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COVID-19 DETECTION ANDROID APP BASED ON CHEST X-Rays CT SCANS.

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Title: COVID-19 DETECTION ANDROID APP BASED ON CHEST X-Rays CT SCANS.
Authors: BASANTWANI, NITIN1 nitinbasantwani14@gmail.com, KUMAR, ASHISH1 iashishkumar3551@gmail.com, GANGWAR, SUMIT1 sumitkurmi9057@gmail.com, OLKHA, ASHISH1 iashisholkha7@gmail.com, PRIJWAL, PRINCE1 prijwal14@gmail.com, MATHUR, GAURI2 gauri.mathur@lpu.co.in
Source: INFOCOMP: Journal of Computer Science. Jun2021, Vol. 20 Issue 1, p91-100. 10p.
Subjects: Android (Operating system), Computed tomography, COVID-19, Machine learning, COVID-19 testing, Communicable diseases, Deep learning
Abstract: 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. [ABSTRACT FROM AUTHOR]
Copyright of INFOCOMP: Journal of Computer Science is the property of INFOCOMP: Journal of Computer Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: COVID-19 DETECTION ANDROID APP BASED ON CHEST X-Rays CT SCANS.
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  Data: <searchLink fieldCode="AR" term="%22BASANTWANI%2C+NITIN%22">BASANTWANI, NITIN</searchLink><relatesTo>1</relatesTo><i> nitinbasantwani14@gmail.com</i><br /><searchLink fieldCode="AR" term="%22KUMAR%2C+ASHISH%22">KUMAR, ASHISH</searchLink><relatesTo>1</relatesTo><i> iashishkumar3551@gmail.com</i><br /><searchLink fieldCode="AR" term="%22GANGWAR%2C+SUMIT%22">GANGWAR, SUMIT</searchLink><relatesTo>1</relatesTo><i> sumitkurmi9057@gmail.com</i><br /><searchLink fieldCode="AR" term="%22OLKHA%2C+ASHISH%22">OLKHA, ASHISH</searchLink><relatesTo>1</relatesTo><i> iashisholkha7@gmail.com</i><br /><searchLink fieldCode="AR" term="%22PRIJWAL%2C+PRINCE%22">PRIJWAL, PRINCE</searchLink><relatesTo>1</relatesTo><i> prijwal14@gmail.com</i><br /><searchLink fieldCode="AR" term="%22MATHUR%2C+GAURI%22">MATHUR, GAURI</searchLink><relatesTo>2</relatesTo><i> gauri.mathur@lpu.co.in</i>
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  Data: <searchLink fieldCode="JN" term="%22INFOCOMP%3A+Journal+of+Computer+Science%22">INFOCOMP: Journal of Computer Science</searchLink>. Jun2021, Vol. 20 Issue 1, p91-100. 10p.
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  Data: <searchLink fieldCode="DE" term="%22Android+%28Operating+system%29%22">Android (Operating system)</searchLink><br /><searchLink fieldCode="DE" term="%22Computed+tomography%22">Computed tomography</searchLink><br /><searchLink fieldCode="DE" term="%22COVID-19%22">COVID-19</searchLink><br /><searchLink fieldCode="DE" term="%22Machine+learning%22">Machine learning</searchLink><br /><searchLink fieldCode="DE" term="%22COVID-19+testing%22">COVID-19 testing</searchLink><br /><searchLink fieldCode="DE" term="%22Communicable+diseases%22">Communicable diseases</searchLink><br /><searchLink fieldCode="DE" term="%22Deep+learning%22">Deep learning</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of INFOCOMP: Journal of Computer Science is the property of INFOCOMP: Journal of Computer Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=150781076
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        Text: English
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        StartPage: 91
    Subjects:
      – SubjectFull: Android (Operating system)
        Type: general
      – SubjectFull: Computed tomography
        Type: general
      – SubjectFull: COVID-19
        Type: general
      – SubjectFull: Machine learning
        Type: general
      – SubjectFull: COVID-19 testing
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      – SubjectFull: Communicable diseases
        Type: general
      – SubjectFull: Deep learning
        Type: general
    Titles:
      – TitleFull: COVID-19 DETECTION ANDROID APP BASED ON CHEST X-Rays CT SCANS.
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            NameFull: BASANTWANI, NITIN
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              Text: Jun2021
              Type: published
              Y: 2021
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