Tim@CIS.UPENN.EDU (Tim Finin) (11/26/86)
COLLOQUIUM - UNIVERSITY of PENNSYLVANIA
3pm Tuesday, December 2, 1986
Room 216 Moore School
GRAPHICAL ACCESS TO AN EXPERT SYSTEM:
THE EVOLUTION OF THE ONCOCIN PROJECT
Ted Shortliffe
Visiting Professor of Computer and Information Science
University of Pennsylvania
and
Associate Professor of Medicine and Computer Science
Medical Computer Science Group
Knowledge Systems Laboratory
Stanford Medical School
The research goals of Stanford's Medical Computer Science group are directed
both toward the basic science of artificial intelligence and toward the
development of clinically useful consultation tools. Our approach has been
eclectic, drawing on fields such as decision analysis, interactive graphics,
and both qualitative and probabilistic simulation as well as AI. In this
presentation I will discuss ONCOCIN, an advice system designed to suggest
optimal therapy for patients undergoing cancer treatment, as well as to
assist in the data management tasks required to support research treatment
plans (protocols). A prototype version, developed in Interlisp and SAIL
on a DEC-20, was used between May 1981 and May 1985 by oncology faculty and
fellows in the Debbie Probst Oncology Day Care Center at the Stanford
University Medical Center. In recent years, however, we have spent much
of our time reimplementing ONCOCIN to run on Xerox 1100 series workstations
and to take advantage of the graphics environment provided on those
machines. The physician's interface has been redesigned to approximate the
appearance and functionality of the paper forms traditionally used for
recording patient status. The Lisp machine version of ONCOCIN was introduced
for use by Stanford physicians earlier this year.
In response to the need for an improved method for entering and maintaining
the rapidly expanding ONCOCIN protocol knowledge base, we have also developed
a graphical knowledge acquisition environment known as OPAL. This system
allows expert oncologists to directly enter their knowledge of protocol-
directed cancer therapy using graphics-based forms developed in the
Interlisp-D environment. The development of OPAL's graphical interface led
to a new understanding of the natural structure of knowledge in this domain.
ONCOCIN's knowledge representation was accordingly redesigned for the Lisp
machine environment. This has involved adopting an object-centered knowledge
base design which has provided an increase in the speed of the program while
providing more flexible access to system knowledge.