THOMAS: Building Bayesian Statistical Expert Systems to Aid in Clinical Decision Making

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KSL-90-10 +  redirect page

THOMAS: Building Bayesian Statistical Expert Systems to Aid in Clinical Decision Making +  Has identifier

THOMAS: Building Bayesian Statistical Expert Systems to Aid in Clinical Decision Making +  Ksl tr id

THOMAS: Building Bayesian Statistical Expert Systems to Aid in Clinical Decision Making +  Number

THOMAS: Building Bayesian Statistical Expert Systems to Aid in Clinical Decision Making

Bibtype  techreport

Has publishing details  1990

Has title  THOMAS: Building Bayesian Statistical Expert Systems to Aid in Clinical Decision Making

Has where published  KSL-90-10

Has year  1990

Title  THOMAS: Building Bayesian Statistical Expert Systems to Aid in Clinical Decision Making

Year  1990

Abstract  Previous knowledge-based systems for stati Previous knowledge-based systems for statistical analysis separate the numeric knowledge in the data analysis from the heuristic knowledge in using the results of the analysis. In contrast, a Bayesian framework for building biostatistical expert systems allows for the integration of the data-analytic and decision-making tasks. The architecture of such a framework entails enabling the system (1) to make its recommendations on decision-analytic grounds, (2) to update a statistical model on the basis of data from the study and the userUs prior beliefs, and (3) to construct those models dynamically. This architecture permits the knowledge engineer to represent a variety of types of statistical and domain knowledge, including methodological knowledge. Constructing such systems requires that the knowledge engineer reinterpret traditional statistical concerns, such as by replacing the notion of statistical significance with that of a pragmatic clinical threshold. The user of such a system can interact with the system at the level of general methodological concerns, rather than at the level of statistical details. We demonstrate these issues with a prototype system called THOMAS which helps a physician reader to interpret the results of a published randomized clinical trial for clinical decision making. inical trial for clinical decision making.

Address  Washington D.C. +

Author  Harold P. Lehmann and Edward H. Shortliffe +

Has author  Harold P. Lehmann and Edward H. Shortliffe +

Has identifier  THOMAS: Building Bayesian Statistical Expert Systems to Aid in Clinical Decision Making +

Institution  Knowledge Systems, AI Laboratory +

Ksl tr id  THOMAS: Building Bayesian Statistical Expert Systems to Aid in Clinical Decision Making +

Number  THOMAS: Building Bayesian Statistical Expert Systems to Aid in Clinical Decision Making +

Process note  YES +

Categories  KSL Technical Report +, Publication +, Technical Report +

 

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