Argumentation-based explanations of multimorbidity treatment plans

Qurat-ul-ain Shaheen; Alice Toniolo; Juliana Kuster Filipe Bowles

doi:10.1007/978-3-030-69322-0_29

Argumentation-based explanations of multimorbidity treatment plans

Qurat-ul-ain Shaheen, Alice Toniolo, Juliana Kuster Filipe Bowles

School of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

17 Downloads (Pure)

Abstract

We present an argumentation model to explain the optimal treatment plans recommended by a Satisfiability Modulo Theories solver for multimorbid patients. The resulting framework can be queried to obtain supporting reasons for nodes on a path following a model of argumentation schemes. The modelling approach is generic and can be used for justifying similar sequences.

Original language	English
Title of host publication	PRIMA 2020: Principles and Practice of Multi-Agent Systems
Subtitle of host publication	23rd International Conference, Nagoya, Japan, November 18–20, 2020, Proceedings
Editors	Takahiro Uchiya, Quan Bai, Iván Marsá Maestre
Place of Publication	Cham
Publisher	Springer
Pages	394-402
Number of pages	9
ISBN (Electronic)	9783030693220
ISBN (Print)	9783030693213
DOIs	https://doi.org/10.1007/978-3-030-69322-0_29
Publication status	Published - 2021
Event	23rd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2020 - Online Duration: 18 Nov 2020 → 20 Nov 2020 Conference number: 23 http://uchiya.web.nitech.ac.jp/prima2020/index.html

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12568 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	23rd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2020
Abbreviated title	PRIMA 2020
Period	18/11/20 → 20/11/20
Internet address	http://uchiya.web.nitech.ac.jp/prima2020/index.html

Keywords

Multimorbidity
Argumentation schemes
SMT solvers

Access to Document

10.1007/978-3-030-69322-0_29

PRIMA_Argumentation
Copyright © 2021 Springer Nature Switzerland AG. This work has been made available online in accordance with publisher policies or with permission. Permission for further reuse of this content should be sought from the publisher or the rights holder. This is the author created accepted manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1007/978-3-030-69322-0_29.
Accepted author manuscript, 380 KB

Cite this

Shaheen, Q., Toniolo, A., & Kuster Filipe Bowles, J. (2021). Argumentation-based explanations of multimorbidity treatment plans. In T. Uchiya, Q. Bai, & I. M. Maestre (Eds.), PRIMA 2020: Principles and Practice of Multi-Agent Systems: 23rd International Conference, Nagoya, Japan, November 18–20, 2020, Proceedings (pp. 394-402). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12568 LNCS). Springer. https://doi.org/10.1007/978-3-030-69322-0_29

Shaheen, Qurat-ul-ain ; Toniolo, Alice ; Kuster Filipe Bowles, Juliana. / Argumentation-based explanations of multimorbidity treatment plans. PRIMA 2020: Principles and Practice of Multi-Agent Systems: 23rd International Conference, Nagoya, Japan, November 18–20, 2020, Proceedings. editor / Takahiro Uchiya ; Quan Bai ; Iván Marsá Maestre. Cham : Springer, 2021. pp. 394-402 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Shaheen, Q, Toniolo, A & Kuster Filipe Bowles, J 2021, Argumentation-based explanations of multimorbidity treatment plans. in T Uchiya, Q Bai & IM Maestre (eds), PRIMA 2020: Principles and Practice of Multi-Agent Systems: 23rd International Conference, Nagoya, Japan, November 18–20, 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12568 LNCS, Springer, Cham, pp. 394-402, 23rd International Conference on Principles and Practice of Multi-Agent Systems, PRIMA 2020, 18/11/20. https://doi.org/10.1007/978-3-030-69322-0_29

Argumentation-based explanations of multimorbidity treatment plans. / Shaheen, Qurat-ul-ain; Toniolo, Alice ; Kuster Filipe Bowles, Juliana.
PRIMA 2020: Principles and Practice of Multi-Agent Systems: 23rd International Conference, Nagoya, Japan, November 18–20, 2020, Proceedings. ed. / Takahiro Uchiya; Quan Bai; Iván Marsá Maestre. Cham: Springer, 2021. p. 394-402 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 12568 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Toniolo, Alice

AU - Kuster Filipe Bowles, Juliana

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AB - We present an argumentation model to explain the optimal treatment plans recommended by a Satisfiability Modulo Theories solver for multimorbid patients. The resulting framework can be queried to obtain supporting reasons for nodes on a path following a model of argumentation schemes. The modelling approach is generic and can be used for justifying similar sequences.

KW - Multimorbidity

KW - Argumentation schemes

KW - SMT solvers

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Shaheen Q, Toniolo A , Kuster Filipe Bowles J. Argumentation-based explanations of multimorbidity treatment plans. In Uchiya T, Bai Q, Maestre IM, editors, PRIMA 2020: Principles and Practice of Multi-Agent Systems: 23rd International Conference, Nagoya, Japan, November 18–20, 2020, Proceedings. Cham: Springer. 2021. p. 394-402. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Epub 2021 Feb 14. doi: 10.1007/978-3-030-69322-0_29

Argumentation-based explanations of multimorbidity treatment plans

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