Method and apparatus for training and operating a neural network for detecting breast cancer

L. Parra, Paul Sajda, C. Spence

A method and apparatus for training and operating a neural network using gated data. The neural network is a mixture of experts that performs “soft” partitioning of a network of experts. In a specific embodiment, the technique is used to detect malignancy by analyzing skin surface potential data. In particular, the invention uses certain patient information, such as menstrual cycle information, to “gate” the expert output data into particular populations, i.e., the network is soft partitioned into the populations. An Expectation-Maximization (EM) routine is used to train the neural network using known patient information, known measured skin potential data and correct diagnosis for the particular training data and patient information. Once trained, the neural network parameters are used in a classifier for predicting breast cancer malignancy when given the patient information and skin potentials of other patients.

Accepted 27 March 2001
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