Application of a two-stage fuzzy neural network to a prostate cancer prognosis system

Conclusions The proposed two-stage FNN is able to learn the relationship between the clinical features and the prognosis of prostate cancer. Once the clinical data are known, the prognosis of prostate cancer patient can be predicted. Furthermore, unlike artificial neural networks, it is much easier to interpret the training results of the proposed network since they are in the form of fuzzy IF-THEN rules. These rules are very important for medical doctors. This can dramatically assist medical doctors to make decisions. Graphical abstract
Source: Artificial Intelligence in Medicine - Category: Bioinformatics Source Type: research