Question

Expert Systems
Case Study- 1: Diagnosing Heart Diseases by Signal Processing
 
Learning Objectives:
• Know the concepts behind and application of genetic algorithm
Agent-based simulation helps Analyze Spread of a Pandemic Outbreak
Auscultation is the science of listening to the sounds of internal body organs, in this case the heart. Skilled experts can make diagnoses using this technique. It is a noninvasive screening method of providing valuable information about the conditions of the heart and its valves, but it is highly subjective and depends on the skills and experience of the listener. Researchers from the Department of Electrical & Electronic Engineering at Universiti Teknologi Petronas have developed an Exsys Corvid expert system, SIPMES (Signal Processing Module Integrated Expert System) to analyze digitally processed heart sound.
The system utilizes digitized heart sound algorithms to diagnose various conditions of the heart.
Heart sounds are effectively acquired using a digital electronic stethoscope. The heart sounds were collected from the Institut Jantung Negara (National Heart Institute) in Kuala Lumpur and the Fatimah Ipoh Hospital in Malaysia. A total of 40 patients’ age 16 to 79 years old with various pathologies were used as the control group, and to test the validity of the system using their abnormal heart sound samples and other patient medical data.
The heart sounds are transmitted using a wireless link to a nearby workstation that hosts the Signal Processing Module (SPM). The SPM has the capability to segment the stored heart sounds into individual cycles and identifies the important cardiac events.
The SPM data was then integrated with the Exsys Corvid knowledge automation expert system. The rules in the system use expert physician reasoning knowledge, combined with information acquired from medical journals, medical textbooks, and other noted publications on cardiovascular diseases (CVD). The system provides the diagnosis and generates a list of diseases arranged in descending order of their probability of occurrence.
SIPMES was designed to diagnose all types of cardiovascular heart diseases. The system can help general physicians diagnose heart diseases at the earliest possible stages under emergency situations where expert cardiologists and advanced medical facilities are not readily available.
The diagnosis made by the system has been counterchecked by senior cardiologists, and the
results coincide with these heart experts. A high coincidence factor of 74 percent has been achieved using SIPMES.
What We Can Learn from This Application Case
Many expert systems are prominently being used in the field of medicine. Many traditional diagnostic procedures are now being built into logical rule based systems, which can readily assist the medical staff in quickly diagnosing the patient's condition of disease. These expert systems can help in saving the valuable time of the medical staff and increase the number of patients being served.

 

Based on the above case studies discussion answer the following questions:
1. List the major components involved in building SIPMES and briefly comment on them.
2. You are supposed to design an expert system to diagnose a patient of Novel Cornoa Virus (Covid-19). What will be its major components? Structure your idea about “Covid-19” expert Systems

Answer 1

Hii, hope this work for you

Solution of question 1)-

Digitized heart-sound algorithms gather the heart sounds via an electronic stethoscope. A signal processing module (SPM) segments the inputs into cycles and identifies cardiac events. A rule-based Exsys Corvid expert system provides expert knowledge and reasoning along with documents from the medical literature.

Solution of question 2

An expert system is a computer system that emulates, or acts in all respects, with the decision-making capabilities of a human
expert. Its main components are: Knowledge base, it’s obtainable from books, magazines, knowledgeable persons, etc.
Inference engine, it draws conclusions from the knowledge base

the main component of this expert system that diagnose a patient of covid19 are

1) user interface

2)inference engine

3)knowledge base

The expert system accomplish diagnosis for coronavirus, can applied by display all symptoms in list and select it to analysis the disease. The expert system will ask the user to choose the symptoms that appear on human from the list. There should be a  analyze button to diagnosis the day of recognizing symptoms, survival and spread, favorable conditions and snapshot of the status after clicking on it . The expert system has been designed for change the theme for user interface like font color, background color, font name, and font size. Also, it has may form display specific format. display the basic data for the expert system such as name and image. It should display the format of the first user interface include name of expert system and whom designed it and background about the system. Also should display the format of symptoms screen that display all symptoms in the list. And display the format of result screen that include all details that diagnosis of the disease. It should display the format of screen entering details of disease along with the format of screen entering details of symptom in each day of disease occur. It should display the main page of the coronavirus expert system include the details and the important of the coronavirus expert system.