Classification of Tumor Metastasis Data by Using Quantum kernel-based Algorithms

Tai Yue Li, Venugopala Reddy Mekala, Ka Lok Ng*, Cheng Fang Su*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Tumor metastasis is a dynamic process, and its fatality rate is relatively high. Different genes are regulated during the metastasis process. Next-generation sequencing technology is a new approach that enables rapid and high throughput whole-transcriptome measurements. Support vectoTalgorithms make use of kernel functions to classify data effectively. A few studies suggest that quantum support vector machine algorithms can perform well in classification problems. If biomarkers can be identified to predict tumor metastasis accurately, it will be an important step toward precision medicine. In this study, we use both the SVM and QSVM classifiers with the addition of a certain number of features, we can achieve very good distinctions between patients with or without metastasis. This is a positive result for precision medicine studies. Also, we evaluate the performance of quantum and classical algorithms in classifying tumor metastasis data. Our preliminary study indicates that the classical kernel-based classifier performs better than the quantum version.

Original languageEnglish
Title of host publicationProceedings - IEEE 22nd International Conference on Bioinformatics and Bioengineering, BIBE 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages351-354
Number of pages4
ISBN (Electronic)9781665484879
DOIs
StatePublished - 2022
Event22nd IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2022 - Virtual, Online, Taiwan
Duration: 7 Nov 20229 Nov 2022

Publication series

NameProceedings - IEEE 22nd International Conference on Bioinformatics and Bioengineering, BIBE 2022

Conference

Conference22nd IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2022
Country/TerritoryTaiwan
CityVirtual, Online
Period7/11/229/11/22

Keywords

  • biomarkers
  • precision medicine
  • quantum kernel-based classifier
  • quantum machine learning
  • tumor metastasis

Fingerprint

Dive into the research topics of 'Classification of Tumor Metastasis Data by Using Quantum kernel-based Algorithms'. Together they form a unique fingerprint.

Cite this