Model-Based Interpretation of Time-Varying Medical Data

Citation: Michael G. Kahn and Lewis B. Sheiner and Lewis B. Sheiner. (1989) Model-Based Interpretation of Time-Varying Medical Data. In KSL-89-34, 1989.

Publication techreport ( Edit )
type	Technical Report
bibtype	techreport
Bibtex basics
author	Michael G. Kahn and Lewis B. Sheiner and Lewis B. Sheiner
title	Model-Based Interpretation of Time-Varying Medical Data
number	KSL-89-34
institution	Knowledge Systems, AI Laboratory
address	Washington D.C.
year	1989
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abstract	Temporal concepts are critical in medical therapy-planning. If given early enough, specific therapeutic choices may abort or suppress evolving undesired changes in a patient's clinical status. Effective medical decision making demands recognition and interpretation of complex temporal changes that permeate the medical record. This paper presents a methodology for representing and using medical knowledge about temporal relationships to infer the presence of clinically relevant events, and describes a program, called TOPAZ, that uses this methodology to generate a narrative summary of such events. A unique feature of TOPAZ is the use of numeric and symbolic modeling techniques to perform temporal reasoning tasks that would be difficult to encode and perform using only one modeling methodology.

KSL Technical Report ID: KSL-89-34

Abstract	Temporal concepts are critical in medical … Temporal concepts are critical in medical therapy-planning. If given early enough, specific therapeutic choices may abort or suppress evolving undesired changes in a patient's clinical status. Effective medical decision making demands recognition and interpretation of complex temporal changes that permeate the medical record. This paper presents a methodology for representing and using medical knowledge about temporal relationships to infer the presence of clinically relevant events, and describes a program, called TOPAZ, that uses this methodology to generate a narrative summary of such events. A unique feature of TOPAZ is the use of numeric and symbolic modeling techniques to perform temporal reasoning tasks that would be difficult to encode and perform using only one modeling methodology. rform using only one modeling methodology.
Address	Washington D.C. +
Author	Michael G. Kahn and Lewis B. Sheiner and Lewis B. Sheiner +
Bibtype	techreport +
Has author	Michael G. Kahn and Lewis B. Sheiner and Lewis B. Sheiner +
Has identifier	KSL-89-34 +
Has publishing details	1989 +
Has title	Model-Based Interpretation of Time-Varying Medical Data +
Has where published	KSL-89-34 +
Has year	1989 +
Institution	Knowledge Systems, AI Laboratory +
Ksl tr id	KSL-89-34 +
Number	KSL-89-34 +
Process note	YES +
Title	Model-Based Interpretation of Time-Varying Medical Data +
Year	1989 +