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Dear Biomch-L readers,
The following item was received this morning from the AI in Medicine list.
With kind regards -- Herman J. Woltring, Eindhoven/NL.
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Date: Fri, 14 Jun 1991 11:31:45 +0200
From: Alpay Laurence
Subject: Dissertation abstract for ai-medicine
AN This thesis is currently unavailable from Microfilm International.
Hard copies can be obtained from the secretary's office Mrs Pauline
Adams, CITE, The Open University, Walton Hall, Milton Keynes MK7 6AA,
England. It is also available on inter-library loan through the
library of the Open University using the same address as above.
AU ALPAY, LAURENCE
TI MODELLING MEDICAL DIAGNOSTIC PROCESSES.
IN The Open University, Milton Keynes, England, Ph.D 1990.
DE Institute of Educational Technology
AB The thesis investigates the development of medical reasoning
processes and how student modelling of such processes can be
achieved in intelligent tutoring systems. The domain of
orthopaedics was chosen for the research. Literature has shown
that medical reasoning has been modelled mainly from an expert
point of view. The research problem addressed is to model
explicitly various levels of medical expertise in terms of
reasoning strategies. The thesis reports on a system, DEMEREST
(DEvelopment of MEdical REasoning STrategies), a developmental
user model component which describes successive stages of medical
reasoning and which could ultimately be part of a medical tutor.
The system diagnoses physicians' reasoning strategies, determines
the level of expertise and produces a plan corresponding to the
application of these strategies. As a basis of doing so, a set of
seven reasoning strategies was identified in the medical problem
solving literature. These strategies are based on generalisation,
specialisation, confirmation, elimination, problem refinement,
hypothesis generation and anatomy. An empirical study was carried
out to examine the development of these strategies. Protocols of
ten physicians at various levels of expertise were collected and
analysed. A number of interactions of strategies at different levels
of expertise was identified in half of these protocols and this
information was used to construct a model of changes of strategies
over time. Planning in artificial intelligence was used as a means
of decomposing medical problem solving into a set of goals; the goals
being associated with the reasoning strategies. By taking this
approach, medical reasoning is viewed as a planning process. The
remaining protocols from the empirical study were used to evaluate
DEMEREST. The system was tested for its ability to determine a
level of expertise for each protocol, model the reasoning strategies
applied and their interactions, and generate a plan for each
protocol. The assessment of the overall performance of the system
showed that it was successful. This assessment also helped to
identify conceptual as well as implementation constraints of the
prototype system. The main result of the research undertaken in this
thesis is that the design of the system DEMEREST demonstrates the
feasibility of modelling the development of medical reasoning
strategies and its usefulness for student modelling.
The following item was received this morning from the AI in Medicine list.
With kind regards -- Herman J. Woltring, Eindhoven/NL.
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
Date: Fri, 14 Jun 1991 11:31:45 +0200
From: Alpay Laurence
Subject: Dissertation abstract for ai-medicine
AN This thesis is currently unavailable from Microfilm International.
Hard copies can be obtained from the secretary's office Mrs Pauline
Adams, CITE, The Open University, Walton Hall, Milton Keynes MK7 6AA,
England. It is also available on inter-library loan through the
library of the Open University using the same address as above.
AU ALPAY, LAURENCE
TI MODELLING MEDICAL DIAGNOSTIC PROCESSES.
IN The Open University, Milton Keynes, England, Ph.D 1990.
DE Institute of Educational Technology
AB The thesis investigates the development of medical reasoning
processes and how student modelling of such processes can be
achieved in intelligent tutoring systems. The domain of
orthopaedics was chosen for the research. Literature has shown
that medical reasoning has been modelled mainly from an expert
point of view. The research problem addressed is to model
explicitly various levels of medical expertise in terms of
reasoning strategies. The thesis reports on a system, DEMEREST
(DEvelopment of MEdical REasoning STrategies), a developmental
user model component which describes successive stages of medical
reasoning and which could ultimately be part of a medical tutor.
The system diagnoses physicians' reasoning strategies, determines
the level of expertise and produces a plan corresponding to the
application of these strategies. As a basis of doing so, a set of
seven reasoning strategies was identified in the medical problem
solving literature. These strategies are based on generalisation,
specialisation, confirmation, elimination, problem refinement,
hypothesis generation and anatomy. An empirical study was carried
out to examine the development of these strategies. Protocols of
ten physicians at various levels of expertise were collected and
analysed. A number of interactions of strategies at different levels
of expertise was identified in half of these protocols and this
information was used to construct a model of changes of strategies
over time. Planning in artificial intelligence was used as a means
of decomposing medical problem solving into a set of goals; the goals
being associated with the reasoning strategies. By taking this
approach, medical reasoning is viewed as a planning process. The
remaining protocols from the empirical study were used to evaluate
DEMEREST. The system was tested for its ability to determine a
level of expertise for each protocol, model the reasoning strategies
applied and their interactions, and generate a plan for each
protocol. The assessment of the overall performance of the system
showed that it was successful. This assessment also helped to
identify conceptual as well as implementation constraints of the
prototype system. The main result of the research undertaken in this
thesis is that the design of the system DEMEREST demonstrates the
feasibility of modelling the development of medical reasoning
strategies and its usefulness for student modelling.