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Expert system : Examples

Expert system : Examples. “Classic” systems. Pre-1980s Systems showed how to capture heuristic knowledge and store it; make a software that could mimic advice dispensation like expert human do. Techniques that were implemented were used in many subsequent systems,

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Expert system : Examples

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  1. Expert system : Examples

  2. “Classic” systems • Pre-1980s • Systems showed how to • capture heuristic knowledge and store it; • make a software that could mimic advice dispensation like expert human do. • Techniques that were implemented were used in many subsequent systems, • Many expert system shells were developed. CS 331/531 Dr M M Awais

  3. Expert systems • MACSYMA • advised the user on how to solve complex maths problems. • DENDRAL • advised the user on how to interpret the output from a mass spectrograph • MYCIN • PROSPECTOR • R1/XCON CS 331/531 Dr M M Awais

  4. Others • CENTAUR • INTERNIST • PUFF • CASNET • DELTA - locomotive engineering • Drilling Advisor - oilfield prospecting • ExperTax - tax minimisation advice • XSEL - computer sales All medical expert systems CS 331/531 Dr M M Awais

  5. Task Classification • Various tasks could be performed • A layout presented by Hayes-Roth & colleagues in 1983 is presented here CS 331/531 Dr M M Awais

  6. Diagnosis • finding faults in a system, or diseases in a living system MYCIN - diagnosed blood infection. Shortliffe, 1976. CS 331/531 Dr M M Awais

  7. Interpretation • The analysis of data, to determine their meaning PROSPECTOR - interpreted geological data as potential evidence for mineral deposits. Duda, Hart, et al 1976. CS 331/531 Dr M M Awais

  8. Monitoring • The continuous interpretation of signals from a system for avoiding dangerous situations NAVEX - monitored radar data and estimated the velocity and position of the space shuttle. Marsh, 1984 CS 331/531 Dr M M Awais

  9. CS 331/531 Dr M M Awais

  10. Design • To ensure production of specifications, satisfying particular requirements R1/XCON - configured VAX computer systems on the basis of customers' needs. McDermott, 1980. CS 331/531 Dr M M Awais

  11. Planning • Production of a sequence of actions that will achieve a particular goal. MOLGEN - planned chemical processes whose purpose was to analyse and synthesise DNA. Stefik, 1981. CS 331/531 Dr M M Awais

  12. CS 331/531 Dr M M Awais

  13. Instruction: Intelligent Tutoring Systems • Teaching a student a body of knowledge, varying the teaching according to assessments SOPHIE - instructed the student on the repair of an electronic power-pack. Brown, Burton & de Kleer, 1982. CS 331/531 Dr M M Awais

  14. Prediction • Forecasting future events, using a model based on past events. PLANT - predicted the damage to be expected when a corn crop was invaded by black cutworm. Boulanger, 1983. CS 331/531 Dr M M Awais

  15. CS 331/531 Dr M M Awais

  16. Debugging & repair • Generating, administering remedies for system faults. COOKER ADVISER - provides repair advice with respect to canned soup sterilising machines. Texas Instruments, 1986. CS 331/531 Dr M M Awais

  17. CS 331/531 Dr M M Awais

  18. Controls • Governing the behaviour of a system by anticipating problems, planning solutions, and monitoring actions. VENTILATOR MANAGEMENT ASSISTANT - scrutinised the data from hospital breathing-support machines, and provided accounts of the patients' conditions. Fagan, 1978. CS 331/531 Dr M M Awais

  19. MYCIN: Diagnosis System • Domain: diagnose blood infections of the sort that might be contracted in hospital • Developed by: Edward Shortliffe and colleagues, 1972 to late 1970s. CS 331/531 Dr M M Awais

  20. MYCIN • Purpose:to assist a physician, who was not an expert in the field of antibiotics, with the diagnosis & treatment of blood disorders (and in particular to establish whether the patient was suffering from a serious infection like meningitis). • Input: symptoms & test results • Output: a diagnosis, accompanied by a degree of certainty, & recommended therapy CS 331/531 Dr M M Awais

  21. MYCIN • Knowledge representation: production rules • Inference engine: Mixed chaining, but principally backward chaining from a top goal • Dealing with uncertainty: By calculating certainty factors. CS 331/531 Dr M M Awais

  22. MYCIN • A Complete system that did complex task. • Performed better than medical students and non-specialist doctors. • Performed equally good to blood infection specialist doctors • MYCIN was a laboratory demonstration only • Was never commercialised, was never marketed, or installed in a hospital and used for routine work. CS 331/531 Dr M M Awais

  23. MYCIN • Description of the system. • Written in LISP. • MYCIN was a mixed-chaining production system. CS 331/531 Dr M M Awais

  24. MYCIN • The sequence of operations was that the system asked: • Questions to get general details about the patient (name, age, sex, race, clinical test results already known). • Questions designed to find a possible, general diagnosis (e.g. the patient has probably got some form of meningitis), by forward chaining. CS 331/531 Dr M M Awais

  25. MYCIN • Questions designed to test this theory, and establish specific details, by backward chaining. This was where most of the reasoning was done. • Questions designed to produce a recommended treatment, again by forward chaining. CS 331/531 Dr M M Awais

  26. MYCIN • MYCIN could explain its reasoning in a rather simple way: • when asked "Why do you think that is the diagnosis?”, MYCIN listed the rules it had applied, in reverse order, with CFs. • When asked "Why do you want to know that?", MYCIN described the rule it was trying to execute, and what value it was trying to find. CS 331/531 Dr M M Awais

  27. MYCIN A Consultation with MYCIN @ mycin MYCIN 26-March Instructions? (Y or N) • N 26-March 10:42 -----PATIENT-1----- Patient's name: • Yousaf CS 331/531 Dr M M Awais

  28. Consultation with MYCIN Age? • 34 Sex? • Why • [i.e. Why is it important to determine the sex of PATIENT-1?] The sex of the patient is one of the four standard parameters that identify a patient. This may be useful later. CS 331/531 Dr M M Awais

  29. Consultation with MYCIN Sex? • Male Race? • Sindhi Are there any cultures for Yousaf that may be related to the present illness, and from which organisms have been grown successfully in the lab? • No CS 331/531 Dr M M Awais

  30. Consultation with MYCIN Are there any pending cultures for Yousaf? • Yes -----CULTURE-1----- From what site was the specimen for CULTURE-1 taken? • Cerebro Spinal Fluid Please give the date and time when the pending CSF culture was obtained. CS 331/531 Dr M M Awais

  31. Consultation with MYCIN • 26-March-7:00 Was a smear examined at the time the specimen was obtained? • Yes Were there any cultures seen on the smear of the specimen? • No Are there any other pending cultures? CS 331/531 Dr M M Awais

  32. Consultation with MYCIN • No Has Yousaf recently had symptoms of persistent headache or other abnormal neurological symptoms (dizziness, lethargy, etc)? • Yes Has Yousaf recently had objective evidence of abnormal neurological signs (nuchal rigidity, coma, seizures, etc) documented by a physician? CS 331/531 Dr M M Awais

  33. A Consultation with MYCIN • Yes The CSF cultures will be considered to be associated with MENINGITIS. Please give the date on which clinical evidence (symptoms, signs, or laboratory tests) of the meningitis first appeared. • 25 March 10:00 Has Yousaf had neurosurgery? CS 331/531 Dr M M Awais

  34. A Consultation with MYCIN • Why • [i.e. WHY is it important to determine whether PATIENT-1 has had neurosurgery?] This will aid in determining the organisms (other than those seen on cultures or smears) that might be causing the infection. CS 331/531 Dr M M Awais

  35. A Consultation with MYCIN It has already been established that • [1] the culture that requires therapy is meningitis, and • [2] organisms were not seen on the stain of the pending csf culture (CULTURE-1), and • [3] the type of infection is bacterial CS 331/531 Dr M M Awais

  36. A Consultation with MYCIN Therefore, if • [4] Yousaf has had neurosurgery, and • [5] the time since the neurosurgical operation is less than two months, and • [6] the type of neurosurgery is not ventricular-urethal shunt then • there is evidence that the organisms that might be causing the infection are staphylococcus-coag-pos (0.75), staphylococcus-coag-neg (.5), e.coli (.4), klebsiella (0.3) • Author: Yu [RULE511] CS 331/531 Dr M M Awais

  37. A Consultation with MYCIN Has Yousaf had neurosurgery? • How [3] • [i.e. HOW was it established that the type of infection is bacterial?] CS 331/531 Dr M M Awais

  38. A Consultation with MYCIN The following rules concluded about the likelihood that the type of infection is bacterial: Rule Yes No 500 (.4) 501 (.17) 502 (.1) 524 (.42) 504 (.28) Thus it has been established that the type of infection might be bacterial. CS 331/531 Dr M M Awais

  39. A Consultation with MYCIN Has Yousaf had neurosurgery? • No Is Yousaf a burn patient? • Yes CS 331/531 Dr M M Awais

  40. A Consultation with MYCIN I have found evidence (RULE507) that treatment should cover for Diplococcus pneumoniae causing meningitis. I have found evidence (RULE545) that treatment should cover for e.coli causing meningitis. I have found evidence (RULE545 RULE578) that treatment should cover for Pseudomonas aeruginosa causing meningitis. CS 331/531 Dr M M Awais

  41. A Consultation with MYCIN Does Yousaf have focal neurological signs? • No [Determining which dosages are desirable for use against the e.coli...] [Determining which drugs are desirable for use ...] CS 331/531 Dr M M Awais

  42. A Consultation with MYCIN INFECTION-1 is MENINGITIS + <ITEM-1> DIPLOCOCCUS-PNEUMONIAE (from clinical evidence only) + <ITEM-2> E.COLI (from clinical evidence only) + <ITEM-3> PSEUDOMONAS AERUGINOSA (from clinical evidence only) CS 331/531 Dr M M Awais

  43. A Consultation with MYCIN [REC-1] My preferred therapy recommendation is as follows: In order to cover for items <1 2 3>: Give the following in combination: 1) AMPICILLIN Dose: 3.85g(30.8ml) q4h IV 2) GENTAMICIN Dose: 131mg(3.2ml) q8h IV CS 331/531 Dr M M Awais

  44. A Consultation with MYCIN Comments: monitor serum concentrations. Since high concentrations of penicillins can inactivate aminoglycosides, do not mix these antibiotics in the same IV bottle. Do you wish to see the next choice therapy? • No CS 331/531 Dr M M Awais

  45. CROP ADVISOR • Developed by ICI (in 1989) to advise cereal grain farmers on appropriate fertilisers and pesticides for their farms. • The choice of chemical, amount, and time of application depends on such factors as crop to be grown, previous cropping, soil condition, acidity of soil, and weather. • Farmers can access the system via the internet. CS 331/531 Dr M M Awais

  46. CROP ADVISOR • Given relevant data, the system produces various financial return projections for different application rates of different chemicals. • The system uses statistical reasoning to come to these conclusions. • If the question asked is outside the system's expertise, it refers the caller to a human expert. CS 331/531 Dr M M Awais

  47. CROP ADVISOR • The chief advantages of this system have been • that employees at ICI have been relieved of the need to provide lengthy telephone advice sessions, • and the quality of the advice has become much more uniform, which has increased confidence in the company's products. CS 331/531 Dr M M Awais

  48. R1/XCON • Knowledge domain: Configuring VAX computers, to customers' specifications. • Written by: John McDermott and colleagues, 1978 - 1981 • Input: Required characteristics of the computer system. • Output: Specification for the computer system. CS 331/531 Dr M M Awais

  49. R1/XCON • Knowledge representation: Production rules. • Inference engine: Forward chaining: the output specification was assembled in working memory. • Dealing with uncertainty: No mechanism for this: the system simply assembled one answer, assumed to be good enough to do the job. CS 331/531 Dr M M Awais

  50. R1/XCON • Significance: A rather simple forward-chaining rule-based expert system, which performed well, solved a difficult manufacturing problem, and proved to be enormously profitable. CS 331/531 Dr M M Awais

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