Intelligent Fuzzy Clinical Decision Support System to Classify Breast Cancer—Case Study: The Wisconsin Dataset-Reference-Cited by-同舟云学术

Intelligent Fuzzy Clinical Decision Support System to Classify Breast Cancer—Case Study: The Wisconsin Dataset

Published:2023 Issue: Volume: Page:541-550
ISSN:1876-1100
Container-title:Medical Imaging and Computer-Aided Diagnosis
language:
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Author:

Hernández-Julio Y. F.^ORCID,Díaz-Pertuz L. A.^ORCID,Prieto-Guevara M.^ORCID,Avilés-Román M.^ORCID,Castillo-Osorio B.^ORCID,Barrios-Barrios M.^ORCID,Nieto-Bernal W.^ORCID

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-6775-6_44

Reference12 articles.

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2. Breast Cancer Now. What are the signs and symptoms of breast cancer? Available online: https://breastcancernow.org/about-us/media/facts-statistics#signs-and-symptoms (accessed on February).

3. Nilashi, M.; Ibrahim, O.; Ahmadi, H.; Shahmoradi, L. A knowledge-based system for breast cancer classification using fuzzy logic method. Telematics and Informatics 2017, 34, 133–144, doi: https://doi.org/10.1016/j.tele.2017.01.007.

4. Gayathri, B.M.; Sumathi, C.P. Mamdani fuzzy inference system for breast cancer risk detection. In Proceedings of the 2015 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), 10–12 Dec. 2015, 2015; pp. 1–6.

5. Hernández-Julio, Y.F.; Prieto-Guevara, M.J.; Nieto-Bernal, W.; Meriño-Fuentes, I.; Guerrero-Avendaño, A. Framework for the development of data-driven Mamdani-type fuzzy clinical decision support systems. Diagnostics 2019, 9, 1–33.