Towards Cancer Patients Classification Using Liquid Biopsy - Publication - Bridge of Knowledge

Search

Towards Cancer Patients Classification Using Liquid Biopsy

Abstract

Liquid biopsy is a useful, minimally invasive diagnostic and monitoring tool for cancer disease. Yet, developing accurate methods, given the potentially large number of input features, and usually small datasets size remains very challenging. Recently, a novel feature parameterization based on the RNA-sequenced platelet data which uses the biological knowledge from the Kyoto Encyclopedia of Genes and Genomes, combined with a classifier based on the Convolutional Neural Network (CNN), allowed significantly improving the classification accuracy. In this work, we take a closer look at this approach and find that similar results can be obtained using significantly smaller models. Additionally, competitive results were achieved using gradient boosting. Since it has another advantage of adding interpretability to the model, we further analyze it in this work.

Citations

  • 4

    CrossRef

  • 0

    Web of Science

  • 2

    Scopus

Cite as

Full text

full text is not available in portal

Keywords

Details

Category:
Monographic publication
Type:
rozdział, artykuł w książce - dziele zbiorowym /podręczniku w języku o zasięgu międzynarodowym
Language:
English
Publication year:
2021
Bibliographic description:
Cygert S., Górski F., Juszczyk P., Lewalski S., Pastuszak K., Czyżewski A., Supernat A.: Towards Cancer Patients Classification Using Liquid Biopsy// Predictive Intelligence in Medicine/ : , 2021, s.221-230
DOI:
Digital Object Identifier (open in new tab) 10.1007/978-3-030-87602-9_21
Sources of funding:
  • Medical University of Gdańsk statutory work (ST-23, 02-0023/07)
  • SONATA grant of the National Science Centre (2018/31/D/NZ5/01263)
  • Project -
  • Statutory activity/subsidy
Verified by:
Gdańsk University of Technology

seen 198 times

Recommended for you

Meta Tags