TY - GEN
T1 - A Study of Physiological Homeostasis and Its Analysis Related to Cancer Disease Based on Regulation of pH Values Using Computer-Aided Techniques
AU - Godi, Rakesh Kumar
AU - Balaji, G. N.
AU - Vaidehi, K.
N1 - Publisher Copyright:
© Springer Nature Singapore Pte Ltd 2020.
PY - 2020
Y1 - 2020
N2 - 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).
AB - 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).
UR - https://www.scopus.com/pages/publications/85078453214
UR - https://www.scopus.com/inward/citedby.url?scp=85078453214&partnerID=8YFLogxK
U2 - 10.1007/978-981-15-1097-7_61
DO - 10.1007/978-981-15-1097-7_61
M3 - Conference contribution
AN - SCOPUS:85078453214
SN - 9789811510960
T3 - Advances in Intelligent Systems and Computing
SP - 725
EP - 734
BT - Data Engineering and Communication Technology - Proceedings of 3rd ICDECT 2019
A2 - Raju, K. Srujan
A2 - Senkerik, Roman
A2 - Lanka, Satya Prasad
A2 - Rajagopal, V.
PB - Springer
T2 - 3rd International Conference on Data Engineering and Communication Technology, ICDECT 2019
Y2 - 15 March 2019 through 16 March 2019
ER -
