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Detection of Antibiotic Constituent in Aspergillus flavus Using Quantum Convolutional Neural Network

Author

Listed:
  • Sannidhan M. S.

    (NMAM Institute of Technology (deemed), India)

  • Jason Elroy Martis

    (NMAM Institute of Technology (deemed), India)

  • Ramesh Sunder Nayak

    (Canara Engineering College (deemed), India)

  • Sunil Kumar Aithal

    (NMAM Institute of Technology (deemed), India)

  • Sudeepa K. B.

    (NMAM Institute of Technology (deemed), India)

Abstract

Treatment of influenza and its complications is a major challenge for healthcare systems. Pyrazine is one drug used in treating influenza. Aspergillic acid is major antibiotic constituent in pyrazine compounds mined from Aspergillus flavus' final stage. This stage of flavus is detected through color change forming a pale-yellow crystal structure. Detection of the same is complex and demands an experienced fraternity to continuously monitor the growth of fungus and identify its color change. However, researches proved that the task needs to be perfect and a tiny human error leads to a catastrophe in antibiotic creation. To avoid these flaws, druggists make a huge investment on costly equipment for accurate detection. To overcome these drawbacks, this article proposes a hybrid quantum convolutional neural network that predicts various stages of the fungus from the microscope's sample. To train the network, about 47,000 samples were poised under typical lab settings. The proposed system was tested in usual conditions and positively isolated the mature samples with 96% efficiency.

Suggested Citation

  • Sannidhan M. S. & Jason Elroy Martis & Ramesh Sunder Nayak & Sunil Kumar Aithal & Sudeepa K. B., 2023. "Detection of Antibiotic Constituent in Aspergillus flavus Using Quantum Convolutional Neural Network," International Journal of E-Health and Medical Communications (IJEHMC), IGI Global, vol. 14(1), pages 1-26, January.
    • Handle: RePEc:igg:jehmc0:v:14:y:2023:i:1:p:1-26
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    References listed on IDEAS

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    1. Steven Lawrence Fernandes & G. Josemin Bala, 2018. "Matching images captured from unmanned aerial vehicle," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(1), pages 26-32, February.
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