Paulo Vitor De Campos Souza, Yu-Kai Wang, Edwin Lughofer,
"Knowledge extraction about patients surviving breast cancer treatment through an autonomous fuzzy neural network"
: Proceedings of the 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Serie Proceedings of the FUZZ-IEEE 2020 Conference, IEEE Press, 2020
Knowledge extraction about patients surviving breast cancer treatment through an autonomous fuzzy neural network
Sprache des Titels:
Proceedings of the 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)
Cancer treatment is extremely aggressive and, in addition to causing considerable discomfort, can lead to death. Therefore, identifying aspects related to treatment assertiveness may be efficient for reducing the mortality rate of cancer patients. This paper seeks to identify the prognosis of cancer treatment survival through hybrid techniques based on the autonomous fuzzification process and artificial neural networks. The public dataset on cancer mortality is the source for conducting treatment assertiveness rating tests. The hybrid model had its results compared to other models present in the pattern classification literature with superior accuracy and identification of people likely to survive treatment (90.46%), and the fuzzy rules obtained with the execution of the model corroborate the high assertiveness of the model, even surpassing state of the art for the theme.