Download complete accounting project topics and materials on Design and implementation of data mining for Medical record system from chapter one to five
ABSTRACT
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Data mining is the extraction of hidden predictive information from large database which helps in predicting future trend and behavior thereby helping management make knowledge driven decisions. The data mining tool designed is to aid in quick access and retrieval of patients information to avoid time wasted in retrieving of such data from hospitals data warehouse.
The data mining tool was also designed to discover hidden pattern that helps in decision making by management. Structured System Analysis and Design Methodology were used in the analysis of the existing system which also provided a guide for the design of the proposed system.
PHP programming language and my SQL was used in the creation of a data warehouse for patient‟s information and data mining tool for the retrieval of such information when needed.
TABLE OF CONTENTS
Title Page
Approval Page
Certification Page
Dedication
Acknowledgement
Table of Contents
Abstract
CHAPTER ONE
INTRODUCTION
Background of Study
Statement of the Problem
Objectives of Study
Significance of Study
Scope of Study
Limitations of Study
Definition of related terms
CHAPTER TWO
REVIEW OF RELATED LITERATURE
Introduction
Review of related literature
CHAPTER THREE
SYSTEM ANALYSIS AND METHODOLOGY
System analysis
Method of data collection
Interviewing key officer
Observation method
Examination of document
Analysis of the existing system
Organization profile chart
Advantages of the existing system
Disadvantage of the existing system
Analysis of the proposed system
Justification of the proposed system
Methodology
Recommended appropriate mode
CHAPTER FOUR
SYSTEM DESIGN AND IMPLEMENTATION
Overview of design
Main menu
Program modules specification
Database design and specification
Input/output specification
Input form
Output form
Medical record system
Flowchart of the proposed solution
Choice and justification of programming language
System requirement
Implementation plan
Testing
Conversion
Training
CHAPTER ONE
INTRODUCTION
BACKGROUND OF STUDY
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 data mining move beyond the analyses of past events provided by retrospective tools typical of decision support systems. Data mining tools can answer business questions that traditionally were too time consuming to resolve. The scour databases for hidden patterns, finding predictive information those experts may miss because it lies outside their expectations.
Most companies already collect and refine massive quantities of data. Data mining techniques can be implemented rapidly on existing software and hardware platforms to enhance the value of existing information resources, and can be integrated with new products and system as they are brought on-line.
Which implemented on high performance client/server or parallel processing computers, data mining tools can analyze massive database to deliver answers to questions such as “Which client are most likely to respond to my next promotional mailing, and Why?”
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