International Conference on Signal, Systems, and Computing for Next-Gen Automation (ICSSCNA)

Performance of Quantum Machine Learning Algorithm for Prediction of Dementia Disease

Rajneesh Kumar, S. Aisha Siddika, M. Ram Kumar

Published May 4, 2026• 0 citations

Abstract

Dementia is a brain disorder which affects the human memory, behavior and cognitive abilities. The person affected with dementia is unable to perform daily activities. So, there is a need of a model which identifies the Dementia. Many researchers have designed machine learning and deep learning models which uses MRI, clinical data, and medical imaging. The existing models take much time to provide the decision. The Quantum mechine learning algorithm will greatly reduce the execution time. A Quantum Dementia Classification (QDC) model is designed to predict the Dementia disease. The QDC model achieved the accuracy of 95 %. Early detection of Dementia disease can help the doctor to provide more appropriate treatment. The objective of this study is to develop an efficient Quantum Dementia Classification (QDC) model for accurate and early prediction of dementia using clinical and cognitive features. Index Terms-Dementia, Quantum Machine Learning, Quantum Dementia Classification, Prediction.

DOI: 10.1109/icsscna68616.2026.11546939

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