DIAGNOSTIC RULES GENERATOR

THE NEED TO APPLY EXPERT KNOWLEDGE IN THE INTERPRETATION OF MEDICAL IMAGERY AND SENSOR DATA IS WELL DOCUMENTED. RULE-BASED EXPERT SYSTEMS HAVE PROVEN THEIR VALUE IN SUCH APPLICATIONS AS MEDICAL EXPERTISE. MOST DIAGNOSTIC SYSTEMS MIMIC THE CONSULTING-ROOM ENVIRONMENT, ACQUIRING SYMPTOM DESCRIPTIONS AND LAB FINDINGS THROUGH DIALOG WITH THE USER. AUTOMATED DIAGNOSIS FROM IMAGERY AND ANALOG IS A MORE DIFFICULT PROBLEM. THE PROPOSED EFFORT SEEKS TO ADVANCE THE FIELD BY ADDRESSING KNOWLEDGE ACQUISITION PROBLEMS IN APPLYING EXPERT SYSTEMS TECHNOLOGY TO IMAGERY AND SIGNAL DATA. THIS PROBLEM CAN BE ADDRESSED BY AN EXPERT SYSTEM THAT WRITES RULE BASES. SIMILAR TO A KNOWLEDGE ENGINEER, A RULE-WRITING SYSTEM LEARNS WHAT THE EXPERT KNOWS. WE PROPOSE A PROGRAM OF RESEARCH TO DEVELOP A SYSTEM CALLED METARULE THAT WILL ADVANCE THE STATE-OF-THE-ART IN KNOWLEDGE BASED SYSTEMS-SPECIFICALLY, IN THE AREAS OF MACHINE LEARNING AND KNOWLEDGE REPRESENTATION; LEAD TO THE DEVELOPMENT OF A COMMERCIALLY VIABLE INDUCTIVE REASONING SYSTEM INCORPORATING THE ADVANCES REQUIRED TO DEAL WITH IMAGERY AND SIGNALS; AND ENABLE EXPERT SYSTEMS TO BE DEVELOPED THAT WOULD OTHERWISE BE INFEASIBLE--INCLUDING NON-SIGNALS EXPERT SYSTEMS.