Chih-Wen Kan

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We report the results of an oral cavity pilot clinical trial to detect early precancer and cancer using a fiber optic probe with obliquely oriented collection fibers that preferentially probe local tissue morphology and heterogeneity using oblique polarized reflectance spectroscopy (OPRS). We extract epithelial cell nuclear sizes and 10 spectral features.(More)
Assessment of classifier performance is critical for fair comparison of methods, including considering alternative models or parameters during system design. The assessment must not only provide meaningful data on the classifier efficacy, but it must do so in a concise and clear manner. For two-class classification problems, receiver operating(More)
We compared the use of linear discriminant analysis and an artificial neural network for classifying optical spectral measurements of oral sites. Consistent with studies of optical spectroscopy for diagnosis of other forms of cancer, our results suggest that a non-linear classifier may be warranted. Our study also demonstrated that the classifiers were(More)
PURPOSE The authors present a novel technique based on histogram shaping to reduce the variability in the output and (sensitivity, specificity) pairs of pattern classifiers with identical ROC curves, but differently distributed outputs. METHODS The authors identify different sources of variability in the output of linear pattern classifiers with identical(More)
Assessment of classifier performance is critical for fair comparison of methods, including considering alternative models or parameters during system design. The assessment must not only provide meaningful data on the classifier efficacy, but it must do so in a concise and clear manner. For two-class classification problems, receiver operating(More)
In biomarker identification using mass spectrometry, normalization makes it possible to compare mass spectra obtained from different samples. However, the relative influence of different normalization methods is an unexplored topic. In this study, we compared the most widely used normalization methods in a systemic manner to investigate impact of(More)
We present an approach to adaptively adjust the spectral window sizes for optical spectra feature extraction. Previous studies extracted features from spectral windows of a fixed width. In our algorithm, piecewise linear regression is used to adaptively adjust the window sizes to find the maximum window size with reasonable linear fit with the spectrum.(More)
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