State of the Art: A Pandemic Big HealthCare Analytics Solution: Image Data Classification Using Quantum MAML

Year : 2025 | Volume : 14 | Issue : 02 | Page : 1 9
    By

    Chapala Maharana,

  • Sanjeev Ku. Dash,

  • B.B. Mishra,

  1. Assistant Professor, Department of Computer Science & Engineering, Parala Maharaja Engineering College, Berhampur, Odisha, India
  2. Associate Professor, Department of Computer Science & Engineering, Silicon Institute of Technology, Bhubaneswar, Odisha, India
  3. Ex. Professor, Department of Computer Science & Engineering, Silicon Institute of Technology, Bhubaneswar, Odisha, India

Abstract

The modern age is facing many pandemic healthcare problems, e.g., covid 19, infections, inflammations, and many more, leading to critical, deadly situations. Survival rate can be increased with proper diagnosis of such data. We have proposed one of the implementations based on a medical image dataset for classification using deep reinforcement learning (RL) with quantum computing. Deep RL is the combination of DL (deep learning), generative adversarial network (GAN), and RL. The final classification is made by an ensemble classifier. The GAN is used for generating synthetic, original, and qualitative fame image data like original data. The RL is used for minimizing losses in the classification work. The GANRL method is found to be effective for such noisy, unclear image data of pandemic deadly diseases earlier. The ensemble classifier extreme gradient boosting (XGBoost) is used for classification with high accuracy. Computation can be more effective if quantum circuits are used for such work in terms of CPU cycle time (execution time) and power consumption for the processing. Quantum SVM is found to be more effective for medical data in terms of power consumption and execution time when simulated with quantum simulator than circuit.

Keywords: Deep Learning, Generative Adversarial Network, Model Agnostic Meta Learning, Reinforcement Learning, Quantum Computing.

[This article belongs to Research and Reviews : A Journal of Medical Science and Technology ]

How to cite this article:
Chapala Maharana, Sanjeev Ku. Dash, B.B. Mishra. State of the Art: A Pandemic Big HealthCare Analytics Solution: Image Data Classification Using Quantum MAML. Research and Reviews : A Journal of Medical Science and Technology. 2025; 14(02):1-9.
How to cite this URL:
Chapala Maharana, Sanjeev Ku. Dash, B.B. Mishra. State of the Art: A Pandemic Big HealthCare Analytics Solution: Image Data Classification Using Quantum MAML. Research and Reviews : A Journal of Medical Science and Technology. 2025; 14(02):1-9. Available from: https://journals.stmjournals.com/rrjomst/article=2025/view=211234


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Regular Issue Subscription Review Article
Volume 14
Issue 02
Received 27/03/2025
Accepted 05/05/2025
Published 23/05/2025
Publication Time 57 Days
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