Annotated Bibliography.docx - Asri Hiba Mousannif Hajar Al Moatassime Hassan Noel Thomas.\u201cUsing Machine Learning Algorithms for Breast Cancer Risk

Annotated Bibliography.docx - Asri Hiba Mousannif Hajar Al...

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Asri, Hiba. Mousannif, Hajar. Al Moatassime, Hassan. Noel, Thomas.“Using Machine Learning Algorithms for Breast Cancer Risk Prediction and Diagnosis.” Procedia Computer Science , Elsevier, 12 May 2016, This academic journal discusses which machine learning algorithm is the best for classifying medical datasets for the analysis and diagnosis of breast cancer. Since computing and data science technologies such as big data, data mining and virtuation, and machine learning play a huge role in in the classification, reporting, analysis, and prediction of data; medical scientist apply such technologies due to their high performance in the prediction of outcomes and in optimizing processes to reduce costs and improve quality of service. The objective of this journal, “is to assess … the efficiency and effectiveness of each algorithm in the terms of accuracy, precision, sensitivity, and specificity” (Asri, Mousannif, Al Moatassime, Noel 1). To fulfill this objective an experiment was conducted using the WEKA machine learning environment to answer research questions made for the experiment. These questions are; “Which algorithm exploits better effectiveness? Which algorithm is more efficient? Which algorithm provides a higher accuracy?” (Asri, Mousannif, Al Moatassime, Noel 3). This source is credible because it comes from the ScienceDirect website, which is the world’s leading source for scientific, technical, and medical research journals, books and articles. Also the authors of this academic journal are the lead researchers at Cadi Ayyad University in Marrakech, Morocco and the University of Strasbourg in Strasbourg France.
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