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Title |
Comparative Study of Machine Learning Algorithms in Breast Cancer Prognosis and Prediction |
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Author |
Majid Khawar, Dr. Naeem Aslam, Rao Muhammad Mahtab Mahboob, Mueed Ahmed Mirza, Hassan Jahangir, Awais Mughal |
| Citation |
Vol. 20 No. 8 pp. 125-133 |
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Abstract |
Machine learning is a classification of artificial intelligence that apply collection of analytical and development approach which enable computer to determine the former pattern. It means that it’s severely source desire in to the medical applications, such those based on large or multiplex data values. Machine learning is also concerned many times in cancer detection and diagnosis. In the cancer research the early prognosis and diagnosis of cancer is essential. A collection of machine learning approaches such as na?ve Bayes, support vector machine (SVMs), artificial neural network (ANN) and Decision Trees (DT’s) are used in medical research for progress of anticipate model following in successful and precise decision. It’s a challenge to extract the meaningful information from the large stored dataset. In this study we will provide the performance of machine learning tools by using dataset of cancer related to Breast Cancer and predict the cancer susceptibility, cancer recurrence and cancer survival also we will tell you which tool is better for in term of accuracy and efficiency with respect to CPU time and memory consumption |
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Keywords |
Accuracy, Efficiency, Prediction, Cancer Susceptibility, Cancer Recurrence, Cancer Survival, Precise Decision, Multiplex Data, Performance. |
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