Literature DB >> 9397342

Representing and developing temporally abstracted knowledge as a means towards facilitating time modeling in medical decision-support systems.

C F Aliferis, G F Cooper, M E Pollack, B G Buchanan, M M Wagner.   

Abstract

The utilization of the appropriate level of temporal abstraction is an important aspect of time modeling. We discuss some aspects of the relation of temporal abstraction to important knowledge engineering parameters such as model correctness, ease of model specification, knowledge availability, query completeness, inference tractability, and semantic clarity. We propose that versatile and efficient time-modeling formalisms should encompass ways to represent and reason at more than one level of abstraction, and we discuss such a hybrid formalism. Although many research efforts have concentrated on the automation of specific temporal abstractions, much research needs to be done in understanding and developing provably optimal abstractions. We provide an initial framework for studying this problem in a manner that is independent of the particular problem domain and knowledge representation, and suggest several research challenges that appear worth pursuing.

Mesh:

Year:  1997        PMID: 9397342     DOI: 10.1016/s0010-4825(97)00013-9

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN: 0010-4825            Impact factor:   4.589


  5 in total

1.  The evaluation of a temporal reasoning system in processing clinical discharge summaries.

Authors:  Li Zhou; Simon Parsons; George Hripcsak
Journal:  J Am Med Inform Assoc       Date:  2007-10-18       Impact factor: 4.497

2.  Temporal representation design principles: an assessment in the domain of liver transplantation.

Authors:  C F Aliferis; G F Cooper
Journal:  Proc AMIA Symp       Date:  1998

3.  Mining biomedical time series by combining structural analysis and temporal abstractions.

Authors:  R Bellazzi; P Magni; C Larizza; G De Nicolao; A Riva; M Stefanelli
Journal:  Proc AMIA Symp       Date:  1998

4.  Recognizing Temporal Information in Korean Clinical Narratives through Text Normalization.

Authors:  Youngho Kim; Jinwook Choi
Journal:  Healthc Inform Res       Date:  2011-09-30

5.  A Complex Systems Approach to Causal Discovery in Psychiatry.

Authors:  Glenn N Saxe; Alexander Statnikov; David Fenyo; Jiwen Ren; Zhiguo Li; Meera Prasad; Dennis Wall; Nora Bergman; Ernestine C Briggs; Constantin Aliferis
Journal:  PLoS One       Date:  2016-03-30       Impact factor: 3.240

  5 in total

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