Abstract
This research aims at the design and implementation of a decision support system for the diagnoses of kidney stone to assist physicians make better decisions. Traditional electronic health records tend to display laboratory results in a piecemeal and segregated fashion and this makes the assembly and interpretation of results related to kidney stone challenging. We used the Object-Oriented Analysis and Design Methodology (OOADM) and Visual BASIC.NET as a language of implementation. The new system collects comprehensive information about kidney stone disease from a group of experts and a rule-based system is formed based on this information, which contains a set of significant symptoms relevant to the suspected disease. The medical diagnosis rules were formulated and applied by developing a new system. We defined a set of symptoms related to the set of considered disease. A group of patients were used to validate the effectiveness of the system. The results show that the system was cap
1.1    BACKGROUND OF STUDY
Blood which accounts for about 8 percent of your normal body
weight, plays an important role in how your body functions. As the blood circulates
throughout the vascular system, it supplies all other organs with oxygen,
nutrients, hormones and antibodies. Blood is made of an almost equal mix of
plasma (the liquid that transports cells, waste and nutrients, among other
things) and blood cells (red blood cells, white blood cells and platelets).
When cancer occurs in the blood, it is usually the result of
an abnormal and excessive reproduction of white blood cells. Blood cancers
account for about 10 percent of all diagnosed cancers in the U.S. each year.
Blood cancers (including leukemia, lymphoma and myeloma) are more common in men
than women. Childhood leukemia accounts for about 30 percent of all
cancers in children.
Some blood cancers may cause symptoms such as severe fatigue,
weight loss, night sweats, or lymph node swelling. Other blood cancers may show
no symptoms and slowly progress over years. Treatments for blood cancers also
vary, ranging from active surveillance without cancer-directed therapy to
standard cancer treatments including immunotherapies, chemotherapies and
targeted agents. With over 100 different types of blood cancers now recognized,
it is important to have an accurate diagnosis prior to deciding on treatment.
Cancer is the
uncontrolled growth of abnormal cells in the body. Cancerous cells are also called malignant cells. Cells are the building
blocks of living things. Cancer grows out of normal cells in the body.
Normal cells multiply when the body needs
them, and die when the body doesn’t need them. Cancer appears to occur when the growth of cells in the
body is out of control and cells divide too quickly. It can also occur
when cells forget how to die. There are many different kinds of cancers. Cancer
can develop in almost any organ or tissue, such as the lung, colon, breast, skin, bones, or nerve tissue (Patra, 2010).
ÂÂÂ
Clinical decision support systems
(CDSS) are interactive computer programs designed to assist healthcare
professionals such as physicians, physical therapists, optometrists, healthcare
scientists, dentists, pediatrists, nurse practitioners or physical assistants
with decision making skills. The clinician interacts with the software
utilizing both the clinician’s knowledge and the software to make a better
analysis of the patients’ data than neither human nor software could make on
their own.
Typically, the system makes
suggestions for the clinician to look through and then picks useful information
and removes erroneous suggestions. To diagnose a disease, a physician is
usually based on the clinical history and physical examination of the patient,
visual inspection of medical images as well as the results of laboratory tests.
In some cases, confirmation of the diagnosis is particularly difficult because
it requires specialization and experience or even the application of
interventional methodologies (e.g. biopsy) interpretation of medical images
(e.g. computed tomography, magnetic resonance, imaging, ultrasound, etc.)
usually performed by radiologists, is often limited due to the non-systematic search
patterns of humans, the presence of structure noise in the image and the
presentation of complex disease states requiring the integration of vast amount
of image and clinical information.
ÂÂÂ
Computed aided diagnosis (CAD)
defined as a diagnosis made by a physician who uses the output from a
computerized analysis of a medical data as a second opinion indicating lesions,
accessing disease severity and making diagnostic decisions, is expected to
enhance the diagnostic capabilities of physicians and reduce the time required
for accurate diagnosis. With CAD the final diagnosis is made by the physician.
In
this research, expert system was used to develop models for the rapid diagnosis
of blood cancer for medical records of patients suffering from this condition.
First, a data model was developed for symptoms and diagnosis of blood cancer
after a series of discussion with medical experts in the field on methods of
diagnosis, then expert system models were developed for the diagnosis with
expert advice on educating patients on the possible causes of blood cancer.