Tissue Classification Method for Diagnosis and Treatment of Tumors

The present invention discloses an informational computation method for classifying objects Specifically, the invention is a system, method, and computer-readable media for classifying tumors using a nonparametric statistical classifier in conjunction with an artificial neural network. The invention classifies unknown tumor types based on the correlation of unknown tumor's genetic expression compared to the genetic expression of know tumor types by first performing a nonparametric statistical analysis on the know data, training a artificial neural network with the known data, and then inputting the unknown tumor data into the neural network to calculate the probability that the sample tumor is a member of a class of tumors. By using a statistical classifier in conjunction with a neural network, the invention classifies unknown tumors more accurately then conventionally possible. Advantageously, by using a variety of tumor genetic expression data sets, including both published data sets and generated data sets, a tumor classifier, robust and accurate enough for clinical application, is provided.

Attached files:


Patents:
US 20,110,106,740

Inventor(s): YEATMAN TIMOTHY J [US]; BLOOM GREG [US]

Type of Offer: Licensing



« More Medical Patents
« More Diagnostic Patents

---