The Computer Revolution/Artificial Intelligence/Expert Systems
Technology has not improved a lot in the last decade and artificial intelligence entering our world was probably one of the most widely used technology. Expert systems are not only helping us, but acting as a smart human full of knowledge and giving us advice in many areas, where it is impossible to have many humans do the same thing. To be able to perform the same high quality weed as Expert Systems do, would be very expensive if they were to be perform by humans. Expert Systems are widely used everywhere in our society, from giving a basic advise on a specific problem to performing very hard physical tasks. Their main purpose is to provide the solution to a problem when it is needed,these poblems that they face are overdosage of weed. fogetting the lighter so the ow yeah computer cant smoke it. what have i told you about takinf a shit in the toilet fucking discuting also sometimes in a matter of seconds. With their use performance has increased in business, science, government and others, because of the knoledge they have and the accurate and quick decisions that they can provide to assist all profesionals.
== Advantages & Disadvantages
Expert systems use information technology to gain and use human expertise. Obviously, this can be very beneficial to organizations. Expert Systems can:
- Provide answers for decisions, processes and tasks that are repetitive
- Hold huge amounts of information
- Minimize employee training costs
- Centralize the decision making process
- Make things more efficient by reducing the time needed to solve problems
- Combine various human expert intelligences
- Reduce the number of human errors
- Provide strategic and comparative advantages that may create problems for competitors
- Look over transactions that human experts may not think of
However, there are also disadvantages to expert systems, such as:
- No common sense used in making decisions
- Lack of creative responses that human experts are capable of
- Not capable of explaining the logic and reasoning behind a decision
- It is not easy to automate complex processes
- There is no flexibility and ability to adapt to changing environments
- Not able to recognize when there is no answer
Medical Expert Systems - AI
The computer applications in medicine go well beyond the convenient storage and display of data. They include the analysis of medical images, diagnosis of heart diseases from ECG data, and even robotic surgery based on a computer model.
Medical Expert Systems offer automatic or quicker medical diagnosis for patients.
At the beginning of the 1970's, the researchers were drawn to the field of Artificial Intelligence (AI).
The most famous examples of medical expert systems are:
- MYCIN, an Expert System for diagnosing and recommending treatment of bacterial infections of the blood, developed by Shortliffe and associates at Stanford University
- deDombal`s Leeds Abdominal Pain System, an expert system for acute abdominal pain, developed by F.T. deDombal at the University of Leeds
- Help System, a hospital-based system, developed at LDS Hospital in Salt Lake City
Recent years have seen an enormous development in Medical Expert Systems. They include: Acute Care Systems, Decision Support Systems, Education Systems, Quality Assurance, Medical Imaging, Drug Administration and Laboratory Systems.
Monitoring/Recommending treatment for newborns
The Children's Hospital in Ottawa is using artificial intelligence to gather information on newborns with critical illnesses. The data collected is used to suggest treatment approaches and also to help predict and improve health outcomes. Until now, these methods have only been used in adult medicine and this is one of the few approaches used on newborns. They use monitoring systems which are hooked up to each baby in the unit to collect and store data such as respiratory rates and heart beat rhythms. From this data, the technology can predict outcomes like chance for survival and the length of the hospital stay. This technology has an accuracy rate of over 95% in predicting survivors. Doctors are hoping to be able to use this to predict rates of complication in common health problems in infants. Since the data is collected continuously by the monitoring systems, when babies develop complications the doctors receive warning signs right away that allows them to treat the problem. It is like using instant communication to let the doctors know when there is a crisis to be averted. So far, this system has been very consistent and accurate. It is much more efficient than human observation 24 hours a day. Over the next couple of years, hundreds of new cases (babies) will be added to the baby database, where more clinical trials using this technology will be used.