Breast cancer detection by using Hierarchical Fuzzy Neural system with EKF trainer

Naghibi, Seyedeh Somayeh; Teshnehlab, Mohammad; Shoorehdeli, Mahdi Aliyari

doi:10.1109/icbme.2010.5704983

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2022

2024

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“…A specialized system for diagnosing breast cancer was proposed in [11]. In paper [12], the authors propose a new approach using a hierarchical fuzzy neural network for the diagnosis. In [13] a TSK-type fuzzy model is presented for diagnosing breast cancer.…”

Section: Introductionmentioning

confidence: 99%

Clinical Diagnosis of Breast Cancer Samples Using Negative Selection Algorithm

Souza¹,

Gonçalvez²,

Chavarette³

et al. 2022

Open Science Research III

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This chapter uses an artificial immune system applied for diagnosing breast cancer samples. Taking as basis an immunological process, the Negative Selection Algorithm was used to discriminate the samples, attaining a classification for benign or malignant cases.The main application of the method is to assist professionals in the breast cancer diagnostic process, thereby providing decision-making agility, efficient treatment planning, reliability and the necessary intervention to save lives. To evaluate this method, the Wisconsin Breast Cancer Diagnosis database was used. This is an actual breast cancer database.The results obtained using the method, when compared with the specialized literature, show accuracy, robustness and efficiency in the breast cancer diagnostic process.

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Section: Introductionmentioning

confidence: 99%