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This project implements a comprehensive comparison of quantum and classical SVM algorithms in the context of brain tumor classification (GBM and LGG) based on TCGA genetic data. The study includes robustness analysis of different quantum feature maps against various types and levels of noise in medical data. https://michalkasprowicz.com
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README.md

Genomic_data_QSVM

The aim of the work is to conduct a series of experiments using quantum computing elements in combination with classical machine learning algorithms. In this specific case, the author focused on the support vector machine algorithm. The work addresses the issue of genomic data analysis in terms of cancer mutations.