- -

Personalized conciliation of clinical guidelines for comorbid patients through multi-agent planning

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Personalized conciliation of clinical guidelines for comorbid patients through multi-agent planning

Mostrar el registro sencillo del ítem

Ficheros en el ítem

dc.contributor.author Fernández-Olivares, Juan es_ES
dc.contributor.author Onaindia De La Rivaherrera, Eva es_ES
dc.contributor.author Castillo Vidal, Luis es_ES
dc.contributor.author Jordán, Jaume es_ES
dc.contributor.author Cózar, Juan es_ES
dc.date.accessioned 2020-03-30T07:22:09Z
dc.date.available 2020-03-30T07:22:09Z
dc.date.issued 2019-05 es_ES
dc.identifier.issn 0933-3657 es_ES
dc.identifier.uri http://hdl.handle.net/10251/139770
dc.description.abstract [EN] The conciliation of multiple single-disease guidelines for comorbid patients entails solving potential clinical interactions, discovering synergies in the diagnosis and the recommendations, and managing clinical equipoise situations. Personalized conciliation of multiple guidelines considering additionally patient preferences brings some further difficulties. Recently, several works have explored distinct techniques to come up with an automated process for the conciliation of clinical guidelines for comorbid patients but very little attention has been put in integrating the patient preferences into this process. In this work, a Multi-Agent Planning (MAP) framework that extends previous work on single-disease temporal Hierarchical Task Networks (HTN) is proposed for the automated conciliation of clinical guidelines with patient-centered preferences. Each agent encapsulates a single-disease Computer Interpretable Guideline (CIG) formalized as an HTN domain and conciliates the decision procedures that encode the clinical recommendations of its CIG with the decision procedures of the other agents' CIGs. During conciliation, drug-related interactions, scheduling constraints as well as redundant actions and multiple support interactions are solved by an automated planning process. Moreover, the simultaneous application of the patient preferences in multiple diseases may potentially bring about contradictory clinical decisions and more interactions. As a final step, the most adequate personalized treatment plan according to the patient preferences is selected by a Multi-Criteria Decision Making (MCDM) process. The MAP approach is tested on a case study that builds upon a simplified representation of two real clinical guidelines for Diabetes Mellitus and Arterial Hypertension. es_ES
dc.description.sponsorship This work has been partially supported by Spanish Government Projects MINECO TIN2014-55637-C2-2-R and TIN2015-71618-R. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Artificial Intelligence in Medicine es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Clinical guidelines es_ES
dc.subject Comorbidities es_ES
dc.subject Conciliation es_ES
dc.subject Patient preferences es_ES
dc.subject HTN planning es_ES
dc.subject Multi-agent planning es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Personalized conciliation of clinical guidelines for comorbid patients through multi-agent planning es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.artmed.2018.11.003 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2015-71618-R/ES/PLAN MINER:INTEGRACION DE PLANIFICACION AUTOMATICA Y MINERIA DE PROCESOS PARA EL APRENDIZAJE DE DOMINIOS DE PLANIFICACION JERARQUICA A PARTIR DE LA EXPERIENCIA ALMACENADA EN R/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2014-55637-C2-2-R/ES/GESTION DE METAS PARA AUTONOMIA A LARGO PLAZO EN CIUDADES INTELIGENTES/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Fernández-Olivares, J.; Onaindia De La Rivaherrera, E.; Castillo Vidal, L.; Jordán, J.; Cózar, J. (2019). Personalized conciliation of clinical guidelines for comorbid patients through multi-agent planning. Artificial Intelligence in Medicine. 96:167-186. https://doi.org/10.1016/j.artmed.2018.11.003 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.artmed.2018.11.003 es_ES
dc.description.upvformatpinicio 167 es_ES
dc.description.upvformatpfin 186 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 96 es_ES
dc.relation.pasarela S\375611 es_ES
dc.contributor.funder Ministerio de Economía y Empresa es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem