Converting Raw Medical Data Into Informative Data Through Data-Mining Tools

Data mining allows companies to focus on the more important information in their data warehouses. Data mining can be broken down into two major categories. Automated prediction of trends and behaviors, and automated discovery of previously unknown patterns. In the first category, data mining automates the process of finding predictive information in large databases. Questions that traditionally required exhaustive hands-on analysis can now be quickly answered directly from data. In the second category…

promotional efforts. Data Mining What is Data Mining? Data mining is the process of analyzing data from different perspectives and summarizing it into useful information, this information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of…

Before a data set can be mined, it first has to be ?cleaned?. This cleaning process removes errors, ensures consistency and takes missing values into account. Next, computer algorithms are used to ?mine? the clean data looking for unusual patterns. Finally, the patterns are interpreted to produce new knowledge.3 How data mining can assist bankers in enhancing their businesses is illustrated in this example. Records include information such as age, sex, marital status, occupation, number of…

Populations of data are resented by chromosomes and then go through a process of evolution. The members of one set of data compete to pass on their most favorable characteristics to the next generation of data. This process continues until the best data is found. Many of the models and algorithms used in data mining are simplifications of the linear regression model. Data Mining is largely, if not entirely used for business purposes. The highest users of data mining include banking, financial…

“A number of healthcare advocacy, provider and consumer groups fear changes to new medical privacy rules could give a "green light" to banks and other financial institutions to access sensitive, personal medical information.”3 Consider for a moment the impact of a bank denying a person a loan because they are considered to be “not healthy” enough. Let’s say the person is getting over a drug addiction or has a history of smoking, the bank just might deny the loan based the on belief that the person…

Data stream mining is a stimulating field of study that has raised challenges and research issues to be addressed by the database and data mining communities. The following is a discussion of both addressed and open research issues [19]. Handling the continuous flow of data streams This is a data management issue. Traditional database management systems are not capable of dealing with such continuous high data rate. Novel indexing, storage and querying techniques are required to handle this non…

information age, a lot of data is generated from everywhere. Together with the incoming of information technology tools, so all the data are collected and waiting to be converted to information and knowledge. Therefore, the information industry provides useful information to many areas such as market analysis, science, decision-making and customer relationship. Data mining is the integration between analytical techniques and database system. Previously, it has only database query, data processing or transactional…

Traditional data mining applications had a great deal of attention on helping business gain well than others of a comparable nature. Data mining is explored to an increasing extent in areas such as financial analysis, telecommunications, biomedicines, science and also for counterterrorism and mobile (wireless) data mining. Scalable and interactive data mining methods: Data mining must be able to handle large amount of data efficiently and interactively apart from the existing data analysis methods…

What is Data Mining? Data mining is essentially the ability to discover new information by exploring through various databases of existing information. According to Laura and Jack Cook, data mining "facilitates the discovery of previously unknown relationships among the data. …These operations present results that users already intuitively knew existed in the database."[2] As an example, let us take a school system consisting of three databases: one which stores the student profiles consisting…

A data stream is a real time, continuous, structured sequence of data items. Mining data stream is the process of extracting knowledge from continuous, rapid data records. Data arrives faster, so it is a very difficult task to mine that data. Stream mining algorithms typically need to be designed so that the algorithm works with one pass of the data. Data streams are a computational challenge to data mining problems because of the additional algorithmic constraints created by the large volume of…