Adaptive Neuro-Fuzzy Inference System For Medical Image Classification -A Review
Lilis Yuningsih, Roy Rudolf Huizen, Gede Angga Pradipta, Putu Desiana Wulaning Ayu, Dandy Pramana Hostiadi · 2022 4th International Conference on Cybernetics and Intelligent System (ICORIS) · 2022
Medical image has now been widely used as the object in research particularly in artificial intelligent. Classification automation on medical image can assist to provide information or as the second opinion for the paramedics in doing a medical action and giving a diagnosis for the patients. One of the algorithms as the classifier is the adaptive neuro-fuzzy inference system (ANFIS) method - a hybrid method combining the fuzzy logic and neural network. ANFIS algorithm is the fuzzy inference system (FIS) implemented into the adaptive fuzzy neural network framework. This method combines the explicit knowledge as the representation from FIS and learning ability from the artificial neural network. This paper presents the discussion and the review of the adaptive neuro-fuzzy inference system (ANFIS) algorithm as the classifier in medical image classification. A number of research that have been conducted on the medical image object are evaluated and discussed in terms of their strengths and weaknesses.