Smita Parija

Department of Electronics and Telecommunication Engineering, C V Raman Global University, Odisha, India


  • Research Article   
    Prediction of breast cancer using tools of machine learning techniques
    Author(s): Madhumita Pal, Smita Parija* and Ganapati Panda

    Objective: Machine learning techniques have been shown to support multiple medical prognoses. The purpose of this article is to compare some machine learning techniques to compare the diagnosis of breast cancer (cancerous and non-cancerous) using the inputs from five supervised machine learning approaches through the different feature selections to get a correct result. Materials and methods: This study included 683 cases of breast cancer, four hundred and forty-four being benign and two hundred and thirty-nine malignant; the studied data were taken from the UCI machine learning repository. Ten models for machine learning were evaluated and only five were selected from the correlation matrix (SVC, logistic regression, random forests, XGBoost or K-NNs). Results: Random forests and the K-NNs model predict the most significant true positives among the five techniques... Read More»

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Awards Nomination

Editors List

  • Prof. Elhadi Miskeen

    Obstetrics and Gynaecology Faculty of Medicine, University of Bisha, Saudi Arabia

  • Ahmed Hussien Alshewered

    University of Basrah College of Medicine, Iraq

  • Sudhakar Tummala

    Department of Electronics and Communication Engineering SRM University – AP, Andhra Pradesh




  • Alphonse Laya

    Supervisor of Biochemistry Lab and PhD. students of Faculty of Science, Department of Chemistry and Department of Chemis


  • Fava Maria Giovanna


Google Scholar citation report
Citations : 208

Onkologia i Radioterapia received 208 citations as per Google Scholar report

Onkologia i Radioterapia peer review process verified at publons
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