Patient Centric Healthcare Analysis and Classification to Recommend Medicines

Authors

  • S. Pradeepkumar  Computer Science and Engineering Department, Saranathan College of Engineering, Trichy, Tamilnadu, India
  • S. Sabeek Ahamed  Computer Science and Engineering Department, Saranathan College of Engineering, Trichy, Tamilnadu, India
  • K. Ponnivalavan  Computer Science and Engineering Department, Saranathan College of Engineering, Trichy, Tamilnadu, India
  • B. Srivathsan  Computer Science and Engineering Department, Saranathan College of Engineering, Trichy, Tamilnadu, India

Keywords:

Decision Tree, Machine Learning, Medical Diagnosis, Random Forest, Medical Imaging

Abstract

Handling Bigdata is one of the major issues in the field of Medicine. The huge numbers of tablets, manufacturers, distributors, doctors and diseases leads a world with medical errorness and correptiveness. Our intention is to reduce the fraudulent and the deaths rate due to this. By analyzing patients data and tablets data we conclude that the perfect solution for a patient by make use of machine learning techniques. By implementing our project every patient, doctor and medicines prescribed are monitored and every patient assure that they are treated by correct treatment.

References

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-04-30

Issue

Volume 3, Issue 3, March-April-2018

Section

Research Articles

License

Copyright (c) IJSRCSEIT

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
S. Pradeepkumar, S. Sabeek Ahamed, K. Ponnivalavan, B. Srivathsan, " Patient Centric Healthcare Analysis and Classification to Recommend Medicines" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.1128-1133, March-April-2018.