His primary areas of investigation include Artificial intelligence, Expert system, Mycin, Inference and Legal expert system. His studies in Artificial intelligence integrate themes in fields like Automated theorem proving, Negation and Natural language processing. The study incorporates disciplines such as Heuristic programming and Operations research in addition to Expert system.
His Mycin research includes elements of Management science, Antimicrobial, Selection, Knowledge base and Information system. Bruce G. Buchanan has researched Legal expert system in several fields, including Rule based expert system, Engineering management and Rule-based system. His Rule-based system research is multidisciplinary, incorporating perspectives in Model-based reasoning and Knowledge acquisition.
Artificial intelligence, Machine learning, Expert system, Inference and Knowledge management are his primary areas of study. In his research, Knowledge extraction is intimately related to Domain, which falls under the overarching field of Artificial intelligence. The Expert system study which covers Knowledge acquisition that intersects with Knowledge engineering.
His Inference study combines topics in areas such as Computer program, Applications of artificial intelligence and Mass spectrum. The Knowledge management study combines topics in areas such as Mycin and Knowledge base. The various areas that Bruce G. Buchanan examines in his Knowledge base study include Domain knowledge and Knowledge-based systems.
Bruce G. Buchanan mainly focuses on Artificial intelligence, Machine learning, World Wide Web, Relevance and Publishing. Bruce G. Buchanan has included themes like Reminiscence, Process and Natural language processing in his Artificial intelligence study. His Machine learning research is multidisciplinary, incorporating elements of Domain, Data mining, Knowledge extraction and Protein crystallization.
His Relevance study integrates concerns from other disciplines, such as Crawling, Task and Service. In his work, Expert system is strongly intertwined with Rule-based system, which is a subfield of Rule based expert system. His Expert system course of study focuses on Knowledge-based systems and Mycin.
His scientific interests lie mostly in Software engineering, Artificial intelligence, Rule based expert system, Legal expert system and Expert system. His biological study spans a wide range of topics, including Computational biology and Pattern recognition. His Rule based expert system research includes themes of Class, Key and Knowledge engineer.
His Key research incorporates elements of Intelligent decision support system, Mycin, Knowledge management and Rule-based system. His studies deal with areas such as Tacit knowledge, Engineering management and Knowledge-based systems as well as Expert system. His Knowledge representation and reasoning research is multidisciplinary, relying on both Field, Automated theorem proving, Inference and Language understanding.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Rule-based expert systems : the MYCIN experiments of the Stanford Heuristic Programming Project
Bruce G. Buchanan;Edward Hance Shortliffe.
Rule-Based Expert Systems
Bruce G. Buchanan;Edward H. Shortliffe;Barclay Adams;John J. Osborn.
A model of inexact reasoning in medicine
E. H. Shortliffe;B. G. Buchanan.
A simple algorithm for identifying negated findings and diseases in discharge summaries
Wendy Webber Chapman;Will Bridewell;Paul Hanbury;Gregory F. Cooper.
Journal of Biomedical Informatics (2001)
Production rules as a representation for a knowledge-based consultation program
Randall Davis;Bruce Buchanan;Edward Shortliffe.
Rule Based Expert Systems: The Mycin Experiments of the Stanford Heuristic Programming Project (The Addison-Wesley series in artificial intelligence)
Bruce G. Buchanan;Edward H. Shortliffe.
DENDRAL and Meta-DENDRAL: their applications dimension
Bruce G. Buchanan;Edward A. Feigenbaum.
Computation & intelligence (1995)
Applications of Artificial Intelligence for Organic Chemistry: The DENDRAL Project
Robert K. Lindsay;Bruce G. Buchanan;E. A. Feigenbaum;Joshua Lederberg.
Physicians' information needs: analysis of questions posed during clinical teaching.
Jerome A. Osheroff;Diana E. Forsythe;Bruce G. Buchanan;Richard A. Bankowitz.
Annals of Internal Medicine (1991)
Knowledge engineering for medical decision making: A review of computer-based clinical decision aids
E.H. Shortliffe;B.G. Buchanan;E.A. Feigenbaum.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: