Smart Health Prediction System Using Data Mining

Authors

  • Nikita Kamble  Information Technology, University of Mumbai, Mumbai, Maharashtra, India
  • Manjiri Harmalkar  Information Technology, University of Mumbai, Mumbai, Maharashtra, India
  • Manali Bhoir  Information Technology, University of Mumbai, Mumbai, Maharashtra, India
  • Supriya Chaudhary  Information Technology, University of Mumbai, Mumbai, Maharashtra, India

Keywords:

Smart Health Prediction System, Data Mining, Clinical Predictions, Semi-Automatic Means, Clustering, Forecasting, Predictive Analysis.

Abstract

The paper presents an overview of the data mining techniques with its applications, medical,and educational aspects of Clinical Predictions. In medical and health care areas, due to regulations and due to the availability of computers, a large amount of data is becoming available. Such a large amount of data cannot be processed by humans in a short time to make diagnosis, and treatment schedules. A major objective is to evaluate data mining techniques in clinical and health care applications to develop accurate decisions. It also gives a detailed discussion of medical data mining techniques which can improve various aspects of Clinical Predictions. It is a new powerful technology which is of high interest in computer world. It is a sub field of computer science that uses already existing data in different databases to transform it into new researches and results. It makes use of machine learning and database management to extract new patterns from large data sets and the knowledge associated with these patterns. The actual task is to extract data by automatic or semi-automatic means. The different parameters included in data mining include clustering, forecasting, path analysis and predictive analysis.

References

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Published

2017-04-30

Issue

Section

Research Articles

How to Cite

[1]
Nikita Kamble, Manjiri Harmalkar, Manali Bhoir, Supriya Chaudhary, " Smart Health Prediction System Using Data Mining, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 2, pp.1020-1025, March-April-2017.