Data Mining In Healthcare

ABSTRACT

Health care industries are fastest growing field. The medical industries have massive amount of collected works about patient details, diagnosis and medications. Data mining approaches are utilized in health care industries to turns these data is into valuable pattern and to predicting coming up trends. The healthcare industry brings together vast amount of healthcare data which are not “mined” to discover unseen information. To achieve good quality of service, the healthcare industries should provide better diagnosis and treatment to the patients.

CHAPTER-1

INTRODUCTION

Data Mining is one of the most fundamental and inspiring area of research with the objective of finding significant information from huge data sets.

Data mining can be done on textual, quantitative or multimedia data. Data mining applications can use different kind of parameters to monitor the data. They include association (patterns where one event is related to another event), sequence or path analysis (patterns where one event leads to another event), classification (identification of new patterns with predefined targets) and clustering (grouping of identical or alike objects).Data mining involves some of the following key steps:

(1) Problem definition: The first step is to discover goals. Based on the defined goal, the correct series of tools can be applied to the data to build the corresponding behavioral model.

(2) Data exploration: If the value of data is not suitable for an perfect model then recommendations on future data collection and storage strategies can be made at this. For analysis, all data needs to be consolidated so that it can be treated consistently.

(3) Data preparation: The purpose of this step is to clean and convert the data so that missing and invalid values are treated and all known valid values are made reliable for more robust

Srinivas, B. Kavitha Rani and Dr. A. Govardhan, ―Applications of Data Mining Techniques in Healthcare and Prediction of Heart Attacks International Journal on Computer Science and Engineering (2010).

[3] ShwetaKharya, ―Using Data Mining Techniques for Diagnosis and Prognosis of Cancer Diseaseǁ, International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.2, April 2012.

[4] Arvind Sharma and P.C. Gupta ―Predicting the Number of Blood Donors through their Age and Blood Group by using Data Mining Tool| International Journal of Communication and Computer Technologies Volume 01 – No.6, Issue: 02 September 2012.

[5] M. Durairaj, V. Ranjani- Data Mining Applications in Healthcare Sector: A Study International Journal of Scientific& Technology Research Volume 2, Issue 10, October 2013

[6] Gitanjali J., C.Ranichandra, M. Pounambal, ―APROIRI algorithm based medical data mining for frequent disease identification, ǁ Univ. VIT, Vellore, 4, April 4, 2014, Vol 2.

[7] S. Nagaparameshwara Chary, B.Ram, "Analysis of Classification Technique Algorithms in Data mining- A Review", International Journal of Computer Sciences and Engineering, Volume-04, Issue-06, Page No (180-185), Jun