Computerisation of Medical Diagnosis Information System (a Case Study of University of Ilorin Teaching Hospital – UITH)
Chapter One
AIM AND OBJECTIVES
The aim of the project is to develop an application that will assist the medical experts and technicians who are concerned with diagnosing ailments in their work for quick and efficient service delivery. The following are the objectives of this project;
- To evaluate the accuracy ofsuch computer diagnosis of diseases.
- To analyze the influence of study characteristics,and compare the accuracy of computer diagnosis of diseases with human diagnosis.
- To reduce the huge amount of money spent on purchase, maintenance and management of other diagnostic facilities.
- To critically review the contemporary literatureon computer diagnosis of diseases.
- Top analysis the difficulties and problems of existing approaches to disease diagnosis.
CHAPTER TWO
LITERATURE REVIEW
COMPUTER-AIDED DIAGNOSIS
In radiology computer-aided diagnosis (CADx), are procedures in medicine that assist doctors in the interpretation of medical images. Imaging techniques in X-ray, MRI, and Ultrasound diagnostics yield a great deal of information, which the radiologist has to analyze and evaluate comprehensively in a short time. CAD systems help scan digital images, e.g. from computed tomography, for typical appearances and to highlight conspicuous sections, such as possible diseases. (Munk et al, 1993)
CAD is a relatively young interdisciplinary technology combining elements of artificial intelligence and digital image processing with radiological image processing. A typical application is the detection of a tumor. For instance, some hospitals use CAD to support preventive medical check-ups in mammography (diagnosis of breast cancer), the detection of polyps in the colon, and lung cancer.
APPLICATIONS OF COMPUTER-AIDED DIAGNOSIS SYSTEM
CAD is used in the diagnosis of breast cancer, lung cancer, colon cancer, prostate cancer, bone metastases, coronary artery disease and congenital heart defect.
Breast cancer
CAD is used in screening mammography (X-ray examination of the female breast). Screening mammography is used for the early detection of breast cancer. CAD is especially established in US and the Netherlands and is used in addition to human evaluation, usually by a radiologist. The first CAD system for mammography was developed in a research project at the University of Chicago. Today it is commercially offered by iCAD and Hologic. There are currently some non-commercial projects being developed, such as Ashita Project, a gradient-based screening software by Alan Hshieh, as well. However, while achieving high sensitivities, CAD systems tend to have very low specificity and the benefits of using CAD remain uncertain. Some studies suggest a positive impact on mammography screening programs, but others show no improvement. A 2008 systematic review on computer-aided detection in screening mammography concluded that CAD does not have a significant effect on cancer detection rate, but does undesirably increase recall rate (i.e. the rate of false positives). However, it noted considerable heterogeneity in the impact on recall rate across studies. Procedures to evaluate mammography based on magnetic resonance imaging exist too. (Fisher et al, 2005)
Lung cancer (bronchial carcinoma)
In the diagnosis of lung cancer, computed tomography with special three-dimensional CAD systems are established and considered as gold standard.[citation needed] At this a volumetric dataset with up to 3,000 single images is prepared and analyzed. Round lesions (lung cancer, metastases and benign changes) from 1 mm are detectable. Today all well-known vendors of medical systems offer corresponding solutions.
Early detection of lung cancer is valuable. The 5-year-survival-rate of lung cancer has stagnated in the last 30 years and is now at approximately just 15%. Lung cancer takes more victims than breast cancer, prostate cancer and colon cancer together. This is due to the asymptomatic growth of this cancer. In the majority of cases it is too late for a successful therapy if the patient develops first symptoms (e.g. chronic croakiness or hemoptysis). But if the lung cancer is detected early (mostly by chance), there is a survival rate at 47% according to the American Cancer Society. At the same time the standard x-ray-examination of the lung is the most frequently x-ray examination with a 50% share. Indeed the random detection of lung cancer in the early stage (stage 1) in the x-ray image is difficult. It is a fact that round lesions vary from 5–10 mm are easily overlooked. The routine application of CAD Chest Systems may help to detect small changes without initial suspicion. Philips was the first vendor to present a CAD for early detection of round lung lesions on x-ray images.
Colon cancer
CAD is available for detection of colorectal polyps in the colon. Polyps are small growths that arise from the inner lining of the colon. CAD detects the polyps by identifying their characteristic “bump-like” shape. To avoid excessive false positives, CAD ignores the normal colon wall, including the haustral folds. In early clinical trials, CAD helped radiologists find more polyps in the colon than they found prior to using CAD. (Trost et al, 2005)
Coronary artery disease
CAD is available for the automatic detection of significant (causing more than 50% stenosis) coronary artery disease in coronary CT angiography (CCTA) studies. A low false positives rate (60-70% specificity per patient) allows using it as a computer-aided simple triage (CAST) tool distinguishing between positive and negative studies and yielding a preliminary report. This, for example, can be used for chest pain patients’ triage in an emergency setting.
Congenital heart defect
Early detection of pathology can be the difference between life and death. CADe can be done by auscultation with a digital stethoscope and specialized software, also known as Computer-aided auscultation. Murmurs, irregular heart sounds, caused by blood flowing through a defective heart, can be detected with high sensitivity and specificity. Computer-aided auscultation is sensitive to external noise and bodily sounds and requires an almost silent environment to function accurately.
Nuclear medicine
CADx is available for nuclear medicine images. Commercial CADx systems for the diagnosis of bone metastases in whole-body bone scans and coronary artery disease in myocardial perfusion images exist.
CHAPTER THREE
ANALYSIS OF THE SYSTEM
METHOD OF DATA COLLECTION
Data collection method is indispensable in any new system design. One of the methods of data collection used was personal interview.
Another method of data collection used in this project work was the review of articles and literatures on medical diagnostic techniques by consulting the school library and by browsing vital resources on the internet.
DESCRIPTION OF CURRENT PROCEDURE
The type of system in practice in this hospital is the manual system for sorting records and also for diagnosis and prescription.
In this system, the patient gets to the card room to register and given a card which will by keeping the records of such patient. When the patient gets to the doctor, he collects the patient’s card, to interview the patient be asking him/her what she/he is going through and thereafter the doctor prescribes the medication in the patients card while the patient takes the card back to the dispensary to collect his/her drugs, injection and the like.
A typical examination will include a careful healthy appraisal by an examination Physician, a healthy history of the patient and study of the patient body appearance and functions of the X RAY of the Chest area, radiographic analysis of the stool, urine and semen’s samples.
The doctor’s interest in a set of signs and symptoms may vary with difficult patient as pieces of evidences are combined to come up with a complete evaluation of a particular patient.
Diagnosis begins with the medical history and this includes details which may seem unimportant to the patient. Information sometimes can provide important clues to a physical compilation of data about a patient. The information normally includes:- the age, sex, marital status, occupation, birth place, height, weight and blood will bring to view any current or recent illness of the patient. Then how long the patient has been suffering can also be known also through the due on the interview between the doctor and the patient, the patient to these questions will bring to view any current or recent illness to discuss. The symptoms can be physical and non-physical, which may be aches, pains, projectile, vomiting e.t.c. The signs and symptoms always go together in solving a medical problems.
CHAPTER FOUR
DESIGN, IMPLEMENTATION AND DOCUMENTATION OF THE SYSTEM
DESIGN OF THE SYSTEM
Developing an expert system, the aim of this project is to develop a program which will be inform of interaction program in which the expert system will be able to ask a series of questions from the patient and the answer been supply by the patient in question.
This program is design to give logical questions and answer (i.e true or false, yes or no) to void complication since a question from the patient can lead to so many other questions but this will be limited to specific question that are necessary.
CHAPTER FIVE
SUMMARY, RECOMMENDATION AND CONCLUSION
SUMMARY
In summary an expert system is developed to solve some of the problem that may be encountered by human expert.
The system start by interrogating the patient for useful information based on the information supplied by the patient, the expert system can confirm that an individual is having an ailment.
The efficiency is achieved as a result of the various menu options that simplify the structure of the proposed system
This project showed how computer system could be used in diagnosis of diseases and drug prescription to epileptic patients without undergoing any stress which last for long period of time before a patient could even be diagnose of his/her ailment not to talk of when to commence treatment.
The project solved the problems that are usually encountered in many hospitals and medical centers in relation to disease diagnosis mechanisms or procedures. Therefore, some of the high cost and complex procedures that are formally used before in diseases diagnostic mechanisms are hoped to be simplified and subsidized with the implementation of the computer-based system proposed in this project.
EXPERIENCE GAINED
A lot of experiences were gained during this project work especially in the area of case study of this write up. I was meant to know the in details the causes of many diseases, which I have noted always abstain from it.
Also at length, I have learnt the various methods of curing the disease.
It is also a good experience to discover the system of using computer been an expert system for consulting and diagnosis of diseases in human life.
RECOMMENDATIONS
From the above analysis, it is recommended that hospital and clinic employed the use of an expert system to increase their productivity. The expert system will allow adequate and constant backing up of their files at a direct period of time in order to guide against accidental loss of data.
It is also possible to transfer a measure of intelligence from person to computer in a specific field. One of the biggest challenge to be overcome before major breakthrough are possible is the human automatic sense. In this regard, I recommended that computer be initiated to do human activities like the expert system that is developed in this project.
In conclusion the study of the existing and the proposed system discussed in chapter three suggest that the implementation of the proposed system will be more effective rather than the human expert system method.
The proposed system is able to eliminate the various problems that a pertinent may encounter in an attempt to use a doctor since the expert system can perform the work of a human expert.
Subsequently, the computer is able to ask some question and draw conclusion from the answer given as the consultation, so that a relatively junior doctor aided by the computer could be as expert as the consultant.
The problem of over tiredness, fatigue and inconsistency are overcome by the expert system, the problem of tedious work is eliminated.
CONCLUSION
In conclusion, the study of the existing and the proposed system discussed in chapter three suggest that the implementation of the proposed system will be more effective rather than the human expert system method.
The proposed system is able to eliminate the various problems that a patient may encounter in an attempt to use a doctor since the expert system can perform the work of a human expert.
Subsequently, the computer is able to ask some questions and draw conclusion from the answer given as the consultations, so that a relatively junior doctor aided by the computer could be as expert as the consultant.
The problem of over tiredness, fatigue and inconsistency are overcome b the expert system, the problems of tedious work is eliminated.
REFERENCES
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