IDEAS home Printed from https://ideas.repec.org/a/igg/jsda00/v7y2018i2p1-14.html
   My bibliography  Save this article

An Efficient Feed Foreword Network Model with Sine Cosine Algorithm for Breast Cancer Classification

Author

Listed:
  • Santosh Kumar Majhi

    (VSS University of Technology, Burla, India)

Abstract

This article describes how breast cancer is the most common invasive cancer in females worldwide and is major cause of deaths. The diagnoses of breast cancer include mammograms, breast ultrasound, magnetic resonance imaging (MRI), ductogram and biopsy. Biopsy is best and only way to know if the breast tumour is cancerous. Reports say that positive detection of breast cancer through biopsy can reach as low as 10%. So many statistical techniques and cognitive science approaches like artificial intelligence are being used to detect the type of breast cancer in a patient. This article presents the breast cancer classification using a feed foreword neural network trained by a sine-cosine algorithm. The superiority of the SCA-NN is shown by experimenting on the Wisconsin Hospital data set and comparing with the recently reported results. The evaluations show that the proposed approach is very robust, effective and gives better correct classification as compared to other classifiers.

Suggested Citation

  • Santosh Kumar Majhi, 2018. "An Efficient Feed Foreword Network Model with Sine Cosine Algorithm for Breast Cancer Classification," International Journal of System Dynamics Applications (IJSDA), IGI Global, vol. 7(2), pages 1-14, April.
    • Handle: RePEc:igg:jsda00:v:7:y:2018:i:2:p:1-14
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJSDA.2018040101
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Anwar E. Ibrahim & Salah Abdel-Mageid & Nadra Nada & Marwa A. Elshahed, 2022. "Human Identification Using Electrocardiogram Signal as a Biometric Trait," International Journal of System Dynamics Applications (IJSDA), IGI Global, vol. 11(3), pages 1-17, August.
    2. Priya Bhaskar Pandharbale & Sachi Nandan Mohanty & Alok Kumar Jagadev, 2021. "Novel Clustering-Based Web Service Recommendation Framework," International Journal of System Dynamics Applications (IJSDA), IGI Global, vol. 11(5), pages 1-15, September.
    3. Akram Belazi & Héctor Migallón & Daniel Gónzalez-Sánchez & Jorge Gónzalez-García & Antonio Jimeno-Morenilla & José-Luis Sánchez-Romero, 2022. "Enhanced Parallel Sine Cosine Algorithm for Constrained and Unconstrained Optimization," Mathematics, MDPI, vol. 10(7), pages 1-47, April.
    4. Jiang Wu & Feng Miu & Taiyong Li, 2020. "Daily Crude Oil Price Forecasting Based on Improved CEEMDAN, SCA, and RVFL: A Case Study in WTI Oil Market," Energies, MDPI, vol. 13(7), pages 1-20, April.
    5. Héctor Migallón & Akram Belazi & José-Luis Sánchez-Romero & Héctor Rico & Antonio Jimeno-Morenilla, 2020. "Settings-Free Hybrid Metaheuristic General Optimization Methods," Mathematics, MDPI, vol. 8(7), pages 1-25, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:jsda00:v:7:y:2018:i:2:p:1-14. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.