Integrative visual data mining of biomedical data: Investigating cases in Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia

Paul Kennedy; Simeon J. Simoff; Daniel R. Catchpoole; David B. Skillicorn; Franco Ubaudi; Ahmad Al-Oqaily

doi:10.1007/978-3-540-71080-6_21

Integrative visual data mining of biomedical data: Investigating cases in Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia

Paul Kennedy, Simeon J. Simoff, Daniel R. Catchpoole, David B. Skillicorn, Franco Ubaudi, Ahmad Al-Oqaily

School of Computer, Data & Mathematical Sciences

Research output: Chapter in Book / Conference Paper › Chapter

3 Citations (Scopus)

Abstract

This chapter presents an integrative visual data mining approach towards biomedical data. This approach and supporting methodology are presented at a high level. They combine in a consistent manner a set of visualisation and data mining techniques that operate over an integrated data set of several diverse components, including medical (clinical) data, patient outcome and interview data, corresponding gene expression and SNP data, domain ontologies and health management data. The practical application of the methodology and the specific data mining techniques engaged are demonstrated on two case studies focused on the biological mechanisms of two different types of diseases: Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia, respectively. The common between the cases is the structure of the data sets.

Original language	English
Title of host publication	Visual Data Mining : Theory, Techniques and Tools for Visual Analytics
Editors	Simeon J. Simoff, Michael H. Bohlen, Arturas Mazeika
Place of Publication	Germany
Publisher	Springer
Pages	367-388
Number of pages	22
ISBN (Print)	3540710795, 9783540710790
DOIs	https://doi.org/10.1007/978-3-540-71080-6_21
Publication status	Published - 2008

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4404 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Keywords

data mining
information visualisation
medical informatics
leukaemia
chronic fatigue syndrome

UN SDGs

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

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10.1007/978-3-540-71080-6_21

Cite this

Kennedy, P., Simoff, S. J., Catchpoole, D. R., Skillicorn, D. B., Ubaudi, F., & Al-Oqaily, A. (2008). Integrative visual data mining of biomedical data: Investigating cases in Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia. In S. J. Simoff, M. H. Bohlen, & A. Mazeika (Eds.), Visual Data Mining : Theory, Techniques and Tools for Visual Analytics (pp. 367-388). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4404 LNCS). Springer. https://doi.org/10.1007/978-3-540-71080-6_21

Kennedy, Paul ; Simoff, Simeon J. ; Catchpoole, Daniel R. et al. / Integrative visual data mining of biomedical data : Investigating cases in Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia. Visual Data Mining : Theory, Techniques and Tools for Visual Analytics. editor / Simeon J. Simoff ; Michael H. Bohlen ; Arturas Mazeika. Germany : Springer, 2008. pp. 367-388 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Integrative visual data mining of biomedical data: Investigating cases in Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia",

abstract = "This chapter presents an integrative visual data mining approach towards biomedical data. This approach and supporting methodology are presented at a high level. They combine in a consistent manner a set of visualisation and data mining techniques that operate over an integrated data set of several diverse components, including medical (clinical) data, patient outcome and interview data, corresponding gene expression and SNP data, domain ontologies and health management data. The practical application of the methodology and the specific data mining techniques engaged are demonstrated on two case studies focused on the biological mechanisms of two different types of diseases: Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia, respectively. The common between the cases is the structure of the data sets.",

keywords = "data mining, information visualisation, medical informatics, leukaemia, chronic fatigue syndrome",

author = "Paul Kennedy and Simoff, {Simeon J.} and Catchpoole, {Daniel R.} and Skillicorn, {David B.} and Franco Ubaudi and Ahmad Al-Oqaily",

year = "2008",

doi = "10.1007/978-3-540-71080-6_21",

language = "English",

isbn = "3540710795",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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pages = "367--388",

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booktitle = "Visual Data Mining : Theory, Techniques and Tools for Visual Analytics",

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Kennedy, P, Simoff, SJ, Catchpoole, DR, Skillicorn, DB, Ubaudi, F & Al-Oqaily, A 2008, Integrative visual data mining of biomedical data: Investigating cases in Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia. in SJ Simoff, MH Bohlen & A Mazeika (eds), Visual Data Mining : Theory, Techniques and Tools for Visual Analytics. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4404 LNCS, Springer, Germany, pp. 367-388. https://doi.org/10.1007/978-3-540-71080-6_21

Integrative visual data mining of biomedical data: Investigating cases in Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia. / Kennedy, Paul; Simoff, Simeon J.; Catchpoole, Daniel R. et al.
Visual Data Mining : Theory, Techniques and Tools for Visual Analytics. ed. / Simeon J. Simoff; Michael H. Bohlen; Arturas Mazeika. Germany: Springer, 2008. p. 367-388 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4404 LNCS).

Research output: Chapter in Book / Conference Paper › Chapter

TY - CHAP

T1 - Integrative visual data mining of biomedical data

T2 - Investigating cases in Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia

AU - Kennedy, Paul

AU - Simoff, Simeon J.

AU - Catchpoole, Daniel R.

AU - Skillicorn, David B.

AU - Ubaudi, Franco

AU - Al-Oqaily, Ahmad

PY - 2008

Y1 - 2008

N2 - This chapter presents an integrative visual data mining approach towards biomedical data. This approach and supporting methodology are presented at a high level. They combine in a consistent manner a set of visualisation and data mining techniques that operate over an integrated data set of several diverse components, including medical (clinical) data, patient outcome and interview data, corresponding gene expression and SNP data, domain ontologies and health management data. The practical application of the methodology and the specific data mining techniques engaged are demonstrated on two case studies focused on the biological mechanisms of two different types of diseases: Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia, respectively. The common between the cases is the structure of the data sets.

AB - This chapter presents an integrative visual data mining approach towards biomedical data. This approach and supporting methodology are presented at a high level. They combine in a consistent manner a set of visualisation and data mining techniques that operate over an integrated data set of several diverse components, including medical (clinical) data, patient outcome and interview data, corresponding gene expression and SNP data, domain ontologies and health management data. The practical application of the methodology and the specific data mining techniques engaged are demonstrated on two case studies focused on the biological mechanisms of two different types of diseases: Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia, respectively. The common between the cases is the structure of the data sets.

KW - data mining

KW - information visualisation

KW - medical informatics

KW - leukaemia

KW - chronic fatigue syndrome

UR - http://handle.uws.edu.au:8081/1959.7/488963

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DO - 10.1007/978-3-540-71080-6_21

M3 - Chapter

SN - 3540710795

SN - 9783540710790

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

SP - 367

EP - 388

BT - Visual Data Mining : Theory, Techniques and Tools for Visual Analytics

A2 - Simoff, Simeon J.

A2 - Bohlen, Michael H.

A2 - Mazeika, Arturas

PB - Springer

CY - Germany

ER -

Kennedy P, Simoff SJ, Catchpoole DR, Skillicorn DB, Ubaudi F, Al-Oqaily A. Integrative visual data mining of biomedical data: Investigating cases in Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia. In Simoff SJ, Bohlen MH, Mazeika A, editors, Visual Data Mining : Theory, Techniques and Tools for Visual Analytics. Germany: Springer. 2008. p. 367-388. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-71080-6_21

Integrative visual data mining of biomedical data: Investigating cases in Chronic Fatigue Syndrome and Acute Lymphoblastic Leukaemia

Abstract

Publication series

Keywords

UN SDGs

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