Fourier transform infrared spectroscopic marker of glioblastoma obtained from machine learning and changes in the spectra

Bartłomiej Tołpa,Joanna Depciuch,Paweł Jakubczyk,Wiesław Paja, Krzysztof Pancerz,Agnieszka Wosiak,Ewa Kaznowska,Agnieszka Gala-Błądzińska,Józef Cebulski

Photodiagnosis and Photodynamic Therapy（2023）

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摘要

•Features of absorbance at specific wavenumbers between 1053 cm−1 and 1056 cm−1 as well as between 1564 cm−1 and 1588 cm−1 are characteristic for glioblastoma tissues.•α-helix structure in the control tissues was around 51%, while in cancer 30%.•Accuracy was 100% for k nearest neighbors and support vector machine algorithms.

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关键词

Glioblastoma,Fourier transform infrared spectroscopy,Principal component analysis,Machine learning,Spectroscopic marker

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