Enhancing reasoning through reduction of vagueness using fuzzy OWL-2 for representation of breast cancer ontologies

Author:

Oyelade Olaide N.ORCID,Ezugwu Absalom E.,Adewuyi Sunday A.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Reference64 articles.

1. Dheebaa J, Albert Singh NN, Tamil Selvi S (2014) Computer-aided detection of breast cancer on mammograms: a swarm intelligence optimized wavelet neural network approach. J Biomed Informa. https://doi.org/10.1016/j.jbi.2014.01.010

2. Silva VTDCE, Costalonga EC, Coelho FO, Caires RA, Burdmann AEA (2018) Assessment of kidney function in patients with cancer. Adv Chron Kidney Dis 25(1):49–56

3. Costa A, Oliveira H, Catani J, de Barros N, Melo C, Vieira M (2020) Data augmentation for detection of architectural distortion in digital mammography using deep learning approach.. Comput Vis Pattern Recognit. (2018). arXiv:1807.031672020

4. Zadeh HG, Pakdelazar O, Haddadnia J, Rezai-Rad G, Mohammad-Zadeh M (2012) Diagnosing breast cancer with the aid of fuzzy logic based on data mining of a genetic algorithm in infrared Images. Middle East J Cancer 3(4):119–129

5. Hadjiiski L, Sahiner B, Chan H-P (2006) Advances in CAD for diagnosis of breast cancer. Curr Opin Obstet Gynecol 18(1):64–70

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