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Mobile Cancer Prophecy System to Assist Patients: Big Data Analysis and Design

Publication Type : Journal Article

Publisher : Journal of Computational and Theoretical Nanoscience

Source : Journal of Computational and Theoretical Nanoscience, 16(8), pp.3623-362

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Campus : Chennai

School : School of Engineering

Department : Computer Science and Engineering

Year : 2019

Abstract : The growth of cancer in India is growing hastily in recent years. Efficient monitoring and medication procedures are needed in high demand. Recent research states diagnose of cancer during its early break through will prevent mortality. The evolution of smart mobile devices paves its mutual focus in healthcare sectors. In this paper, an Intellectual model of disease diagnosis using the advantage of smart mobile devices has been proposed. This mobile based cancer diagnosis model uses a cloud environment for disease prediction and analysis. The Principal Component Analysis (PCA) technique is utilized to confiscate the superfluous features and choose the most appropriate features. Using the optimized features, cancer disease classification is accomplished using Support Vector Machines with sigmoid kernel function. SVM classifies the patients as normal and abnormal and the evaluated results are conveyed to the patients as well as the respective medical practitioners. The accuracy achieved through proposed model is satisfiable in comparison with other existing methods. Proposed Model incorporates with big data technologies to address the current issues of cancer system.

Cite this Research Publication : Suganya, E., Sountharrajan, S., Shandilya, S.K. and Karthiga, M., 2019. Mobile cancer prophecy system to assist patients: Big data analysis and design. Journal of Computational and Theoretical Nanoscience, 16(8), pp.3623-3628.

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