A survey on Data Mining approaches for Healthcare

@inproceedings{Tomar2013ASO,
  title={A survey on Data Mining approaches for Healthcare},
  author={Divya Tomar and Sonali Agarwal},
  booktitle={Bio-Science and Bio-Technology},
  year={2013}
}
Data Mining is one of the most motivating area of research that is become increasingly popular in health organization. Data Mining plays an important role for uncovering new trends in healthcare organization which in turn helpful for all the parties associated with this field. This survey explores the utility of various Data Mining techniques such as classification, clustering, association, regression in health domain. In this paper, we present a brief introduction of these techniques and their… 

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References

SHOWING 1-10 OF 117 REFERENCES

Data Mining in Healthcare : Current Applications and Issues By

A survey of current techniques of KDD, using data mining tools for healthcare and public health, found a growing number of data mining applications, including analysis of health care centers for better health policy-making, detection of disease outbreaks and preventable hospital deaths, and detection of fraudulent insurance claims.

Application of Data Mining Techniques to Healthcare Data

  • Mary K Obenshain
  • Computer Science
    Infection Control & Hospital Epidemiology
  • 2004
A concrete example illustrates steps involved in the data mining process, and three successful data mining applications in the healthcare arena are described.

Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction

A survey of current techniques of knowledge discovery in databases using data mining techniques that are in use in today’s medical research particularly in Heart Disease Prediction reveals that Decision Tree outperforms and some time Bayesian classification is having similar accuracy as of decision tree but other predictive methods are not performing well.

Mining medical data to identify frequent diseases using Apriori algorithm

  • M. IlayarajaT. Meyyappan
  • Computer Science, Medicine
    2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering
  • 2013
A method to identify frequency of diseases in particular geographical area at given time period with the aid of association rule based Apriori data mining technique is developed.

Analysis of effectiveness of apriori algorithm in medical billing data mining

Apriori algorithm has been shown that the algorithm is equally beneficent for finding the large item sets and thus generating the association rules in medical billing data.

A Hybrid Data Mining Method for the Medical Classification of Chest Pain

This study concentrates on building a hybrid methodology, combining data mining techniques such as association rules and classification trees, that is applied to real-world emergency data collected from a hospital and is evaluated by comparing with other techniques.

Using Associative Classifiers for Predictive Analysis in Health Care Data Mining

The combined approach that integrates association rule mining and classification rule mining called Associative Classification (AC) is introduced, which gives a new type of Associative classifiers with small refinement in the definition of support and confidence that satisfies the validation of downward closure property.

Decision Support System for Medical Diagnosis Using Data Mining

This paper proposes the use of decision trees C4.5 algorithm, ID3 algorithm and CART algorithm to classify these diseases and compare the effectiveness, correction rate among them and to develop intelligent medical decision support systems to help the physicians.

Predictive Analysis on Hypertension Treatment using Data Mining Approach in Saudi Arabia

In the present investigation, the data sets of (Non Communicable Diseases) NCD risk factors a standard report of Saudi Arabia 2005 in collaboration with World Health Organisation have been employed
...