Implementing Guideline-based, Experience-based, and Case-based approaches to enrich decision support for the management of breast cancer patients in the DESIREE project

Brigitte Seroussi, Jean-Baptiste Lamy, Naiara Muro, Nekane Larburu, Boomadevi Sekar, Gilles Guézennec, Jacques Bouaud

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

2 Citations (Scopus)

Abstract

DESIREE is a European-funded project to improve the management of primary breast cancer. We have developed three decision support systems (DSSs), a guideline-based, an experience-based, and a case-based DSSs, resp. GL-DSS, EXP-DSS, and CB-DSS, that operate simultaneously to offer an enriched multi-modal decision support to clinicians. A breast cancer knowledge model has been built to describe within a common ontology the data model and the termino-ontological knowledge used for representing breast cancer patient cases. It allows for rule-based and subsumption-based reasoning in the GL-DSS to provide best patient-centered reconciled care plans. It also allows for using semantic similarity in the retrieval algorithm implemented in the CB-DSS. Rainbow boxes are used to display patient cases similar to a given query patient. This innovative visualization technique translates the question of deciding the most appropriate treatment into a question of deciding the colour dominance among boxes.
LanguageEnglish
Title of host publicationDecision Support Systems and Education
Subtitle of host publicationHelp and Support in Healthcare
EditorsJohn Mantas, Zdenko Sonicki, Mihaela Crisan - Vida, Kristina Fister, Maria Hagglund, Aikaterini KoloKathi, Mira Hercigonja - Szekeres
Place of PublicationNetherlands
PublisherIOS Press
Pages190-194
Volume255
ISBN (Electronic)978-1-61499-921-8
ISBN (Print)978-1-61499-920-1
DOIs
Publication statusPublished - 30 Aug 2018
EventEuropean Federation for Medical Informatics (EFMI STC 2018), - Zagreb, Croatia
Duration: 15 Oct 201816 Oct 2018
https://www.efmi.org/159-stc-2018

Publication series

NameStudies in Health Technology and Informatics
PublisherIOS Press
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Conference

ConferenceEuropean Federation for Medical Informatics (EFMI STC 2018),
Abbreviated titleEFMI STC 2018
CountryCroatia
CityZagreb
Period15/10/1816/10/18
Internet address

Fingerprint

Guidelines
Breast Neoplasms
Patient-Centered Care
Semantics
Color
Therapeutics

Cite this

Seroussi, B., Lamy, J-B., Muro, N., Larburu, N., Sekar, B., Guézennec, G., & Bouaud, J. (2018). Implementing Guideline-based, Experience-based, and Case-based approaches to enrich decision support for the management of breast cancer patients in the DESIREE project. In J. Mantas, Z. Sonicki, M. Crisan - Vida, K. Fister, M. Hagglund, A. KoloKathi, & M. Hercigonja - Szekeres (Eds.), Decision Support Systems and Education: Help and Support in Healthcare (Vol. 255, pp. 190-194). (Studies in Health Technology and Informatics). Netherlands: IOS Press. https://doi.org/10.3233/978-1-61499-921-8-190
Seroussi, Brigitte ; Lamy, Jean-Baptiste ; Muro, Naiara ; Larburu, Nekane ; Sekar, Boomadevi ; Guézennec, Gilles ; Bouaud, Jacques. / Implementing Guideline-based, Experience-based, and Case-based approaches to enrich decision support for the management of breast cancer patients in the DESIREE project. Decision Support Systems and Education: Help and Support in Healthcare. editor / John Mantas ; Zdenko Sonicki ; Mihaela Crisan - Vida ; Kristina Fister ; Maria Hagglund ; Aikaterini KoloKathi ; Mira Hercigonja - Szekeres. Vol. 255 Netherlands : IOS Press, 2018. pp. 190-194 (Studies in Health Technology and Informatics).
@inproceedings{a1d67e1d39ee42b3bd1bdffc1961dd2a,
title = "Implementing Guideline-based, Experience-based, and Case-based approaches to enrich decision support for the management of breast cancer patients in the DESIREE project",
abstract = "DESIREE is a European-funded project to improve the management of primary breast cancer. We have developed three decision support systems (DSSs), a guideline-based, an experience-based, and a case-based DSSs, resp. GL-DSS, EXP-DSS, and CB-DSS, that operate simultaneously to offer an enriched multi-modal decision support to clinicians. A breast cancer knowledge model has been built to describe within a common ontology the data model and the termino-ontological knowledge used for representing breast cancer patient cases. It allows for rule-based and subsumption-based reasoning in the GL-DSS to provide best patient-centered reconciled care plans. It also allows for using semantic similarity in the retrieval algorithm implemented in the CB-DSS. Rainbow boxes are used to display patient cases similar to a given query patient. This innovative visualization technique translates the question of deciding the most appropriate treatment into a question of deciding the colour dominance among boxes.",
author = "Brigitte Seroussi and Jean-Baptiste Lamy and Naiara Muro and Nekane Larburu and Boomadevi Sekar and Gilles Gu{\'e}zennec and Jacques Bouaud",
year = "2018",
month = "8",
day = "30",
doi = "10.3233/978-1-61499-921-8-190",
language = "English",
isbn = "978-1-61499-920-1",
volume = "255",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press",
pages = "190--194",
editor = "John Mantas and Zdenko Sonicki and {Crisan - Vida}, Mihaela and Kristina Fister and Maria Hagglund and Aikaterini KoloKathi and {Hercigonja - Szekeres}, Mira",
booktitle = "Decision Support Systems and Education",
address = "Netherlands",

}

Seroussi, B, Lamy, J-B, Muro, N, Larburu, N, Sekar, B, Guézennec, G & Bouaud, J 2018, Implementing Guideline-based, Experience-based, and Case-based approaches to enrich decision support for the management of breast cancer patients in the DESIREE project. in J Mantas, Z Sonicki, M Crisan - Vida, K Fister, M Hagglund, A KoloKathi & M Hercigonja - Szekeres (eds), Decision Support Systems and Education: Help and Support in Healthcare. vol. 255, Studies in Health Technology and Informatics, IOS Press, Netherlands, pp. 190-194, European Federation for Medical Informatics (EFMI STC 2018), Zagreb, Croatia, 15/10/18. https://doi.org/10.3233/978-1-61499-921-8-190

Implementing Guideline-based, Experience-based, and Case-based approaches to enrich decision support for the management of breast cancer patients in the DESIREE project. / Seroussi, Brigitte; Lamy, Jean-Baptiste; Muro, Naiara; Larburu, Nekane; Sekar, Boomadevi; Guézennec, Gilles; Bouaud, Jacques.

Decision Support Systems and Education: Help and Support in Healthcare. ed. / John Mantas; Zdenko Sonicki; Mihaela Crisan - Vida; Kristina Fister; Maria Hagglund; Aikaterini KoloKathi; Mira Hercigonja - Szekeres. Vol. 255 Netherlands : IOS Press, 2018. p. 190-194 (Studies in Health Technology and Informatics).

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

TY - GEN

T1 - Implementing Guideline-based, Experience-based, and Case-based approaches to enrich decision support for the management of breast cancer patients in the DESIREE project

AU - Seroussi, Brigitte

AU - Lamy, Jean-Baptiste

AU - Muro, Naiara

AU - Larburu, Nekane

AU - Sekar, Boomadevi

AU - Guézennec, Gilles

AU - Bouaud, Jacques

PY - 2018/8/30

Y1 - 2018/8/30

N2 - DESIREE is a European-funded project to improve the management of primary breast cancer. We have developed three decision support systems (DSSs), a guideline-based, an experience-based, and a case-based DSSs, resp. GL-DSS, EXP-DSS, and CB-DSS, that operate simultaneously to offer an enriched multi-modal decision support to clinicians. A breast cancer knowledge model has been built to describe within a common ontology the data model and the termino-ontological knowledge used for representing breast cancer patient cases. It allows for rule-based and subsumption-based reasoning in the GL-DSS to provide best patient-centered reconciled care plans. It also allows for using semantic similarity in the retrieval algorithm implemented in the CB-DSS. Rainbow boxes are used to display patient cases similar to a given query patient. This innovative visualization technique translates the question of deciding the most appropriate treatment into a question of deciding the colour dominance among boxes.

AB - DESIREE is a European-funded project to improve the management of primary breast cancer. We have developed three decision support systems (DSSs), a guideline-based, an experience-based, and a case-based DSSs, resp. GL-DSS, EXP-DSS, and CB-DSS, that operate simultaneously to offer an enriched multi-modal decision support to clinicians. A breast cancer knowledge model has been built to describe within a common ontology the data model and the termino-ontological knowledge used for representing breast cancer patient cases. It allows for rule-based and subsumption-based reasoning in the GL-DSS to provide best patient-centered reconciled care plans. It also allows for using semantic similarity in the retrieval algorithm implemented in the CB-DSS. Rainbow boxes are used to display patient cases similar to a given query patient. This innovative visualization technique translates the question of deciding the most appropriate treatment into a question of deciding the colour dominance among boxes.

U2 - 10.3233/978-1-61499-921-8-190

DO - 10.3233/978-1-61499-921-8-190

M3 - Conference contribution

SN - 978-1-61499-920-1

VL - 255

T3 - Studies in Health Technology and Informatics

SP - 190

EP - 194

BT - Decision Support Systems and Education

A2 - Mantas, John

A2 - Sonicki, Zdenko

A2 - Crisan - Vida, Mihaela

A2 - Fister, Kristina

A2 - Hagglund, Maria

A2 - KoloKathi, Aikaterini

A2 - Hercigonja - Szekeres, Mira

PB - IOS Press

CY - Netherlands

ER -

Seroussi B, Lamy J-B, Muro N, Larburu N, Sekar B, Guézennec G et al. Implementing Guideline-based, Experience-based, and Case-based approaches to enrich decision support for the management of breast cancer patients in the DESIREE project. In Mantas J, Sonicki Z, Crisan - Vida M, Fister K, Hagglund M, KoloKathi A, Hercigonja - Szekeres M, editors, Decision Support Systems and Education: Help and Support in Healthcare. Vol. 255. Netherlands: IOS Press. 2018. p. 190-194. (Studies in Health Technology and Informatics). https://doi.org/10.3233/978-1-61499-921-8-190