighting against COVID-19, the most critical step is to effectively screen and diagnose infected patients. RT-PCR is considered to be a reliable test for detection of coronavirus, but the problem with RT-PCR test and Elisa tests is that they take a lot of time to generate results, Since Covid is highly contagious and spreads through Human-to-Human Interactions it’s Crucial to detect it as early as possible to stop the transmission. Corona is an Infectious disease that affects the Lungs similar to Pneumonia, Deep Learning and Machine Learning models have produced significant results in the past for pneumonia detection in Lungs in this project we tried the same approach where we trained the Deep learning model on more than 13000 images of CT scans & 9000 images for X-rays and used the model to build an android application for users, the application is user friendly and easy to use. Since radiology scanning takes far less time to generate results as compared to the RT-PCR & ELISA tests, we believe our app will be convenient and it’ll help people in the early detection of Covid.