Pancreatic cancer detection with self-expanding ART fuzzy neural network online training
Keywords:
Pancreatic Ductal Adenocarcinoma, Adaptive Resonance Theory, Machine Learning, Fuzzy ARTAbstract
Pancreatic cancer is one of the most aggressive cancers and has a high mortality rate due to late diagnosis, as the first symptoms usually appear when it is at an advanced stage, making resection of the tumor impossible. With the aim of assisting in early diagnosis, this article presents the results obtained using urinary biomarkers to detect pancreatic cancer. The Self-Expanding ART Fuzzy Neural Network Online Training achieved superior results compared to other machine learning models in the different types of proposed classifications. This makes the use of our method promising to improve the diagnosis of pancreatic cancer compared to the methods still used and contributing to precision medicine.
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Copyright (c) 2024 André Luiz Caliari Costa, Reginaldo José da Silva, Mara Lúcia Martins Lopes, Angela Leite Moreno

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.