Infrared micro-spectroscopy coupled with multivariate and machine learning techniques for cancer classification in tissue: a comparison of classification method, performance, and pre-processing technique-Reference-Cited by-同舟云学术

Infrared micro-spectroscopy coupled with multivariate and machine learning techniques for cancer classification in tissue: a comparison of classification method, performance, and pre-processing technique

Published:2022 Issue:16 Volume:147 Page:3709-3722
ISSN:0003-2654
Container-title:The Analyst
language:en
Short-container-title:Analyst

Author:

Ferguson Dougal¹²^ORCID,Henderson Alex¹²^ORCID,McInnes Elizabeth F.³,Lind Rob³,Wildenhain Jan³^ORCID,Gardner Peter¹²^ORCID

Affiliation:

1. Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK

2. Department of Chemical Engineering and Analytical Science, School of Engineering, University of Manchester, Oxford Road, Manchester, M13 9PL, UK

3. Syngenta, International Research Centre, Jealotts Hill, Bracknell, RG42 6EY, UK

Abstract

A meta-analysis of various multivariate/Machine Learning (ML) classifiers trained on IR Micro-spectroscopy tissue datasets for cancer classification are directly compared using a calculated F1-Score metric alongside study pre-processing techniques.

Funder

Engineering and Physical Sciences Research Council

Syngenta Foundation for Sustainable Agriculture

University of Manchester

Publisher

Royal Society of Chemistry (RSC)

Subject

Electrochemistry,Spectroscopy,Environmental Chemistry,Biochemistry,Analytical Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2022/AN/D2AN00775D

Reference63 articles.

1. B. C.Smith , Fundamentals of Fourier transform infrared spectroscopy , CRC press , 2011