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A System For Health Document Classification Using Machine Learning
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CHAPTER FOUR SYSTEM IMPLEMENTATION
4.0 INTRODUCTION
After careful requirement gathering, analysis and design, the system is implemented. Implementation involves testing the system with required data and observing the results to see if the system has been properly deigned or if it contains bugs. This is usually done with data which has known results. In this chapter we will implement the system designed.
4.1 SYSTEM REQUIREMENTS
To implement the application, the computer on which it will run has to meet some hardware and software requirements. Also since it has been designed as a web enabled application, the server on which the system will be deployed also has to meet certain hardware and software requirements. The following section will outline these requirements.
4.1.1 SERVER HARDWARE SPECIFICATION
1. 4GB of RAM and above
2. 500 GB Hard Disk or more
3. 2.0 GHZ processor speed or more
4.1.2 SERVER SOFTWARE SPECIFICATION
1. 32-bit or 64-bit Operating System, Windows or Linux
2. Java Runtime Environment, version 7
3. Apache Tomcat Server version 7
4. MySQL version 5
4.1.3 CLIENT HARDWARE SPECIFICATION
1. 1GB of RAM
2. 80 GB Hard Disk
3. 2.0 GHZ processor speed.
4. 15 inches Monitor Screen
5. Internet modem
4.1.4 CLIENT SOFTWARE SPECIFICATION
1. 32-bit Operating System, Windows or Linux
2. Web browser
4.2 SYSTEM SAMPLE OUTPUT
This section displays the sample interface, and describes the functions of each web page in the system.
4.2.1 HOME PAGE
This is the first page that displays to the users of the system. It contains a brief introduction to the application as well as the login link for the administrators and the users.
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ABSRACT - [ Total Page(s): 1 ]ABSTRACTDue to the massive increase in medical documents every day (including books, journals, blogs, articles, doctors' instructions and prescriptions, emails from patients, etc.), it is becoming very challenging to handle and to categorize them manually. One of the most challenging projects in information systems is extracting information from unstructured texts, including medical document classification. The discovery of knowledge from medical datasets is important in order to make effective ... Continue reading---
APPENDIX A - [ Total Page(s): 2 ]APPENDIX A ... Continue reading---
APPENDIX C - [ Total Page(s): 1 ]APPENDIX Cen-diseases.trainMalaria is a life-threatening mosquito-borne blood disease caused by a Plasmodium parasite Malaria was eliminated from the U.S. in the early 1950sMalaria is typically spread by mosquitoesMalaria symptoms can be classified into two categoriesMalaria happens when a bite from the female Anopheles mosquito infects the body with PlasmodiumMalaria is a mosquito-borne infectious disease affecting humans and other animals caused by parasitic protozoansMalaria is a mosquito-bor ... Continue reading---
APPENDIX B - [ Total Page(s): 11 ]APPENDIX B ... Continue reading---
CHAPTER ONE - [ Total Page(s): 2 ]CHAPTER ONE1.0 INTRODUCTIONThis chapter introduces the topic of the project work A System for Health Document Classification Using Machine Learning. In this chapter, we will consider the background of the study, statement of the problem, aims and objectives, methodology used to design the system, scope of the study, its significance, definition of terms, and we conclude with the project layout or organization of the project work.1.1 BACKGROUND OF THE STUDYContemporarily, most hospita ... Continue reading---
CHAPTER TWO - [ Total Page(s): 3 ]CHAPTER TWOLITERATURE REVIEW2.0 DOCUMENT CLASSIFICATIONClassification can be divided in two principal phases. The first phase is document representation, and the second phase is classification. The standard document representation used in text classification is the vector space model. The difference of classification systems is in document representation models. The more relevant the representation is, the more relevant the classification will be. The second phase includes learning from tr ... Continue reading---
CHAPTER THREE - [ Total Page(s): 3 ]3.4 SEQUENCE DIAGRAMSequence diagrams are simple subsets of interaction diagrams. They map out sequential events in an engineering or business process in order to streamline activities. Sequence diagrams are used to show how objects interact in a given situation. An important characteristic of a sequence diagram is that time passes from top to bottom: the interaction starts near the top of the diagram and ends at the bottom (i.e. Lower equals Later).3.5 CLASS DIAGRAMSWe begin our OOD ... Continue reading---
CHAPTER FIVE - [ Total Page(s): 1 ]CHAPTER FIVE SUMMARY AND CONCLUSION5.0 INTRODUCTIONThis chapter summarizes and concludes the project work; it also gives recommendations and insight to future work.5.1 SUMMARYIn this project work we were able to succeed in applying Natural Language Processing which is a branch of Machine Learning to Classifying Health related documents. We made use of the OpenNLP Application Programming Interface which is a Java API for training a model and classifying the documents. We make use of M ... Continue reading---
REFRENCES - [ Total Page(s): 1 ]REFERENCERussell Power, Jay Chen, Trishank Karthik and Lakshminarayanan Subramanian (2018),“Document Classification for Focused Topics†https://cs.nyu.edu/~jchen/publications/aaai4d-power.pdf.Hull D., J. Pedersen, and H. Schutze (1996), “Document routing as statistical classification,†in AAAI Spring Symp. On Machine Learning in Information Access Technical Papers, Palo Alto.Fox C. (1992), “Lexical analysis and stoplist,†in Information Retrieval Data Structur ... Continue reading---
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ABSRACT - [ Total Page(s): 1 ]ABSTRACTDue to the massive increase in medical documents every day (including books, journals, blogs, articles, doctors' instructions and prescriptions, emails from patients, etc.), it is becoming very challenging to handle and to categorize them manually. One of the most challenging projects in information systems is extracting information from unstructured texts, including medical document classification. The discovery of knowledge from medical datasets is important in order to make effective ... Continue reading---