A Framework for Modeling Critical Success Factors in the Selection of Machine Learning Algorithms for Breast Cancer Recognition

Martínez, Miguel Ángel Quiroz; Marin, Eddy Raul Montenegro; Landivar, Galo Enrique Valverde; Vázquez, Maikel Yelandi Leyva

doi:10.1007/978-3-030-85540-6_111

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2022

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“…The manual method of detecting the breast tumors: malignant and benign is very complicated and time-consuming process as they share similar structures. The artificial intelligence techniques can give a reliable and faster approach for detecting breast cancer in patients [34], [35]. The artificial intelligence techniques are used in prediction of breast cancer either from the medical images [36]- [43] or from the datasets containing categorical and numerical values [44], [45].…”

Section: Introductionmentioning

confidence: 99%

Blockchain integrated multi-agent system for breast cancer diagnosis

Ramanathan

Hossen

Sayeed

2022

IJEECS

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<span>The integration of multi-agent system and blockchain technology can be beneficial to healthcare applications by providing intelligent data analysis with security. This paper presents an architecture that integrates multi-agent learning system and blockchain technology to support breast cancer diagnosis in a secured manner. The proposed system is based on a parallel hybrid fuzzy logic approach for supporting the prediction of breast cancer disease. The proposed system showed a classification accuracy of 96.49% in breast cancer diagnosis when testing with the Wisconsin Diagnostic Breast Cancer dataset. The blockchain is used to provide agent security in the proposed system to ensure that the only trusted and reputed agents are participated in the decision-making process.</span>

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