Recent application of Raman spectroscopy in tumor diagnosis: from conventional methods to artificial intelligence fusion

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Table 1 Raman spectroscopy for tumor diagnosis

Sample	Methods	Diagnosis	Ref
Tissue	PLS-DA	Brain cancer	[33]
	PCA-LDA		[36]
	PCA		[37, 38]
	PCA-QDA		[39]
	PLS-DA	Breast cancer	[35]
	PCA-LDA, PLS-DA		[41]
	PCA-LDA		[42, 43]
	PCA-LDA	Liver cancer	[47]
	KCA, PCA	Lung cancer	[48]
	PLS-DA		[49]
	PCA-LDA		[50]
	PCA-LDA, PLS-LDA	Oral cancer	[51]
	PCA-LDA	Rectal cancer	[55]
	PLS-DA	Skin cancer	[56]
	PLS-DA	Skin cancer	[57]
	Peak comparison	Ovarian cancer	[53]
Cell	PCA	Breast cancer	[44]
	PCA-LDA	Breast cancer	[58]
	PCA-LDA	Colorectal cancer	[58]
	PCA	Colorectal cancer	[59]
	PCA-QDA	Lymphoma	[60]
Serum	PCA-LDA	Brain cancer	[40]
	GA-QDA	Esophageal cancer	[45]
	PLS-DA	Lung cancer	[49]
Saliva	GA-QDA	Esophageal cancer	[45]
Saliva	PCA-LDA	Oral cancer	[52]
Plasma	GA-QDA	Esophageal cancer	[45]
Urine	GA-QDA	Esophageal cancer	[45]
Bone marrow supernatants	PLS-DA	Leukemia	[46]
Tissue	SVM	Brain cancer	[61]
	RF, BT	Brain cancer	[62]
	SVM	Breast cancer	[63]
	KNN	Cervical cancer	[64]
	SVM, KNN, RF, etc	Kidney cancer	[65]
	SVM	Kidney cancer	[66]
	SVM	Meningiomas	[67]
	1D-CNN	Bone tumors	[68, 69]
	1D-CNN	Breast cancer	[70]
	1D/2D-CNN	Chondrogenic Tumor	[71]
	1D-CNN	Colon cancer	[72]
	1D-CNN	Laryngeal cancer	[73]
	2D-CNN	Lung cancer	[74, 75]
	1D/2D-CNN	Lung cancer	[76]
	1D-CNN	Oral cancer	[77, 78]
	1D/2D-CNN	Pancreatic cancer	[79]
	1D-CNN	Skin cancer	[80]
Cell	SVM, RF	Bladder cancer	[81]
	SVM	Breast cancer	[82]
	RF	Breast cancer	[83]
	SVM	Central nervous system tumor	[84]
	SVM	Osteosarcoma	[69]
	KNN, SVM	Pancreatic cancer	[85]
Serum	RF, SVM	Brain cancer	[86]
	BT	Colorectal cancer	[87]
	SVM	Ovarian cancer	[88]
	SVM, KNN	Pancreatic cancer	[89]
	CNN	Brain cancer	[90]
	RNN, CNN	Brain cancer	[91]
	RNN, CNN	Lung cancer	[91]
Plasma	SVM	Ovarian cancer	[88]
Urine	SVM	Ovarian cancer	[88]

BT Boosted tree, CNN Convolutional neural network, GA Genetic algorithm, KCA K-means cluster analysis, KNN K-nearest neighbors, LDA Linear discriminate analysis, PCA Principal component analysis, PLS-DA Partial least squares discriminant analysis, QDA Quadratic discriminant analysis, RF Random forest, RNN Recursive neural network, SVM Support-vector machines