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AssigneeThe Research Foundation of State University of New York
InventorsThomas Szyperski, Christopher Andrews, Dinesh K. Sukumaran, Adekunle Odunsi
Estimating the term…
A method for generating a model for epithelial ovarian cancer is presented, comprising the steps of obtaining a mass spectrum for each of a plurality of samples, segmenting each of the mass spectra into “bins,” and determining a plurality of relationships between two or more bins. One are more statistically significant factors are identified according to the determined plurality of relationships, and a predictive model is generated as a function of the one or more identified factors. A method of the present invention may further comprise the step of obtaining one or more nuclear magnetic resonance spectra of each of the samples, which are segmented into a plurality of bins. Combinations of mass spectra and NMR spectra may be used to determine the plurality of relationships. In other embodiments, methods for identifying the presence of EOC indicated by a biological sample of an individual are presented.
A method of generating a predictive model for diagnosing early-stage epithelial ovarian cancer using a plurality of biological samples, each sample being taken from a different individual having a known disease state of either diseased (“EOC”), benign ovarian cyst (“benign”), or healthy (“healthy”), the method comprising the steps of:
A method of identifying the presence or absence of early-stage epithelial ovarian cancer (“EOC”) indicated by a biological sample, the method comprising the steps of:
Dependencies are inferred from the claim text.