DESIGN AND IMPLEMENTATION OF A SYSTEM FOR HEALTH DOCUMENT CLASSIFICATION USING MACHINE LEARNING
ABSTRACT
Document classification is the task of grouping documents into categories based upon their content. The aim of this study is to develop a system for Health Document Classification Using Machine Learning. In achieving this aim, the following specific objectives were laid out as follows to design and implement an application software that will totally or partially eliminate the problems encountered in the existing system and accurately classify the health documents either into Malaria, Diarrhea or Hypertension.
The motivation that led to the implementation of the proposed system is that due 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 medical diagnosis. Developing a classification algorithm that classifies a medical document by analyzing its content and categorizing it under predefined topics is the primary aim of this research. In this research, Natural Language Processing was applied which is a branch of Machine Learning to Classifying Health related documents.
The methodology adopted in this study is the structured system analysis and design methodology (SSADM) which is a technical approach for analyzing and designing an application or system by applying object throughout the software development process. The programming language used is HTML, CSS, JAVASCRIPT, PHP, SQL and JQUERY. The reason why web programming languages was used is because, it is platform independent and it is a web based application.
The software delivered from this project work will greatly reduce the time used by doctors, physicians and other health workers in searching and retrieving documents. The expected result is an electronic System for Health Document Classification Using Machine Learning that will be used to hold promising solutions for the global health arena to index and classify medical documents expeditiously and the system will also generate an accurate patients’ diagnostic health result for decision making purpose.
CHAPTER ONE
1.1 Introduction
Document classification is the task of grouping documents into categories based upon their content. Document classification is a significant learning problem that is at the core of many information management and retrieval tasks. Document classification performs an essential role in various applications that deals with organizing, classifying, searching and concisely representing a significant amount of information. Document classification is a longstanding problem in information retrieval which has been well studied (Russell, 2018).
As a prelude to other parts of this study, this chapter will discuss the background upon which this study was initiated, the statement of problems that led to this study, the Aim and Objectives of the study. Others are Significance of the study, Scope of work, Limitations of the Study and Definition of technical terms.
1.2 Background of Study
Contemporarily, most hospitals, medical laboratories and other health facilities make use of some kind of information system. These could be either a hospital management system or a pharmacy management system. Among other functions that these systems provide, they are mainly used in collecting patient records. These information systems stores patient records in digital format. Numerous patient data are being recorded on a daily basis which forms a large data set popularly referred to as “Big Data”.
Every day physicians and other health workers are required to work with this “Big Data” in other to provide solution. Some of the everyday tasks include information retrieval and data mining. Retrieving information from big data can be very laborious and time consuming. This has given rise to the study of text or document classification in other to aid the process of retrieving information from big data. Today, text classification is a necessity due to the very large amount of text documents that we have to deal with daily.
Document classification is the task of grouping documents into categories based upon their content. Document classification is a significant learning problem that is at the core of many information management and retrieval tasks. Document classification performs an essential role in various applications that deals with organizing, classifying, searching and concisely representing a significant amount of information. Document classification is a longstanding problem in information retrieval which has been well studied (Russell, 2018). Usually, machine learning, statistical pattern recognition, or neural network approaches are used to construct classifiers automatically. Machine learning approaches to classification suggest the automatic construction of classifiers using induction over pre-classified sample documents. In this project work we will employ machine learning in classifying health documents.
The challenges encountered that led to the execution of the research work is that, with the explosion of information fuelled by the growth of the World Wide Web it is no longer feasible for a human observer to understand all the data coming in or even classify it into categories. Also in the health sector, numerous patient records are being collected everyday and are used for analysis.
It is against the background that the developments of this software to enable health workers diagnose patients, so the software users should not give false information that is out of the software deeds. This research work is based on providing adequate information about medical records. At the end of this project, the research work, the software will be able to provide precise and concise patient records from the database.
1.3 Statement of Problem
Investigation reveals that due 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 medical diagnosis.
The explosion of information fuelled by the growth of the World Wide Web, it is no longer feasible for a human observer to understand all the data coming in or even classify it into categories. Also in the health sector, numerous patient records are being collected everyday and are used for analysis. How do we efficiently classify or categorize these health documents to complement easy retrieval.
1.4 Aim and Objectives of the Study
The aim of this study is to develop a system for Health Document Classification Using Machine Learning. In achieving this aim, the following specific objectives were laid out as follows to design and implement an application software that will:
- Study the various machine learning classification algorithm.
- Accurately classify the health documents either into Malaria, Diarrhea or Hypertension.
- Totally or partially eliminate the problems encountered in the existing system.
1.5 Significance of Study
The software delivered from this project work will greatly reduce the time used by doctors, physicians and other health workers in searching and retrieving documents.
Other importance of this project work includes:
- Helps students and other interested individuals that want to develop a similar application.
- It will serve as source of materials for those interested in investigating the processes involved in developing a document classification system using machine learning.
- It will serve as source of materials for students who are interested in studying machine learning.
1.6 Scope of the Study
The scope of this research focuses on the Design and Implementation of Health Document Classification Using Machine Learning. As stated earlier, statistical pattern recognition, or neural network are used in classifying documents, this project work will concentrate on using machine learning algorithm to classify document.
1.7 Limitations of the Study
During the course of this study, many things militated against its completion, some of which are:
- Time Constraint: The time frame given to accomplish this project was very short due to school academic calendar and it was carried out under pressure which made the researcher not to implement some necessary features.
- Research material: availability of research material is a major setback to the scope of the study.
- Frequent power failure: This made the researcher append more money on fuel to ensure sustainable power.
- Financial Constraint: Insufficient fund tends to impede the efficiency of the researcher in sourcing for the relevant materials, literature or information and in the process of data collection (internet).
1.8 Definition of Terms
Document Classification: is the task of grouping documents into categories based upon their content.
Health Document: A health certificate is written by a doctor and displays the official results of a physical examination.
Machine Learning: the study and construction of algorithms that can learn from and make predictions on data.
CHAPTER TWO
2.0 Literature Review
2.1 Introduction
The review of relevant literature is the main topic of this chapter. A literature review covers theoretical and methodological contributions to a certain issue in addition to the state of knowledge at the time of writing. It provides information about the state of the art in relation to the subject you are writing about. It examines the body of work on the chosen subject. The literature evaluation in this study comprises the …
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TABLE OF CONTENTSPRELIMINARY PAGES
- Title page
- Approval page
- Dedication
- Acknowledgement
- Table of Contents
- Abstract
INTRODUCTION
- 1.1 Introduction
- 1.2 Background of Study
- 1.3 Statement of Problem
- 1.4 Aim and Objectives of the Study
- 1.5 Significance of Study
- 1.6 Scope of the Study
- 1.7 Limitations of the Study
- 1.8 Definition of Terms
- 1.9 Organization of Work
LITERATURE REVIEW
- 2.1 Introduction
- 2.2 Overview of Document Classification
- 2.2.1 Text Categorization
- 2.3 Taxonomy of Text Classification Process
- 2.3.1 Tokenization
- 2.3.2 Stemming
- 2.3.3 Stop Word Removal
- 2.3.4 Vector Representation of the Documents
- 2.3.5 Feature Selection and Transformation
- 2.4 Assortment of Machine Learning Algorithms for Text Classification
- 2.5 Review of Related Work
SYSTEM ANALYSIS AND DESIGN
- 3.1 Introduction
- 3.2 Methodology Adopted
- 3.2.1 Problem Identification Using SSADM
- 3.3 Analysis of the Existing System
- 3.4 Analysis of the Proposed System
- 3.4.1 Requirements of the System
- 3.5 Training a Model
- 3.6 Classifying the Document
- 3.7 Use Case Diagrams
- 3.8 Sequence Diagram
- 3.9 Class Diagrams
- 3.10 System Flow Chart
SYSTEM DESIGN AND IMPLEMENTATION
- 4.1 Introduction
- 4.2 System Sample Output
- 4.2.1 Home Page
- 4.2.2 Administrator Login Page
- 4.2.3 Administrator Dashboard
- 4.2.4 User Login Page
- 4.2.5 User Dashboard
- 4.2.6 Upload Document
- 4.2.7 Upload Train File
- 4.3 System Specification and Design
- 4.3.1 Input and Output Specification
- 4.3.2 Database Specification and Design
- 4.4 Justification of the Programming Language
- 4.5 System Requirement
- 4.5.1 Software Requirement
- 4.5.2 Hardware Requirement
- 4.5.3 People
- 4.6 System Testing
- 4.7 Implementation Details
- 4.7.1 Coding
- 4.7.2 File Conversion
- 4.7.3 Changeover Procedure
- 4.7.4 Commissioning
- 4.7.5 File Maintenance Module
SUMMARY, CONCLUSION AND RECOMMENDATION
- 5.1 Introduction
- 5.2 Summary
- 5.3 Conclusion
- 5.4 Recommendation
- 5.5 Future Work
REFERENCES
APPENDIX A - “SOURCE CODE”
APPENDIX B - “OBJECT PROGRAM”
Disclaimer for Complete Material Utilization
The displayed research work titled "Design and Implementation of a System for Health Document Classification Using Machine Learning" is stated as a research guideline towards accomplishing your assigned project / seminar research work. All the research materials on this website are ONLY for research purposes and should be used as a guideline in developing your research work. For no reason should you copy word for word as projectlist.com.ng will not be liable for any who copied the material. By ordering the complete research guideline, it signifies that you've accepted our terms of service.
PRELIMINARY PAGES
- Title page
- Approval page
- Dedication
- Acknowledgement
- Table of Contents
- Abstract
INTRODUCTION
- 1.1 Introduction
- 1.2 Background of Study
- 1.3 Statement of Problem
- 1.4 Aim and Objectives of the Study
- 1.5 Significance of Study
- 1.6 Scope of the Study
- 1.7 Limitations of the Study
- 1.8 Definition of Terms
- 1.9 Organization of Work
LITERATURE REVIEW
- 2.1 Introduction
- 2.2 Overview of Document Classification
- 2.2.1 Text Categorization
- 2.3 Taxonomy of Text Classification Process
- 2.3.1 Tokenization
- 2.3.2 Stemming
- 2.3.3 Stop Word Removal
- 2.3.4 Vector Representation of the Documents
- 2.3.5 Feature Selection and Transformation
- 2.4 Assortment of Machine Learning Algorithms for Text Classification
- 2.5 Review of Related Work
SYSTEM ANALYSIS AND DESIGN
- 3.1 Introduction
- 3.2 Methodology Adopted
- 3.2.1 Problem Identification Using SSADM
- 3.3 Analysis of the Existing System
- 3.4 Analysis of the Proposed System
- 3.4.1 Requirements of the System
- 3.5 Training a Model
- 3.6 Classifying the Document
- 3.7 Use Case Diagrams
- 3.8 Sequence Diagram
- 3.9 Class Diagrams
- 3.10 System Flow Chart
SYSTEM DESIGN AND IMPLEMENTATION
- 4.1 Introduction
- 4.2 System Sample Output
- 4.2.1 Home Page
- 4.2.2 Administrator Login Page
- 4.2.3 Administrator Dashboard
- 4.2.4 User Login Page
- 4.2.5 User Dashboard
- 4.2.6 Upload Document
- 4.2.7 Upload Train File
- 4.3 System Specification and Design
- 4.3.1 Input and Output Specification
- 4.3.2 Database Specification and Design
- 4.4 Justification of the Programming Language
- 4.5 System Requirement
- 4.5.1 Software Requirement
- 4.5.2 Hardware Requirement
- 4.5.3 People
- 4.6 System Testing
- 4.7 Implementation Details
- 4.7.1 Coding
- 4.7.2 File Conversion
- 4.7.3 Changeover Procedure
- 4.7.4 Commissioning
- 4.7.5 File Maintenance Module
SUMMARY, CONCLUSION AND RECOMMENDATION
- 5.1 Introduction
- 5.2 Summary
- 5.3 Conclusion
- 5.4 Recommendation
- 5.5 Future Work
REFERENCES
APPENDIX A - “SOURCE CODE”
APPENDIX B - “OBJECT PROGRAM”
Disclaimer for Complete Material Utilization
The displayed research work titled "Design and Implementation of a System for Health Document Classification Using Machine Learning" is stated as a research guideline towards accomplishing your assigned project / seminar research work. All the research materials on this website are ONLY for research purposes and should be used as a guideline in developing your research work. For no reason should you copy word for word as projectlist.com.ng will not be liable for any who copied the material. By ordering the complete research guideline, it signifies that you've accepted our terms of service.
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