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Multiple sclerosis is a debilitating disease that affects the central nervous system, a disease that can cause issues with the optic nerve, brain, and spinal cord. An estimated 2.8 million people have multiple sclerosis. Every five minutes, a new case of multiple sclerosis is reported worldwide. This study explores QML classifiers in the diagnosis of multiple sclerosis and powers the quantum algorithm to enhance diagnostic accuracy and prediction capabilities. Although quantum machine learning (QML) provides diagnostic and predictive skills along with exponential speedups in specific settings, classical machine learning techniques are still able to solve problems. The research presents a comparative analysis of pertinent traditional and quantum machine learning techniques, shedding light on their strengths and limitations of MS.

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Diagnosis and Prediction of Multiple Sclerosis Disease Using Quantum Machine Learning Classifiers

  • 会议论文

  • 发表日期：

    2025年

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  • Jyoti Garg,
  • Vaishali Mehta,
  • Dolly Sharma,
  • Saurabh Yadav

摘要

Multiple sclerosis is a debilitating disease that affects the central nervous system, a disease that can cause issues with the optic nerve, brain, and spinal cord. An estimated 2.8 million people have multiple sclerosis. Every five minutes, a new case of multiple sclerosis is reported worldwide. This study explores QML classifiers in the diagnosis of multiple sclerosis and powers the quantum algorithm to enhance diagnostic accuracy and prediction capabilities. Although quantum machine learning (QML) provides diagnostic and predictive skills along with exponential speedups in specific settings, classical machine learning techniques are still able to solve problems. The research presents a comparative analysis of pertinent traditional and quantum machine learning techniques, shedding light on their strengths and limitations of MS.