Fig. 5
From: Early cancer detection by serum biomolecular fingerprinting spectroscopy with machine learning
Construction of cancer-related database at bond level by SERS-AICS. A The original spectral data of 1465 dimensions of serum with no obvious specificity can obtain 50 valid dimensions with the best specificity after the correlation between dimensions is judged by the covariance matrix, which related to the molecular bond energy information in serum associated with cancer or disease. B Heatmap of the covariance matrix formed on 30 true dimensions between 600 and 623.77051 cm−1 using peak data for lung cancer and healthy controls, the dimension at 600 cm−1 and 618.03276 cm−1 showed the minimal correlation. C List of common valid dimensions of different cancers compared with normal control group or common disease