A constraint-based approach for the conciliation of clinical guidelines

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Abstract

The medical domain often arises new challenges to Artificial Intelligence. An emerging challenge is the support for the treatment of patients affected by multiple pathologies (comorbid patients). In the medical context, clinical practice guidelines (CPGs) are usually adopted to provide physicians with evidence-based recommendations, considering only single pathologies. To support physicians in the treatment of comorbid patients, suitable methodologies must be devised to “merge” CPGs. Techniques like replanning or scheduling, traditionally adopted in AI to “merge” plans, must be extended and adapted to fit the requirements of the medical domain. In this paper, we propose a novel methodology, that we term “conciliation”, to merge multiple CPGs, supporting the treatments of comorbid patients.

Lingua originaleInglese
Titolo della pubblicazione ospiteAdvances in Artificial Intelligence - IBERAMIA 2016 - 15th Ibero-American Conference on AI 2016, Proceedings
EditorHugo Jair Escalante, Manuel Montes-y-Gomez, Alberto Segura, Juan de Dios Murillo
EditoreSpringer Verlag
Pagine77-88
Numero di pagine12
ISBN (stampa)9783319479545
DOI
Stato di pubblicazionePubblicato - 2016
Evento15th Ibero-American Conference on Advances in Artificial Intelligence, IBERAMIA 2016 - San Jose, Costa Rica
Durata: 23 nov 201625 nov 2016

Serie di pubblicazioni

NomeLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10022 LNAI
ISSN (stampa)0302-9743
ISSN (elettronico)1611-3349

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???event.eventtypes.event.conference???15th Ibero-American Conference on Advances in Artificial Intelligence, IBERAMIA 2016
Paese/TerritorioCosta Rica
CittàSan Jose
Periodo23/11/1625/11/16

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