PM08: LEARNING PROGNOSIS CLASSIFIER (LPC) BASED ON HYBRID ANN-FUZZY
Functions & goal
The third subsystem-LPC (Figure 1) uses inputs from: (a) biomarkers (discriminators genes), (b) prognostic factors (optional markers), (c) medical statistics data, and (d) success of one treatment phase (therapy).
Applying Radial bases networks, ANN, LVQ and ensemble methods, the subsystem generates an output signal called the predictive survival prognosis. The subsystem is capable of incorporating multiple factors for prediction of medical prognosis including: cure prediction, unforeseen complications, disease recurrence, level of functions, length of hospital stay, and patient survival. The LPC is the most responsible subsystem in estimating the patient survival.
Figure 1. LPC structure