Breast Cancer Prediction Using Neuro-Fuzzy Systems | IEEE Conference Publication | IEEE Xplore

Breast Cancer Prediction Using Neuro-Fuzzy Systems


Abstract:

Cancer is one of the most dangerous diseases in the world. The scientists are in pursue of finding better methods of detecting the various type of cancerous cell formatio...Show More

Abstract:

Cancer is one of the most dangerous diseases in the world. The scientists are in pursue of finding better methods of detecting the various type of cancerous cell formations in the tissues. The purpose of this work is to develop a more accurate prediction model to identify breast cancer. In this work, Genetic algorithm (GA) based trained recurrent fuzzy neural network (RFNN) and adaptive neuro-fuzzy inference system (ANFIS) are used on the dataset provided by the UCI Machine Learning Repository. In this data set there are 9 quantitative attributes and a label that clinical features are observed or measured for 116 participants. The dataset separated into two sub-sets; one for training (81 instances) and one for testing (35 instances). For 8 different combinations of variables 8 different GA based trained RFNN and 8 different ANFIS were designed. The sensitivity, specificity, precision, F-score, probability of the misclassification error (PME) and accuracy of the training set, testing set and overall performances of the models were analyzed. The RFNN with 9 variables gave the highest overall accuracy (88.79%). The overall results showed that the GA based trained RFNN outperformed both ANFIS and other previous works that used the same dataset.
Date of Conference: 14-16 April 2020
Date Added to IEEE Xplore: 28 May 2020
ISBN Information:
Conference Location: Antalya, Turkey
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Cites in Papers - |

Cites in Papers - IEEE (2)

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1.
Rahul Mishra, Archana Mantri, "Cancer Detection in Highly Dense Breasts using Coherently Focused Time versa Microwave Imaging and Using Warm-Boot Random Forest Classifier", 2023 IEEE International Conference on Integrated Circuits and Communication Systems (ICICACS), pp.1-5, 2023.
2.
Mayank Agrawal, Vinod Jain, "Prediction of Breast Cancer based on Various Medical Symptoms Using Machine Learning Algorithms", 2022 6th International Conference on Trends in Electronics and Informatics (ICOEI), pp.1242-1245, 2022.

Cites in Papers - Other Publishers (3)

1.
Jie Zhang, Xiaohong Zhang, Xiaoyan Quan, Xiaoxiao Fu, Jinlian Chai, "Research on the Prediction Model of off Campus Training Base in Fuzzy Neural Network Algorithm", Application of Big Data, Blockchain, and Internet of Things for Education Informatization, vol.582, pp.232, 2024.
2.
Semih Latif İPEK, Dilek GÖKTÜRK, "Evaluation of artificial neural network and adaptive-network-based fuzzy inference system for ovarian and lung cancer prediction", Journal of Health Sciences and Medicine, vol.7, no.1, pp.80, 2024.
3.
Umit Ilhan, Kaan Uyar, Erkut Inan Iseri, "Breast Cancer Classification Using Deep Learning", 14th International Conference on Theory and Application of Fuzzy Systems and Soft Computing – ICAFS-2020, vol.1306, pp.709, 2021.

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