Data Mining
Data Mining On Medical Domain
Smita Malik, Karishma Naik, Archa Ghodge, Shivani Gaunker
Shree Rayeshwar Institute of Engineering & Information Technology
Shiroda, Goa, India.
Smilemalik777@gmail.com; naikkarishma39@gmail.com; archaghodge@gmail.com; shivanigaunker@gmail.com
Abstract-The successful application of data mining in highly visible fields like retail, marketing & e-business have led to the popularity of its use in knowledge discovery in databases (KDD) in other industries & sectors. Among this sectors that are just discovering data mining are the fields of medicine and public health. The data generated by healthcare transactions is huge. This medical data about large patient population is analysed to perform medical research.
We propose a system which allows us to obtain data patterns with the help of clustering algorithms. In this paper we have experimented on data gathered from Community Health Centre hospital which surveys the people from various area of Ponda Goa, India. This medical data is then analysed using the clustering algorithms like K-means & CLIQUE. K-means algorithm reveals the percentage of a particular disease in the surveyed areas & also finds out the percentage of diseases which prevails in a particular area. It also finds out the age group in which the disease is most significant. A complete study on Anaemia in pregnant women is done using CLIQUE algorithm.
Keywords- Data Mining, KDD, K-means, CLIQUE
I. INTRODUCTION
The huge amounts of data generated by healthcare transactions are too complex and voluminous to be processed and analysed by traditional methods. When medical sectors apply data mining on their existing data they can discover new, useful & potentially life-saving knowledge that otherwise would have remained inert in their databases. Data Mining is the process of extracting or mining knowledge from large amounts of data. In Data Mining, intelligent methods are applied in order to
Smita Malik, Karishma Naik, Archa Ghodge, Shivani Gaunker
Shree Rayeshwar Institute of Engineering & Information Technology
Shiroda, Goa, India.
Smilemalik777@gmail.com; naikkarishma39@gmail.com; archaghodge@gmail.com; shivanigaunker@gmail.com
Abstract-The successful application of data mining in highly visible fields like retail, marketing & e-business have led to the popularity of its use in knowledge discovery in databases (KDD) in other industries & sectors. Among this sectors that are just discovering data mining are the fields of medicine and public health. The data generated by healthcare transactions is huge. This medical data about large patient population is analysed to perform medical research.
We propose a system which allows us to obtain data patterns with the help of clustering algorithms. In this paper we have experimented on data gathered from Community Health Centre hospital which surveys the people from various area of Ponda Goa, India. This medical data is then analysed using the clustering algorithms like K-means & CLIQUE. K-means algorithm reveals the percentage of a particular disease in the surveyed areas & also finds out the percentage of diseases which prevails in a particular area. It also finds out the age group in which the disease is most significant. A complete study on Anaemia in pregnant women is done using CLIQUE algorithm.
Keywords- Data Mining, KDD, K-means, CLIQUE
I. INTRODUCTION
The huge amounts of data generated by healthcare transactions are too complex and voluminous to be processed and analysed by traditional methods. When medical sectors apply data mining on their existing data they can discover new, useful & potentially life-saving knowledge that otherwise would have remained inert in their databases. Data Mining is the process of extracting or mining knowledge from large amounts of data. In Data Mining, intelligent methods are applied in order to