Cancer Cell Detection Using a Hybrid Quantum and Classical Machine Learning Model

Kalluru Hitesh, Pushpa P. V

2025

Abstract

The early diagnosis of cancer using MRI is vital in medical diagnostics. Traditional machine learning approaches struggle with the high dimensionality and complexity of medical image data. As quantum computing technology progresses, such hybrid approaches are expected to become increasingly practical, leading to significant advancements in the early detection and diagnosis of cancer. This research investigates quantum machine learning for the classification task, utilizing a Support Vector Machine (SVM) with a quantum kernel to detect cancer cells from MRI scans with improved accuracy and efficiency. The quantum feature space is created through quantum feature mapping of classical data, enhancing the SVM's ability to classify cancerous and non-cancerous cells. The proposed solution consists of a quantum machine learning model, that utilizes the classical algorithm with quantum kernel, showing a significant potential to revolutionize medical diagnostics. By integrating the strengths of quantum computing with classical machine learning techniques, this approach provides a powerful and efficient tool for medical image analysis. The proposed quantum machine learning model gives the accurate analysis of cancer cells detection present in MRI scans of the brain.

Paper Citation

in Harvard Style

Hitesh K. and P. V P. (2025). Cancer Cell Detection Using a Hybrid Quantum and Classical Machine Learning Model. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 189-194. DOI: 10.5220/0013589100004664

in Bibtex Style

@conference{incoft25,
author={Kalluru Hitesh and Pushpa P. V},
title={Cancer Cell Detection Using a Hybrid Quantum and Classical Machine Learning Model},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT},
year={2025},
pages={189-194},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013589100004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT
TI - Cancer Cell Detection Using a Hybrid Quantum and Classical Machine Learning Model
SN - 978-989-758-763-4
AU - Hitesh K.
AU - P. V P.
PY - 2025
SP - 189
EP - 194
DO - 10.5220/0013589100004664
PB - SciTePress