Abstract
In this modern life, many people are prone to cancer disease. According to the survey made by WHO (World Health Organization), the percentage of cancer found to increase up to 45 in middle-aged people and even found in children within age limit of 14; hence, death rate because of cancer is increasing day by day. This disaster is big challenge to medical world and has a massive amount of data to be analyzed within short time. It is not feasible for the doctors to predict the cancer at early stages based on the medical examination tests and reports. Hence in order to process the collected medical data, time reduction, data optimization, minimize service costs, quality of advanced treatment and efficiency of the clinical data, the health care industry relies on biomedical information technology. This paper aims to provide feasible solution for human health analysis related to cancer disease based on the electrolyte values extracted from the collected samples of urine and blood from the patient, and based on the output analysis, the patient condition is predicted. The electrolyte values from urine and blood samples are integrated with help of data fusion techniques to generate single-dimensional data. The desired pH homeostasis information is extracted using feature extraction technique from the data set. This optimized data is then classified using ANN (artificial neural network) and analyzed using SVM (support vector machine).
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Change history
11 March 2024
A correction has been published.
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Acknowledgements
The authors would like to thank Dr. N. Chidambaram, Annamalai University for providing the data set required for this research.
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Godi, R.K., Balaji, G.N., Vaidehi, K. (2020). RETRACTED CHAPTER: A Study of Physiological Homeostasis and Its Analysis Related to Cancer Disease Based on Regulation of pH Values Using Computer-Aided Techniques. In: Raju, K.S., Senkerik, R., Lanka, S.P., Rajagopal, V. (eds) Data Engineering and Communication Technology. Advances in Intelligent Systems and Computing, vol 1079. Springer, Singapore. https://doi.org/10.1007/978-981-15-1097-7_61
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DOI: https://doi.org/10.1007/978-981-15-1097-7_61
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