DEVELOPING DIAGNOSTIC SYSTEM FOR PROSTATE CANCER
TABLE OF CONTENT
Table of content………v
1.1 GENERAL OVERVIEW OF THE STUDY
1.2 STATEMENT OF PROBLEM
1.3 AIM OF STUDY
1.5 SCOPE AND LIMITATION
1.6 ORGANIZATION OF THE PROJECT
1.8 DEFINITION OF TERMS
2.1. Anatomy, Physiology and Pathology of the prostate
2.2. Prostate Functionality:
2.3. Anatomy of the prostate gland:
2.4. Surrounding functions of the prostate:
2.5. Pathology - Prostate cancer:
2.6. Prostate cancer symptoms:
2.7. Prostate Cancer Statistics:
2.8. FUZZY LOGIC:
2.9. Expert systems
2.10. FUZZY EXPERT SYSTEM
2.12. Types of Cancer
SYSTEM ANALYSIS AND DESIGN
3.2 System Analysis
3.2.1 System Architecture
22.214.171.124 Components of The System Architecture
3.2.2 Database Model
3.2.3 Fuzzy Logic Model
126.96.36.199 Rule Base
188.8.131.52 Fuzzy Inference Mechanism
3.3.1 Use-case Diagram
3.5 Activity Diagram
3.6 System Class Diagram
4.1 SOFTWARE REQUIREMENTS
4.2 HARDWARE REQUIREMENTS
4.3 PROGRAM SETUP
4.3 SNAPSHOTS OF THE SYSTEM
SUMMARY, RECOMMENDATIONS AND CONCLUSION
1.2 GENERAL OVERVIEW OF THE STUDY
Prostate cancer is cancer that occurs in the prostate, a small walnut-shaped gland in men that produces the seminal fluid that nourishes and transports sperm. Prostate cancer is one of the most common type of cancer in men. Usually it grows slowly and is initially confined to the prostate gland, where it may cause serious harm. However, while some types of prostate cancers grow slowly and may need minimal or no treatment, other types are aggressive and can spread quickly. Prostate cancer that is detected early when it is still confined to the prostate gland has a better chance of successful treatment.
Prostate cancer is the second leading cause of cancer-related deaths and the most common non-skin cancer malignancy among men; it is the most commonly diagnosed cancer among older men in Nigeria. An estimated 240,000 men were newly diagnosed with prostate cancer in 2011.Despite attempts to minimize gap in healthcare, African American men are disproportionately burdened by prostate cancer compared to all other racial and ethnic groups. The mortality rate of prostate cancer is an estimated 2 to 4 times greater amongst African-American men. (American Cancer Society. Cancer Facts & Figures 2011. Atlanta, GA: American Cancer Society; 2011)
It is quite possible to diagnose prostate cancer fully based on ultrasonography and image processing. However, attempt will be made in this study in developing a rule based fuzzy expert system (FES) that uses a laboratory and other data and simulates an expert doctor’s behaviour. As known when the prostate cancer can be diagnosed earlier the patient can be treated completely. Diagnosis is the determination of the nature of a disease, modern diagnosis combine the taking of the patient’s health history, physical examination, and laboratory examination. Prostate specific antigen (PSA) and prostate volume (PV) and age of the patient will be used as sign and symptoms (variable for the diagnosis).Using this variable fuzzy logic Expert system will be developed in a MATLAB programming environment. The Fuzzy Expert System (FES) is rapid, economical, without risk compared to traditional diagnostic system and it has also a high reliability and it can be used as a learning system for medical students.
1.2 STATEMENT OF PROBLEM
In the world today, access to medical education and health out is getting more limited than access to computer system. Early diagnosis of prostate cancer is vital to prevent premature death due to prostate cancer. In this regard a computer diagnostic system can bridge the gap.
1.7 AIM OF STUDY
The aim of this research project is to design and develop a fuzzy logic expert system for the diagnosis of prostate cancer.
The objective includes:
a) design of a fuzzy type-one rules and membership function for the diagnose of prostate cancer.
b) coding the design in (a) in MATLAB programming environment.
c) carry out a case study of the design using data obtained from the University of Uyo Teaching Hospital
The method of carrying out the research include, Review of literature on prostate cancer and fuzzy logic technology.
The use of fuzzy type-1 Mamdani Minmax operator formulation of fuzzy rules and triangular membership grade.
1.9 SCOPE AND LIMITATION
Only data obtained from University of Uyo Teaching Hospital for the diagnose.
1.10 ORGANIZATION OF THE PROJECT
The study is organized into five chapters.
Chapter one deals with the introductory aspect of the study and provides an insight on what the study is all about. Chapter one is the introduction of the project.
Chapter two is the literature review.
Chapter three is the design of the fuzzy expert system.
Chapter four is the implementation.
Chapter five is the summary
1.8 DEFINITION OF TERMS
EXPERT SYSTEM: This is a software which uses database of expert knowledge to offer advice or make decision in such area of medical diagnosis. In AI an expert system is a computer system that emulates the decision making ability of a human expert.
PROSTATE: It is a male sex gland that produces a thick fluid that forms a part of the semen. The prostate is located below the bladder and in front of the rectum and it surrounds the upper part of the urethra, the tube that empties urine from the bladder.
CANCER: It is a group of many different diseases that have important things in common. They all affect cell, the body’s basic unit of life. Cancer is made up of abnormal cell that grow even when the body does not need them.
PROSTATE CANCER: It is the most common cancer in men. It tends to occur mainly in older men from the age of 45 and above. It affects the prostate gland that produces some of the fluid in semen and plays a role in urine control in men. However most prostate cancer is diagnosed with the following symptoms:
1) Inability to urinate
2) Discontinuous or weak urine flows,
3) Difficulty in starting or stopping urine flow,
4) Blood in the urine
5) Pain or burning with urination ,
6) Frequent urination, especially at night
7) Prostate specific antigen.
8) Prostate volume.
10) Family history..