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A general multivariate statistical algorithm has been developed to analyze the diagnostic content of cervical tissue fluorescence spectra acquired in vivo.

The primary steps of the algorithm are to: (1) preprocess the data to reduce inter‐patient and intra‐patient variation of tissue spectra within a diagnostic category, without a priori information, (2) dimensionally reduce the preprocessed fluorescence emission spectrum with minimal information loss and use it to select the minimum number of the original emission variables of the fluorescence spectrum required to achieve classification with negligible decrease in predictive ability, and (3) assign a posterior probability to the diagnosis of each sample, so that samples with relative uncertain diagnosis can be reevaluated by a clinician. The algorithm was tested retrospectively and prospectively on cervical tissue spectra …