Method for integrating and fusing heterogeneous data types to perform predictive analysis

A method for predicting the onset of a disease, the method comprising:

• receiving patient data including a first input sample of a first data type and a second input sample of a second data type, the first data type including discrete data and the second data type including continuous data;
• receiving a training data set including a first plurality of training samples of the first data type and a corresponding second plurality of training samples of the second data type;
• providing the first input sample and the first plurality of training samples to a first kernel function of a multiple kernel decision function;
• providing the second input sample and the second plurality of training samples to a second kernel function of the multiple kernel decision function;
• performing at least one calculation using the multiple kernel decision function to produce at least one result;
• and
• determining a probability of whether the patient data indicates that the patient will develop the disease based on the at least one result of the multiple kernel decision function.

A method for predicting the probability of an event comprising:

• receiving a plurality of input samples, each input sample of the plurality of input samples having a data type of a plurality of data types, the data types including quantitative data, discrete data, continuous data, and categorical data;
• receiving a training data set including a plurality of training samples, each of the plurality of training samples having a data type of the plurality of data types;
• providing each input sample and each respective training sample with the same data type of the plurality of training samples to a corresponding kernel function of a multiple kernel decision function having a plurality of kernel functions;
• performing at least one calculation using the multiple kernel decision function to produce at least one result;
• and
• determining a probability of an event based on the at least one result of the multiple kernel decision function.