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iConDet2: An Improved Conjunctivitis Detection Portable Healthcare App Powered by Artificial Intelligence

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Applied Intelligence and Informatics (AII 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1724))

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Abstract

Conjunctivitis is one of the common and contagious ocular diseases which affects the conjunctiva of the human eye. Both the bacterial and viral types of it can be treated with eye drops and other medicines. It is important to diagnose the disease at its early stage to realise the connection between it and other diseases, especially COVID-19. Mobile applications like iConDet is such a solution that performs well for the initial screening of Conjunctivitis. In this work, we present with iConDet2 which provides an advanced solution than the earlier version of it. It is faster with a higher accuracy level (95%) than the previously released iConDet.

M. Adak and A. Chatterjee—Contributed equally.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Institute of Engineering and Management, Kolkata, India

    Mainak Adak, Aayushman Chatterjee & Nilanjana Dutta Roy

  2. Department of Computer Science, Nottingham Trent University, Clifton, Nottingham, NG11 8NS, UK

    Mufti Mahmud

  3. Computing and Informatics Research Centre, Nottingham Trent University, Clifton, Nottingham, NG11 8NS, UK

    Mufti Mahmud

  4. Medical Technologies Innovation Facility, Nottingham Trent University, Clifton, Nottingham, NG11 8NS, UK

    Mufti Mahmud

Authors
  1. Mainak Adak
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  2. Aayushman Chatterjee
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  3. Nilanjana Dutta Roy
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  4. Mufti Mahmud
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Corresponding authors

Correspondence to Nilanjana Dutta Roy or Mufti Mahmud .

Editor information

Editors and Affiliations

  1. Nottingham Trent University, Nottingham, UK

    Mufti Mahmud

  2. University Mediterranea of Reggio Calabria, Reggio Calabria, Italy

    Cosimo Ieracitano

  3. Jahangirnagar University, Dhaka, Bangladesh

    M. Shamim Kaiser

  4. University Mediterranea of Reggio Calabria, Reggio Calabria, Italy

    Nadia Mammone

  5. University Mediterranea of Reggio Calabria, Reggio Calabria, Italy

    Francesco Carlo Morabito

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© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Adak, M., Chatterjee, A., Roy, N.D., Mahmud, M. (2022). iConDet2: An Improved Conjunctivitis Detection Portable Healthcare App Powered by Artificial Intelligence. In: Mahmud, M., Ieracitano, C., Kaiser, M.S., Mammone, N., Morabito, F.C. (eds) Applied Intelligence and Informatics. AII 2022. Communications in Computer and Information Science, vol 1724. Springer, Cham. https://doi.org/10.1007/978-3-031-24801-6_15

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