文章基本信息

标题：COVID-19 DETECTION ANDROID APP BASED ON CHEST X-Rays & CT SCANS
本地全文：下载
作者：Nitin Basantwani ; Ashish Kumar ; Sumit Gangwar 等
期刊名称：INFOCOMP
印刷版ISSN：1807-4545
出版年度：2021
卷号：20
期号：1
页码：91-100
出版社：Federal University of Lavras
摘要：The Covid-19 android app based on Chest X-rays & CT scans is an integration of Machine learning and android. Our group developed an android application that uses a Deep learning model and predict if the user is suffering from Covid based on the chest X-rays & CT scans. 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 using the pre-trained model InceptionV3. 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 for this research project we tried to implement the same approach.
其他摘要：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.
关键词：Deep Learning; Transfer Learning; Machine Learning; TensorFlow; InceptionV3; Supervised Learning; Android Studio; Java; Python