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23 INTERNATIONAL JOURNAL OF INNOVATION IN ENGINEERING RESEARCH & MANAGEMENT ISSN: 2348-4918

Peer Reviewed and Refereed Journal

VOLUME: 10, Special Issue 02, (IC-IMAF-2023) Paper id-IJIERM-X-II, January 2023

DATA MINING AND KNOWLEDGE DISCOVERY IN HEALTH SECTOR

1Sunil Saini, Research Scholar

2Dr. Himanshu Aggarwal, Professor

1,2Department of Computer Science & Engineering, UCOE, Punjabi University, Patiala, India

1 INTRODUCTION

Data mining for predicting the disease in an early phase in one of the most important topic of research in today’s era. The health care sector is one of the largest sectors that directly impact people’s lives in every country of the world. Due to unhealthy life styles, the number of patients increase sine very category of diseases, so their related data also increase sat alarming rates. The way of organizing the data is most important by which it could best ore easily and searched when ever required by the user. The data stored can be analyzed and lead to better decision-making [1]. The different organizations collect data sets from different sources like digital health wearable, health trackers, genomic sequences, electronic health records, and prescriptions. In the past, the storing and management of data was a more significant problem, but now it is much easier with the new technology. This figure shows share of health care expenditure.

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2 KNOWLEDGE DISCOVERY PROCESS

3 DATA MINING TECHNIQUES

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4 KEY POINTS

 Due to rise in number of disease, the scale of health care data is increasing day by day. Therefore mining of this large scale data can provide hidden in sights and patterns.

 This research will provide accurate data to practitioners for analysis

 It helps practitioners to diagnose the disease in better way

 It will help the society to modify their habits for healthy life style

 This research will help society to save lot of money and every class in society will be benefited

5 CONCLUSION & FUTURE SCOPE

 Raw data can provide useful information by applying know ledged is co very process.

 With the help of right data mining technique, a patient can be treated with correct treatment at early stage of disease.

 Amalgamation of mining techniques with approximation method will provide better results in future.