A Representation for Gaining Insight into Clinical Decision Models

From Tetherless World Wiki

Jump to: navigation, search

Citation: Holly Brügge Jimison. (1988) A Representation for Gaining Insight into Clinical Decision Models. In KSL-88-75, November,1988.

Publication techreport ( Edit )
type Technical Report
bibtype techreport
Bibtex basics
author Holly Brügge Jimison
title A Representation for Gaining Insight into Clinical Decision Models
number KSL-88-75
institution Knowledge Systems, AI Laboratory
year 1988
month November
Bibtex more
note 5 pages.
Access Paper
abstract For many medical domains uncertainty and patient preferences are important components of decision making. Decision theory is useful as a representation for such medical models in computer decision aids, but the methodology has typically had poor performance in the areas of explanation and user interface. The additional representation of probabilities and utilities as random variables serves to provide a framework for graphical and text insight into complicated decision models. The approach allows for efficient customization of a generic model that describes the general patient population of interest to a patient-specific model. Monte Carlo simulation is used to calculate the expected value of information and sensitivity for each model variable, thus providing a metric for deciding what to emphasize in the graphics and text summary. The computer-generated explanation includes variables that are sensitive with respect to the decision or that deviate significantly from what is typically observed. These techniques serve to keep the assessment and explanation of the patient's decision model concise, allowing the user to focus on the most important aspects for that patient.

KSL Technical Report ID: KSL-88-75
Facts about A Representation for Gaining Insight into Clinical Decision ModelsRDF feed
Abstract For many medical domains uncertainty and p … For many medical domains uncertainty and patient preferences are important components of decision making. Decision theory is useful as a representation for such medical models in computer decision aids, but the methodology has typically had poor performance in the areas of explanation and user interface. The additional representation of probabilities and utilities as random variables serves to provide a framework for graphical and text insight into complicated decision models. The approach allows for efficient customization of a generic model that describes the general patient population of interest to a patient-specific model. Monte Carlo simulation is used to calculate the expected value of information and sensitivity for each model variable, thus providing a metric for deciding what to emphasize in the graphics and text summary. The computer-generated explanation includes variables that are sensitive with respect to the decision or that deviate significantly from what is typically observed. These techniques serve to keep the assessment and explanation of the patient's decision model concise, allowing the user to focus on the most important aspects for that patient. e most important aspects for that patient.
Author Holly Brügge Jimison  +
Bibtype techreport  +
Has author Holly Brügge Jimison  +
Has identifier KSL-88-75  +
Has publishing details November,1988  +
Has title A Representation for Gaining Insight into Clinical Decision Models  +
Has where published KSL-88-75  +
Has year 1988  +
Institution Knowledge Systems, AI Laboratory  +
Ksl tr id KSL-88-75  +
Month November  +
Note 5 pages.
Number KSL-88-75  +
Process note YES  +
Title A Representation for Gaining Insight into Clinical Decision Models  +
Year 1988  +
Retrieved from "http://tw.rpi.edu/wiki/A_Representation_for_Gaining_Insight_into_Clinical_Decision_Models"
Personal tools