Analysis of Raman spectroscopy data with algorithms based on paraconsistent logic for characterization of skin cancer lesions

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art_GARCIA_Analysis_of_Raman_spectroscopy_data_with_algorithms_based_2019.PDF (1.78 MB)
Citações na Scopus
14
Tipo de produção
article
Data de publicação
2019
DOI
Scopus
Web of Science
Título da Revista
ISSN da Revista
Título do Volume
Editora
ELSEVIER
Autores
GARCIA, Dorotea Vilanova
SILVA FILHO, Joao Inacio da
SILVEIRA JR., Landulfo
PACHECO, Marcos Tadeu Tavares
ABE, Jair Minoro
CARVALHO JR., Arnaldo
BLOS, Mauricio Fontoura
MARIO, Mauricio Conceicao
Citação
VIBRATIONAL SPECTROSCOPY, v.103, article ID 102929, 10p, 2019
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
Analysis of the Raman data to obtain results in discrimination models is usually done with multivariate statistics based on principal component analysis (PCA). In this work, we present a technique based on a non-classical logic called paraconsistent logic (PL). The aim of this work is to use computational procedures capable of generating efficient expert systems to discriminate cutaneous tissue samples obtained by Raman spectroscopy. First, a set of algorithms originating from PL is presented, and then its application in discrimination analyses is described; the discrimination analysis was conducted using a database of skin tissue samples obtained ex vivo by Raman spectroscopy of spectrum range of 400-1800 cm(-1) wavelengths. Data processing, pattern creation, and comparisons were performed using the set of paraconsistent algorithms (SPA-PAL2v). The total number of samples was divided into four histopathological groups, with 115 spectra of basal cell carcinoma (BCC), 21 spectra of squamous cell carcinoma (SCC), 57 spectra of actinic keratosis (AK), and 30 normal skin (NO) spectra. An arrangement type was created for this study, and the samples were randomly selected and analyzed, and the NO group was compared with the group of non-melanoma cancer lesions (BCC + SCC) and the AK tumor lesion. Two analyses were performed. The first (SPA-PAL2v) Mode 1 (no cross-validation) achieved 76% of hits, and the second (SPA-PAL2v) Mode 2 (with cross-validation) achieved 75.78% of hits. These results were compared with discrimination using PCA statistical methods (PCA/DA) and presented superior percentages of hits, which proves the robustness of the SPA-PAL2v, confirming its potential for Raman spectrum data analysis.
Palavras-chave
Raman spectroscopy, Algorithms, Skin cancer, Paraconsistent annotated logic, Medical diagnosis
URI
https://observatorio.fm.usp.br/handle/OPI/34553
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Coleções
Artigos e Materiais de Revistas Científicas - FM/MPT
Artigos e Materiais de Revistas Científicas - LIM/22
Artigos e Materiais de Revistas Científicas - ODS/03