… In future studies, we aim to investigate whether similar classification performance metrics
can be obtained for in vivo colorectal tissues and build instruments for automated CRC …

… We considered four classification algorithms (logistic regression, support vector … learning
methods [14], such as neural networks (NNs), support vector machines (SVMs), k nearest …

… -to-noise ratio before the suitable spectra were decomposed and classified using a
combination of principal component analysis and a support vector machine, respectively. After five-…

… Fourier transform infrared (FTIR) spectroscopic imaging of colon biopsy tissues in
transmission combined with machine learning for the classification of different stages of …

… Raman spectroscopy with support vector machine (SVM) model and deep belief network (DBN)
model. The serum Raman spectra … tissue from cancerous tissue by near-infrared Raman …

… involved PCA combined with k-means clustering, as well as the employment of ML based
models for the classification between spectra from normal and cancerous specimens. PCA …

… Raman spectroscopy is suitable for the diagnosis of … in vivo Raman spectra of human
gastrointestinal tissue were … -optic-coupled Raman spectroscopy for disease classification during …

… Support vector machines … They studied suppression effect of anticancer drug 5-fluorouracil
(5-FU) in 3 colon tumor model mice. PCA clearly classified Raman spectra from mouse before …

… The 566 cm −1 peak and 650 cm −1 peak in the serum Raman spectrum were classified
as Tryptophan and Glucose, respectively. They were significantly up-regulated in the sera of …

… Raman spectroscopic measurements were used as a label-free, fast minimally invasive
screening technique. Just using Raman scattering spectra of … group were classified as healthy. …