Every material on this site is authentic and was extracted from the complete available project. GET IT NOW
MS-WORD DOC | CHAPTERS: 1-5 | PAGES: 71 | PRICE: #3,000 ONLY
DESIGN AND IMPLEMENTATION OF DATA MINING FOR MEDICAL RECORD SYSTEM (A CASE STUDY OF OWERRI GENERAL HOSPITAL)
1.1 STUDY BACKGROUND
Data mining is the extraction of hidden predictive information from large database is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses . Data mining tools predict future trends and behaviors, allowing businesses to make proactive, knowledge driven decisions. The automated, prospective analysis offered by movement mining beyond the analyzes of past events provided by retrospective tools typical of decision support systems. Data mining tools can answer business questions that traditionally were too long to resolve. The scour databases for hidden patterns, finding predictive information that experts may miss because it lies outside their expectations.
Most companies already collect and refine massive amounts of data. Data mining techniques can be quickly implemented on software platforms and existing hardware to increase the value of existing information resources, and can be integrated with new products and the system they are brought online . That works on computers of high performance client / server or parallel processing, the data mining tools can analyze massive database to provide answers to questions such as "What customers are o motionalostmailing capable and why?" Data mining techniques are the result of a long research and development process of products. This evolution began when business data was first stored on computers, continued improvement of access to data, and more recently, generated technologies that allow users to navigate through their data in real time. Data mining takes this evolutionary process beyond retrospective data access and navigation to deliver proactive and forward-looking information.
Data mining is ready for application in the business community because it is supported by three technologies that are mature enough: the massive data collection, multiprocessor computers and powerful data mining algorithms. In this evolution from business data to information of the company, each new stage built on the previous. For example, access to dynamic data is essential for the drill in data navigation applications, and the ability to store large database is essential for data exploration. File management is obsolete in developed countries like the United States where and in developing countries like Nigeria the file system is always processed manually in most medical centers; This is a result of low level of technology. It was clear that the computer is everywhere in Nigeria. These computers are to make money, and after that, our hospitals lack of IT services, but with the help of data mining, we can automate our hospitals.
1.2 PROBLEM STATEMENT