Model checking cancer automata

Juliana Kuster Filipe Bowles; Agastya Silvina

doi:10.1109/BHI.2016.7455913

Model checking cancer automata

Juliana Kuster Filipe Bowles
, Agastya Silvina

School of Computer Science

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

Abstract

Cancer is a chronic disease where cells grow and multiply in an uncontrollable manner ultimately spreading and invading surrounding tissue, and metastasising in other parts or organs of the body. Automata can be used to capture cancer
evolving through a (discrete finite) sequence of progressive stages called phenotypes. Automata consist of states (known as hallmarks of cancer) and transitions between states, indicating a progression or regression of the cancer. We explore extensions and combinations of different variants of timed automata
and associated tools to model and analyse a model of the disease in different ways. We combine patient information and comorbidities with the cancer automaton through composition. The goal of this work is to use model checking as an analysis technique to provide further insights into the effectiveness of treatment plans for a given patient, and how these could potentially inhibit or slow down the progression of cancer.

Original language	English
Title of host publication	IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	376-379
ISBN (Electronic)	9781509024551
DOIs	https://doi.org/10.1109/BHI.2016.7455913
Publication status	Published - 18 Apr 2016
Event	3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016 - The Westin Las Vegas Hotel, Las Vegas, United States Duration: 24 Feb 2016 → 27 Feb 2016 http://bhi.embs.org/2016/

Conference

Conference	3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016
Country/Territory	United States
City	Las Vegas
Period	24/02/16 → 27/02/16
Internet address	http://bhi.embs.org/2016/

UN SDGs

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

SDG 3 Good Health and Well-being

Access to Document

10.1109/BHI.2016.7455913

BHI34JBASv2
© 2016, Publisher / the Author(s). This work is made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at ieeexplore.ieee.org /
Accepted author manuscript, 273 KB

Handle.net

Persistent link to portal record

Automated Conflict Resolution: Automated Conflic Resolution in Clinical Pathways
Bowles, J. (PI)
EPSRC
1/07/15 → 15/12/18
Project: Standard

Cite this

@inproceedings{3dcba5153ed34110970f2c1fae404d48,

title = "Model checking cancer automata",

abstract = "Cancer is a chronic disease where cells grow and multiply in an uncontrollable manner ultimately spreading and invading surrounding tissue, and metastasising in other parts or organs of the body. Automata can be used to capture cancer evolving through a (discrete finite) sequence of progressive stages called phenotypes. Automata consist of states (known as hallmarks of cancer) and transitions between states, indicating a progression or regression of the cancer. We explore extensions and combinations of different variants of timed automata and associated tools to model and analyse a model of the disease in different ways. We combine patient information and comorbidities with the cancer automaton through composition. The goal of this work is to use model checking as an analysis technique to provide further insights into the effectiveness of treatment plans for a given patient, and how these could potentially inhibit or slow down the progression of cancer. ",

author = "Bowles, \{Juliana Kuster Filipe\} and Agastya Silvina",

year = "2016",

month = apr,

day = "18",

doi = "10.1109/BHI.2016.7455913",

language = "English",

pages = "376--379",

booktitle = "IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016 ; Conference date: 24-02-2016 Through 27-02-2016",

url = "http://bhi.embs.org/2016/",

}

Bowles, JKF & Silvina, A 2016, Model checking cancer automata. in IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016., 7455913, Institute of Electrical and Electronics Engineers Inc., pp. 376-379, 3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016, Las Vegas, United States, 24/02/16. https://doi.org/10.1109/BHI.2016.7455913

TY - GEN

T1 - Model checking cancer automata

AU - Bowles, Juliana Kuster Filipe

AU - Silvina, Agastya

PY - 2016/4/18

Y1 - 2016/4/18

N2 - Cancer is a chronic disease where cells grow and multiply in an uncontrollable manner ultimately spreading and invading surrounding tissue, and metastasising in other parts or organs of the body. Automata can be used to capture cancer evolving through a (discrete finite) sequence of progressive stages called phenotypes. Automata consist of states (known as hallmarks of cancer) and transitions between states, indicating a progression or regression of the cancer. We explore extensions and combinations of different variants of timed automata and associated tools to model and analyse a model of the disease in different ways. We combine patient information and comorbidities with the cancer automaton through composition. The goal of this work is to use model checking as an analysis technique to provide further insights into the effectiveness of treatment plans for a given patient, and how these could potentially inhibit or slow down the progression of cancer.

AB - Cancer is a chronic disease where cells grow and multiply in an uncontrollable manner ultimately spreading and invading surrounding tissue, and metastasising in other parts or organs of the body. Automata can be used to capture cancer evolving through a (discrete finite) sequence of progressive stages called phenotypes. Automata consist of states (known as hallmarks of cancer) and transitions between states, indicating a progression or regression of the cancer. We explore extensions and combinations of different variants of timed automata and associated tools to model and analyse a model of the disease in different ways. We combine patient information and comorbidities with the cancer automaton through composition. The goal of this work is to use model checking as an analysis technique to provide further insights into the effectiveness of treatment plans for a given patient, and how these could potentially inhibit or slow down the progression of cancer.

U2 - 10.1109/BHI.2016.7455913

DO - 10.1109/BHI.2016.7455913

M3 - Conference contribution

SP - 376

EP - 379

BT - IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 3rd IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2016

Y2 - 24 February 2016 through 27 February 2016

ER -

Model checking cancer automata

Abstract

Conference

UN SDGs

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Projects

Automated Conflict Resolution: Automated Conflic Resolution in Clinical Pathways

Cite this