Using Machine Learning for Classification of Cancer Cells from Raman Spectroscopy

Lerina Aversano, Mario Bernardi, Vincenzo Calgano, Marta Cimitile, Concetta Esposito, Martina Iammarino, Marco Pisco, Sara Spaziani, Chiara Verdone

2022

Abstract

Since cancer represents one of the leading causes of death worldwide, the development of approaches capable of discerning healthy from diseased cells would be of fundamental importance to support diagnostic and screening techniques. Raman spectroscopy is the most effective molecular analysis technique currently available and provides information on the molecular composition, bonds, chemical environment, phase, and crystalline structure of the samples under examination. This work exploits a combination of Raman spectroscopy and machine learning models to discriminate patients’ liver cells between tumor and non-tumor. The research uses real patient data, provided by the Center for Nanophotonics and Optoelectronics for Human Health (CNOS), which analyzed the cells of a patient with liver cancer. Specifically, the dataset has been built through a long data collection process, which first involved the analysis of the cells with Raman spectroscopy and then the training of two classifiers, Decision Tree and Random Forest. The results show good performance for the trained classifiers, especially those relating to the Random Forest, which reaches an accuracy of 90%.

Paper Citation

in Harvard Style

Aversano L., Bernardi M., Calgano V., Cimitile M., Esposito C., Iammarino M., Pisco M., Spaziani S. and Verdone C. (2022). Using Machine Learning for Classification of Cancer Cells from Raman Spectroscopy. In Proceedings of the 3rd International Conference on Deep Learning Theory and Applications - Volume 1: DeLTA, ISBN 978-989-758-584-5, pages 15-24. DOI: 10.5220/0011142600003277

in Bibtex Style

@conference{delta22,
author={Lerina Aversano and Mario Bernardi and Vincenzo Calgano and Marta Cimitile and Concetta Esposito and Martina Iammarino and Marco Pisco and Sara Spaziani and Chiara Verdone},
title={Using Machine Learning for Classification of Cancer Cells from Raman Spectroscopy},
booktitle={Proceedings of the 3rd International Conference on Deep Learning Theory and Applications - Volume 1: DeLTA,},
year={2022},
pages={15-24},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011142600003277},
isbn={978-989-758-584-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Deep Learning Theory and Applications - Volume 1: DeLTA,
TI - Using Machine Learning for Classification of Cancer Cells from Raman Spectroscopy
SN - 978-989-758-584-5
AU - Aversano L.
AU - Bernardi M.
AU - Calgano V.
AU - Cimitile M.
AU - Esposito C.
AU - Iammarino M.
AU - Pisco M.
AU - Spaziani S.
AU - Verdone C.
PY - 2022
SP - 15
EP - 24
DO - 10.5220/0011142600003277