A constraint logic programming approach to identifying inconsistencies in clinical practice guidelines for patients with comorbidity

Martin Michalowski, Marisela Mainegra Hing, Szymon Wilk, Wojtek Michalowski, Ken Farion

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

This paper describes a novel methodological approach to identifying inconsistencies when concurrently using multiple clinical practice guidelines. We discuss how to construct a formal guideline model using Constraint Logic Programming, chosen for its ability to handle relationships between patient information, diagnoses, and treatment suggestions. We present methods to identify inconsistencies that are manifested by treatment-treatment and treatment-disease interactions associated with comorbidity. Using an open source constraint programming system (ECLiPSe), we demonstrate the ability of our approach to find treatment given incomplete patient data and to identify possible inconsistencies.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Medicine - 13th Conference on Artificial Intelligence in Medicine, AIME 2011, Proceedings
Pages296-301
Number of pages6
DOIs
StatePublished - 2011
Externally publishedYes
Event13th Conference on Artificial Intelligence in Medicine, AIME 2011 - Bled, Slovenia
Duration: Jul 2 2011Jul 6 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6747 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th Conference on Artificial Intelligence in Medicine, AIME 2011
Country/TerritorySlovenia
CityBled
Period7/2/117/6/11

Keywords

  • Clinical practice guideline
  • Constraint Logic Programming
  • comorbidity

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