Performance Analysis of Healthcare data and its Implementation on NVIDIA GPU using CUDA-C

  • Naseem Rao Assistant Professors, CSE Department, Hamdard University, Delhi, India
  • Safdar Tanweer Assistant Professors, CSE Department, Hamdard University, Delhi, India

Abstract

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.

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Author Biographies

Naseem Rao, Assistant Professors, CSE Department, Hamdard University, Delhi, India

Assistant Professors, CSE Department, Hamdard University, Delhi, India

Safdar Tanweer, Assistant Professors, CSE Department, Hamdard University, Delhi, India

Assistant Professors, CSE Department, Hamdard University, Delhi, India

References

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How to Cite
Rao, N., & Tanweer, S. (2019). Performance Analysis of Healthcare data and its Implementation on NVIDIA GPU using CUDA-C. Journal of Drug Delivery and Therapeutics, 9(1-s), 361-363. https://doi.org/10.22270/jddt.v9i1-s.2447