Systems and methods for response prediction to chemotherapy in high grade bladder cancer

Abstract

Contemplated systems and methods allow for prediction of chemotherapy outcome for patients diagnosed with high-grade bladder cancer. In particularly preferred aspects, the prediction is performed using a model based on machine learning wherein the model has a minimum predetermined accuracy gain and wherein a thusly identified model provides the identity and weight factors for omics data used in the outcome prediction.

Description

[0001] This application claims priority to U.S. Provisional Application Serial No. 62 / 105697 filed 1 / 20 / 15 and U.S. Provisional Application Serial No. 62 / 127546 filed 3 / 3 / 15, which are incorporated herein by reference . technical field [0002] The field of the invention is systems and methods for in silico prediction of treatment outcome of chemotherapy in bladder cancer. Background technique [0003] The Background Description includes information useful in understanding the present invention. It is not an admission that any information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art. [0004] All publications herein are herein incorporated by reference as if each individual publication or patent application was specifically and individually indicated to be incorporated by reference. Where the definition or usage of a term in an incorporated reference is inconsistent o...

AI Technical Summary

Problems solved by technology

Although Cesano discusses the selection of suitable models, these models, once selected, still suffer from the same inherent bias difficulties

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