Performance Analysis of Healthcare data and its Implementation on NVIDIA GPU using CUDA-C
In this paper we show how commodity GPU based data mining can help classify various healthcare data in different groups faster than traditional CPU based systems. In addition such systems are cheaper than various ASIC (Application Specific Integrated Circuits) based solutions. Such faster clustering of data could provide useful insights for making successful decisions in case of emergency and outbreaks. Finally, we present conclusion based on our research done so far. In our work we used NVIDIA GPU for implementing an algorithm for healthcare data classification. Speech dissiliency and stuttering assessment can also be addressed through classification audio/speech samples using ANN, k-NN, SVM etc4. Such a faster and economical way to get such insights is of paramount importance. Specifically as a proof-of-concept we have implement k-means algorithm on health care related data set.
Keywords: NVIDIA; GPU; ECG; CPU; ANN.
 DevashriS. Deshmukh, et al. ,“ REVIEW ON- ANDROID BASED HEALTH CARE MONITORING SYSTEM,” in International Journal of Innovation in Engineering, Research and Technology 2015.
 Rajasekaran S, et al., “HUMAN HEALTH MONITORING USING WIRELESS SENSORS NETWORK(WSN),” in International Journal of Application or Innovation in Engineering and Management(IJMIEM) , December 2013.
 Mahesh Kumar D, HEALTHCARE MONITORING SYSTEM USING WIRELESS SENSOR NETWORKS,” in International Journal of Advanced Networking and Applications, Apirl 2012.
 AlSharqi K, et al. ,“ZIGBEE BASED WEARABLE REMOTE HEALTHCARE MONITORING SYSTEM FOR ELDERLY PATIENTS,” in International Journal of Wireles & Mobile Networks(IJWMN) Vol. 6, No. , June 2014.
 Bourouis A et al. , “UBIQUITOUS MOBILE HEALTHCARE MONITORING SYSTEM FOR ELEDERLY (UMHMSE)”, International Journal of computer Science and Information Technology, 2011; 2(3):74-82.
 Lee Y.D., Chung W.Y.“WIRELESS SENSOR NETWORK BASED WEARABLE SMART SHIRT FOR UBIQUITIOUS HEALTH AND ACTIVITY MONITORNING" Sensors and Actuators B: Chemical, 2009; 140(2):390-395.
 Orlando R.E.P., et al. , “AN EFFICIENT AND LOW COST WINDOWS MOBILE BSN MONITORINING SYSTEM BASED ON TINYOS” , Journal of Telecommunications Systems, 2014; 54(1):1-9.
 Yuce M.R, “IMPLEMENTATION OF WIRELESS BODY AREA NETWORKS FOR HEALTHCARE SYSTEMS” , Sensor and Actuators A: Physical, 2010; 162(1):116- 129.
 Lei Clifton, et al. , “PREDICTIVE MONITORNING OF MOBILE PATIENTS BY COMBINING CLINICAL OBSERVATIONS WITH DATA FROM WEARABLE SENSORS “ , IEEE Journal of Biomedical and Health Informatics , 2014; 18(3):22-730.
 Hassanalieragh M et al ,“HEALTH MONITORING AND MANAGEMENT USING INTERNETOF- THINGS (IOT) SENSING WITH CLOUD-BASED PROCESSING: OPPORTUNITIES AND CHALLENGES” , IEEE International Conference on Services Computing , 2015.
 Picture Delhi’s AIIMS: HINDUSTAN TIMES, 16 SEPTEMBER 2016.
 Stephen D, Boyles.” USER EQUILIBRIUM AND SYSTEM OPTIMUM.”, https//webspace.utexas.edu.
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