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. 2014 Mar;58(3):1302–1314. doi: 10.1128/AAC.02098-13

TABLE 5.

Impact of Raman spectra normalization methods

Antibiotic Class % Correct predictiona
No normalization Vector normalization 1,003 cm−1 1,445–1,455 cm−1 2,900–3,100 cm−1
Chloramphenicol PROT 46.9 93.9 81.6 89.8 89.8
Clindamycin PROT 23.6 83.6 61.8 58.2 87.3
Gentamicin PROT 16.0 69.3 60.0 36.0 73.3
Kanamycin PROT 13.0 63.0 40.7 37.0 61.1
Streptomycin PROT 30.6 71.4 71.4 71.4 71.4
Tetracycline PROT 11.3 75.5 34.0 37.7 67.9
Ciprofloxacin DNA 62.3 47.8 47.8 36.2 34.8
Nalidixic acid DNA 88.1 67.8 52.5 71.2 67.8
Trimethoprim DNA 81.1 64.2 64.2 67.9 62.3
Amoxicillin CW 63.9 41.0 57.4 42.6 42.6
Ampicillin CW 0.0 0.0 0.0 0.0 0.0
Cefotaxime CW 61.4 38.6 40.4 40.4 38.6
Rifampin RNA 0.0 3.5 3.5 3.5 1.8
Rifapentine RNA 78.0 66.1 59.3 72.9 66.1
Rifaximin RNA 80.0 80.0 86.2 83.1 78.5
Overall accuracy (%) 43.8 57.7 50.7 49.9 56.2
Randomb 20.0 20.0 20.0 20.0 20.0
a

Percentage of correct PC-DA prediction of antibiotic class for the spectra representing each antibiotic excluded from the training data set. Raman signal intensities were normalized using vector normalization and with respect to the signal intensity of the phenylalanine band at 1,003 cm−1, the signal intensity of the C-H band at 1,450 cm−1, and the signal intensity of the C-H stretching vibration region at 2,900 to 3,100 cm−1.

b

The probability of correct classifications by random assignment.