combines transformational and hierarchical adaptation techniques with artificial neural
networks (ANN's) and certainty factors (CF's). The model consists of a hierarchy of three
phases, which simulates the expert doctor phases of cancer diagnosis. Each phase uses a
single ANN to learn the adaptation knowledge to perform the main adaptation task. The
model has been tested with 820 thyroid cancered patient cases. Cross-validation test has …