Recognition of breast cancer subtypes using FTIR hyperspectral data
dc.contributor.author | FAROOQ, SAJID | |
dc.contributor.author | DEL-VALLE, MATHEUS | |
dc.contributor.author | SANTOS, SOFIA N. dos | |
dc.contributor.author | BERNARDES, EMERSON S. | |
dc.contributor.author | ZEZELL, DENISE M. | |
dc.coverage | Internacional | |
dc.date.accessioned | 2024-04-15T13:58:36Z | |
dc.date.available | 2024-04-15T13:58:36Z | |
dc.date.issued | 2024 | |
dc.description.abstract | Fourier -transform infrared spectroscopy (FTIR) is a powerful, non-destructive, highly sensitive and a promising analytical technique to provide spectrochemical signatures of biological samples, where markers like carbohydrates, proteins, and phosphate groups of DNA can be recognized in biological micro -environment. However, method of measurements of large cells need an excessive time to achieve high quality images, making its clinical use difficult due to speed of data -acquisition and lack of optimized computational procedures. To address such challenges, Machine Learning (ML) based technologies can assist to assess an accurate prognostication of breast cancer (BC) subtypes with high performance. Here, we applied FTIR spectroscopy to identify breast cancer subtypes in order to differentiate between luminal (BT474) and nonluminal (SKBR3) molecular subtypes. For this reason, we tested multivariate classification technique to extract feature information employing three -dimension (3D) -discriminant analysis approach based on 3D -principle component analysis -linear discriminant analysis (3D-PCA-LDA) and 3D -principal component analysis -quadratic discriminant analysis (3D-PCA-QDA), showing an improvement in sensitivity (98%), specificity (94%) and accuracy (98%) parameters compared to conventional unfolded methods. Our results evidence that 3D-PCALDA and 3D-PCA-QDA are potential tools for discriminant analysis of hyperspectral dataset to obtain superior classification assessment. | |
dc.description.sponsorship | Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) | |
dc.description.sponsorship | Coordenação de Aperfeiçoamento de Pessoal de Ensino Superior (CAPES) | |
dc.description.sponsorship | Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) | |
dc.description.sponsorshipID | CNPq: INCT-INTERAS 406761/2022-1; INCT-INFO 465763/2014-6; Sisfoton 440228/2021-2; PQ 314517/2021-9 | |
dc.description.sponsorshipID | CAPES: 001 | |
dc.description.sponsorshipID | FAPESP: 17/50332-0; 21/00633-0 | |
dc.format.extent | 1-8 | |
dc.identifier.citation | FAROOQ, SAJID; DEL-VALLE, MATHEUS; SANTOS, SOFIA N. dos; BERNARDES, EMERSON S.; ZEZELL, DENISE M. Recognition of breast cancer subtypes using FTIR hyperspectral data. <b>Spectrochimica Acta Part A</b>, v. 310, p. 1-8, 2024. DOI: <a href="https://dx.doi.org/10.1016/j.saa.2024.123941">10.1016/j.saa.2024.123941</a>. Disponível em: https://repositorio.ipen.br/handle/123456789/48043. | |
dc.identifier.doi | 10.1016/j.saa.2024.123941 | |
dc.identifier.issn | 1386-1425 | |
dc.identifier.orcid | https://orcid.org/0000-0002-0029-7313 | |
dc.identifier.orcid | https://orcid.org/0000-0001-7404-9606 | |
dc.identifier.percentilfi | 89.8 | |
dc.identifier.percentilfiCiteScore | 85.50 | |
dc.identifier.uri | https://repositorio.ipen.br/handle/123456789/48043 | |
dc.identifier.vol | 310 | |
dc.relation.ispartof | Spectrochimica Acta Part A | |
dc.rights | openAccess | |
dc.subject | fourier transform spectrometers | |
dc.subject | fourier transformation | |
dc.subject | infrared spectra | |
dc.subject | neoplasms | |
dc.subject | mammary glands | |
dc.title | Recognition of breast cancer subtypes using FTIR hyperspectral data | |
dc.type | Artigo de periódico | |
dspace.entity.type | Publication | |
ipen.autor | SAJID FAROOQ | |
ipen.autor | MATHEUS DEL VALLE | |
ipen.autor | SOFIA NASCIMENTO DOS SANTOS | |
ipen.autor | EMERSON SOARES BERNARDES | |
ipen.autor | DENISE MARIA ZEZELL | |
ipen.codigoautor | 15722 | |
ipen.codigoautor | 15209 | |
ipen.codigoautor | 14464 | |
ipen.codigoautor | 12099 | |
ipen.codigoautor | 693 | |
ipen.contributor.ipenauthor | SAJID FAROOQ | |
ipen.contributor.ipenauthor | MATHEUS DEL VALLE | |
ipen.contributor.ipenauthor | SOFIA NASCIMENTO DOS SANTOS | |
ipen.contributor.ipenauthor | EMERSON SOARES BERNARDES | |
ipen.contributor.ipenauthor | DENISE MARIA ZEZELL | |
ipen.identifier.fi | 4.3 | |
ipen.identifier.fiCiteScore | 8.4 | |
ipen.identifier.ipendoc | 30368 | |
ipen.identifier.iwos | WoS | |
ipen.range.fi | 3.000 - 4.499 | |
ipen.range.percentilfi | 75.00 - 100.00 | |
ipen.type.genre | Artigo | |
relation.isAuthorOfPublication | 60d3fba4-40e1-482c-9eda-4530bc63fecb | |
relation.isAuthorOfPublication | fdd01116-8cc4-406a-aafb-606941dc28dc | |
relation.isAuthorOfPublication | ab78881a-78eb-42be-a463-aaf80e70de3d | |
relation.isAuthorOfPublication | 8115c8bd-822c-4f5a-9f49-3c12570ed40a | |
relation.isAuthorOfPublication | a565f8ad-3432-4891-98c0-a587f497db21 | |
relation.isAuthorOfPublication.latestForDiscovery | 60d3fba4-40e1-482c-9eda-4530bc63fecb | |
sigepi.autor.atividade | SAJID FAROOQ:15722:920:S | |
sigepi.autor.atividade | MATHEUS DEL VALLE:15209:920:N | |
sigepi.autor.atividade | SOFIA NASCIMENTO DOS SANTOS:14464:110:N | |
sigepi.autor.atividade | EMERSON SOARES BERNARDES:12099:110:N | |
sigepi.autor.atividade | DENISE MARIA ZEZELL:693:920:N |