A CIG Integration Framework to Provide Decision Support for Comorbid Conditions Using Transaction-Based Semantics and Temporal Planning

William Van Woensel, Samina Abidi, Borna Jafarpour, Syed Sibte Raza Abidi

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

3 Citations (Scopus)

Abstract

Managing comorbid conditions, i.e., patients with multiple medical conditions, is quite challenging for Clinical Decision Support Systems (CDSS) based on computerized Clinical Practice Guidelines (CPG). In case of comorbidity, CDSS will need to recommend treatments from multiple different CPG, which may adversely interact (e.g., drug-disease interactions), or introduce inefficiencies. A-priori, static integration of computerized comorbid CPG is insufficient for clinical practice. In this paper, we present a solution for dynamic integration of CPG in response to evolving health profiles. Using Description and Transaction Logics, we define a set of CIG integration semantics for encoding integration decisions that cope with comorbidity issues at execution-time. These dynamic, transaction-based semantics are well-suited to roll back prior decisions when no longer safe or efficient; or, inversely, apply new decisions when relevant. Moreover, comorbid CIG integration should consider temporal properties of CIG tasks—at execution-time, these properties will be influenced by a range of temporal constraints. Given all temporal constraints, optimal task schedules will be calculated that will determine the feasibility of CIG integration decisions.

Original languageEnglish
Title of host publicationArtificial Intelligence in Medicine - 18th International Conference on Artificial Intelligence in Medicine, AIME 2020, Proceedings
EditorsMartin Michalowski, Robert Moskovitch
PublisherSpringer Science and Business Media Deutschland GmbH
Pages440-450
Number of pages11
ISBN (Print)9783030591366
DOIs
Publication statusPublished - 2020
Event18th International Conference on Artificial Intelligence in Medicine, AIME 2020 - Minneapolis, United States
Duration: Aug 25 2020Aug 28 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12299 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Artificial Intelligence in Medicine, AIME 2020
Country/TerritoryUnited States
CityMinneapolis
Period8/25/208/28/20

Bibliographical note

Publisher Copyright:
© 2020, Springer Nature Switzerland AG.

ASJC Scopus Subject Areas

  • Theoretical Computer Science
  • General Computer Science

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