Automated integration of external databases: a knowledge-based approach to enhancing rule-based expert systems.
Expert system applications in the biomedical domain have long been hampered by the difficulty inherent in maintaining and extending large knowledge bases. We have developed a knowledge-based method for automatically augmenting such knowledge bases. The method consists of automatically integrating data contained in commercially available, external, online databases with data contained in an expert system's knowledge base. We have built a prototype system, named DBX, using this technique to augment an expert system's knowledge base as a decision support aid and as a bibliographic retrieval tool. In this paper, we describe this prototype system in detail, illustrate its use, and discuss the lessons we have learned in its implementation.
Berman
L
L
Section of Pulmonary and Critical Care Medicine, Yale University School of Medicine, New Haven, Connecticut 06510.
Cullen
M
M
Miller
P L
PL
D001185:Artificial Intelligence; D001249:Asthma / Q000139:chemically induced; D003485:Cyanates / Q000009:adverse effects; D003628:Database Management Systems; D016206:Databases, Bibliographic; D004853:Epoxy Resins / Q000009:adverse effects; D005103:Expert Systems; D006801:Humans; D017953:Isocyanates; D009532:Nickel / Q000009:adverse effects; D009784:Occupational Diseases / Q000139:chemically induced; D009862:Online Systems; D010796:Phthalic Anhydrides / Q000009:adverse effects; D012985:Software Design; D001559:Benzhydryl Compounds
D003485:Cyanates; D004853:Epoxy Resins; D017953:Isocyanates; D009532:Nickel; D010796:Phthalic Anhydrides; C005752:araldite; C005969:4,4'-diphenylmethane diisocyanate; D001559:Benzhydryl Compounds; C043103:phthalic anhydride