Finding and explaining optimal treatments

Concha Bielza; Juan A. Fernández del Pozo; Peter Lucas

doi:10.1007/978-3-540-39907-0_41

Finding and explaining optimal treatments

Concha Bielza
, Juan A. Fernández del Pozo
, Peter Lucas

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

2 Citations (Scopus)

Abstract

Influence diagrams are modern decision-theoretic representations that can be used to model medical decision-making problems. The output of evaluating an influence diagram are decision tables with optimal decision alternatives. For real-life clinical problems the resulting tables can be really big, so that understanding what they say is nearly impossible. KBM2L lists are new list-based structures suitable for minimising memory storage space of these tables, and at the same time searching for a better knowledge organisation. In this paper, we study the application of KBM2L lists for finding the optimal treatments for gastric non-Hodgkin lymphoma.

Original language	English
Title of host publication	Artificial Intelligence in Medicine
Subtitle of host publication	9th Conference on Artificial Intelligence in Medicine in Europe, AIME 2003, Protaras, Cyprus, October 18-22, 2003, Proceedings
Editors	Michel Dojat, Elpida T. Keravnou, Pedro Barahona
Place of Publication	Berlin, Heidelberg
Publisher	Springer
Pages	299-303
Number of pages	5
ISBN (Electronic)	978-3-540-39907-0
ISBN (Print)	978-3-540-20129-8
DOIs	https://doi.org/10.1007/978-3-540-39907-0_41
Publication status	Published - 2003
Externally published	Yes
Event	9th Conference on Artificial Intelligence on in Medicine in Europe, AIME 2003 - Protaras, Cyprus Duration: 18 Oct 2003 → 22 Oct 2003 Conference number: 9

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	2780
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	9th Conference on Artificial Intelligence on in Medicine in Europe, AIME 2003
Abbreviated title	AIME 2003
Country/Territory	Cyprus
City	Protaras
Period	18/10/03 → 22/10/03

Keywords

n/a OA procedure

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1007/978-3-540-39907-0_41

Cite this

Bielza, C., Fernández del Pozo, J. A., & Lucas, P. (2003). Finding and explaining optimal treatments. In M. Dojat, E. T. Keravnou, & P. Barahona (Eds.), Artificial Intelligence in Medicine: 9th Conference on Artificial Intelligence in Medicine in Europe, AIME 2003, Protaras, Cyprus, October 18-22, 2003, Proceedings (pp. 299-303). (Lecture Notes in Computer Science; Vol. 2780). Springer. https://doi.org/10.1007/978-3-540-39907-0_41

Bielza, Concha ; Fernández del Pozo, Juan A. ; Lucas, Peter. / Finding and explaining optimal treatments. Artificial Intelligence in Medicine: 9th Conference on Artificial Intelligence in Medicine in Europe, AIME 2003, Protaras, Cyprus, October 18-22, 2003, Proceedings. editor / Michel Dojat ; Elpida T. Keravnou ; Pedro Barahona. Berlin, Heidelberg : Springer, 2003. pp. 299-303 (Lecture Notes in Computer Science).

@inproceedings{1f2970816ff74a168f3cf78d80a49097,

title = "Finding and explaining optimal treatments",

abstract = "Influence diagrams are modern decision-theoretic representations that can be used to model medical decision-making problems. The output of evaluating an influence diagram are decision tables with optimal decision alternatives. For real-life clinical problems the resulting tables can be really big, so that understanding what they say is nearly impossible. KBM2L lists are new list-based structures suitable for minimising memory storage space of these tables, and at the same time searching for a better knowledge organisation. In this paper, we study the application of KBM2L lists for finding the optimal treatments for gastric non-Hodgkin lymphoma.",

keywords = "n/a OA procedure",

author = "Concha Bielza and \{Fern{\'a}ndez del Pozo\}, \{Juan A.\} and Peter Lucas",

year = "2003",

doi = "10.1007/978-3-540-39907-0\_41",

language = "English",

isbn = "978-3-540-20129-8",

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editor = "Michel Dojat and Keravnou, \{Elpida T.\} and Pedro Barahona",

booktitle = "Artificial Intelligence in Medicine",

address = "Germany",

note = "9th Conference on Artificial Intelligence on in Medicine in Europe, AIME 2003, AIME 2003 ; Conference date: 18-10-2003 Through 22-10-2003",

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Bielza, C, Fernández del Pozo, JA & Lucas, P 2003, Finding and explaining optimal treatments. in M Dojat, ET Keravnou & P Barahona (eds), Artificial Intelligence in Medicine: 9th Conference on Artificial Intelligence in Medicine in Europe, AIME 2003, Protaras, Cyprus, October 18-22, 2003, Proceedings. Lecture Notes in Computer Science, vol. 2780, Springer, Berlin, Heidelberg, pp. 299-303, 9th Conference on Artificial Intelligence on in Medicine in Europe, AIME 2003, Protaras, Cyprus, 18/10/03. https://doi.org/10.1007/978-3-540-39907-0_41

Finding and explaining optimal treatments. / Bielza, Concha; Fernández del Pozo, Juan A.; Lucas, Peter.
Artificial Intelligence in Medicine: 9th Conference on Artificial Intelligence in Medicine in Europe, AIME 2003, Protaras, Cyprus, October 18-22, 2003, Proceedings. ed. / Michel Dojat; Elpida T. Keravnou; Pedro Barahona. Berlin, Heidelberg: Springer, 2003. p. 299-303 (Lecture Notes in Computer Science; Vol. 2780).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Finding and explaining optimal treatments

AU - Bielza, Concha

AU - Fernández del Pozo, Juan A.

AU - Lucas, Peter

N1 - Conference code: 9

PY - 2003

Y1 - 2003

N2 - Influence diagrams are modern decision-theoretic representations that can be used to model medical decision-making problems. The output of evaluating an influence diagram are decision tables with optimal decision alternatives. For real-life clinical problems the resulting tables can be really big, so that understanding what they say is nearly impossible. KBM2L lists are new list-based structures suitable for minimising memory storage space of these tables, and at the same time searching for a better knowledge organisation. In this paper, we study the application of KBM2L lists for finding the optimal treatments for gastric non-Hodgkin lymphoma.

AB - Influence diagrams are modern decision-theoretic representations that can be used to model medical decision-making problems. The output of evaluating an influence diagram are decision tables with optimal decision alternatives. For real-life clinical problems the resulting tables can be really big, so that understanding what they say is nearly impossible. KBM2L lists are new list-based structures suitable for minimising memory storage space of these tables, and at the same time searching for a better knowledge organisation. In this paper, we study the application of KBM2L lists for finding the optimal treatments for gastric non-Hodgkin lymphoma.

KW - n/a OA procedure

UR - https://www.scopus.com/pages/publications/7444222913

U2 - 10.1007/978-3-540-39907-0_41

DO - 10.1007/978-3-540-39907-0_41

M3 - Conference contribution

AN - SCOPUS:7444222913

SN - 978-3-540-20129-8

T3 - Lecture Notes in Computer Science

SP - 299

EP - 303

BT - Artificial Intelligence in Medicine

A2 - Dojat, Michel

A2 - Keravnou, Elpida T.

A2 - Barahona, Pedro

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T2 - 9th Conference on Artificial Intelligence on in Medicine in Europe, AIME 2003

Y2 - 18 October 2003 through 22 October 2003

ER -

Bielza C, Fernández del Pozo JA, Lucas P. Finding and explaining optimal treatments. In Dojat M, Keravnou ET, Barahona P, editors, Artificial Intelligence in Medicine: 9th Conference on Artificial Intelligence in Medicine in Europe, AIME 2003, Protaras, Cyprus, October 18-22, 2003, Proceedings. Berlin, Heidelberg: Springer. 2003. p. 299-303. (Lecture Notes in Computer Science). doi: 10.1007/978-3-540-39907-0_41

Finding and explaining optimal treatments

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

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Cite this