Modelling the Time Taken to Experience a Type 2 Diabetes Related Complication Using a Survival Tree in Order to Advise General Practitioners

Christopher J. Steele; Adele H. Marshall; Anne Kouvonen; Frank Kee; Reijo Sund

doi:10.1109/CBMS.2016.69

Modelling the Time Taken to Experience a Type 2 Diabetes Related Complication Using a Survival Tree in Order to Advise General Practitioners

Christopher J. Steele
, Adele H. Marshall
, Anne Kouvonen
, Frank Kee
, Reijo Sund

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

2 Citations (Scopus)

Abstract

Type 2 diabetes (T2D) is a major public health problem. The prevalence of the disease is growing at an alarming rate and the sharp increase in T2D shows no signs of slowing down. The increased number of T2D cases worldwide has caused a simultaneous increase in the number of T2D related complications. This paper demonstrates how a survival tree based approach can be used to enable predictions to be made concerning when an individual is expected to experience a complication of T2D. A survival tree is used to identify cohorts of individuals with significantly different survival distributions from T2D to complication. By fitting appropriate survival distributions to the individual leaves of the tree, the expected time until complication can be calculated for each group of individuals. Survival trees were built for death, stroke/acute myocardial infarction (AMI) and amputation/coronary revascularisation.

Original language	English
Title of host publication	IEEE 29th International Symposium on Computer-Based Medical Systems, CBMS 2016: Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	271-272
Number of pages	2
ISBN (Electronic)	978-1-4673-9036-1
ISBN (Print)	978-1-4673-9037-8
DOIs	https://doi.org/10.1109/CBMS.2016.69
Publication status	Published - 18 Aug 2016

Publication series

Name	IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS)
Publisher	IEEE
ISSN (Electronic)	2372-9198

UN SDGs

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

SDG 3 Good Health and Well-being

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10.1109/CBMS.2016.69Licence: Unspecified

Cite this

Steele, C. J., Marshall, A. H., Kouvonen, A., Kee, F., & Sund, R. (2016). Modelling the Time Taken to Experience a Type 2 Diabetes Related Complication Using a Survival Tree in Order to Advise General Practitioners. In IEEE 29th International Symposium on Computer-Based Medical Systems, CBMS 2016: Proceedings (pp. 271-272). (IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CBMS.2016.69

Steele, Christopher J. ; Marshall, Adele H. ; Kouvonen, Anne et al. / Modelling the Time Taken to Experience a Type 2 Diabetes Related Complication Using a Survival Tree in Order to Advise General Practitioners. IEEE 29th International Symposium on Computer-Based Medical Systems, CBMS 2016: Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 271-272 (IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS)).

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title = "Modelling the Time Taken to Experience a Type 2 Diabetes Related Complication Using a Survival Tree in Order to Advise General Practitioners",

abstract = "Type 2 diabetes (T2D) is a major public health problem. The prevalence of the disease is growing at an alarming rate and the sharp increase in T2D shows no signs of slowing down. The increased number of T2D cases worldwide has caused a simultaneous increase in the number of T2D related complications. This paper demonstrates how a survival tree based approach can be used to enable predictions to be made concerning when an individual is expected to experience a complication of T2D. A survival tree is used to identify cohorts of individuals with significantly different survival distributions from T2D to complication. By fitting appropriate survival distributions to the individual leaves of the tree, the expected time until complication can be calculated for each group of individuals. Survival trees were built for death, stroke/acute myocardial infarction (AMI) and amputation/coronary revascularisation.",

author = "Steele, \{Christopher J.\} and Marshall, \{Adele H.\} and Anne Kouvonen and Frank Kee and Reijo Sund",

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series = "IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS)",

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Steele, CJ, Marshall, AH, Kouvonen, A, Kee, F & Sund, R 2016, Modelling the Time Taken to Experience a Type 2 Diabetes Related Complication Using a Survival Tree in Order to Advise General Practitioners. in IEEE 29th International Symposium on Computer-Based Medical Systems, CBMS 2016: Proceedings. IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS), Institute of Electrical and Electronics Engineers Inc., pp. 271-272. https://doi.org/10.1109/CBMS.2016.69

Modelling the Time Taken to Experience a Type 2 Diabetes Related Complication Using a Survival Tree in Order to Advise General Practitioners. / Steele, Christopher J.; Marshall, Adele H.; Kouvonen, Anne et al.
IEEE 29th International Symposium on Computer-Based Medical Systems, CBMS 2016: Proceedings. Institute of Electrical and Electronics Engineers Inc., 2016. p. 271-272 (IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS)).

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

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T1 - Modelling the Time Taken to Experience a Type 2 Diabetes Related Complication Using a Survival Tree in Order to Advise General Practitioners

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AU - Kee, Frank

AU - Sund, Reijo

PY - 2016/8/18

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N2 - Type 2 diabetes (T2D) is a major public health problem. The prevalence of the disease is growing at an alarming rate and the sharp increase in T2D shows no signs of slowing down. The increased number of T2D cases worldwide has caused a simultaneous increase in the number of T2D related complications. This paper demonstrates how a survival tree based approach can be used to enable predictions to be made concerning when an individual is expected to experience a complication of T2D. A survival tree is used to identify cohorts of individuals with significantly different survival distributions from T2D to complication. By fitting appropriate survival distributions to the individual leaves of the tree, the expected time until complication can be calculated for each group of individuals. Survival trees were built for death, stroke/acute myocardial infarction (AMI) and amputation/coronary revascularisation.

AB - Type 2 diabetes (T2D) is a major public health problem. The prevalence of the disease is growing at an alarming rate and the sharp increase in T2D shows no signs of slowing down. The increased number of T2D cases worldwide has caused a simultaneous increase in the number of T2D related complications. This paper demonstrates how a survival tree based approach can be used to enable predictions to be made concerning when an individual is expected to experience a complication of T2D. A survival tree is used to identify cohorts of individuals with significantly different survival distributions from T2D to complication. By fitting appropriate survival distributions to the individual leaves of the tree, the expected time until complication can be calculated for each group of individuals. Survival trees were built for death, stroke/acute myocardial infarction (AMI) and amputation/coronary revascularisation.

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BT - IEEE 29th International Symposium on Computer-Based Medical Systems, CBMS 2016: Proceedings

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Steele CJ, Marshall AH, Kouvonen A, Kee F, Sund R. Modelling the Time Taken to Experience a Type 2 Diabetes Related Complication Using a Survival Tree in Order to Advise General Practitioners. In IEEE 29th International Symposium on Computer-Based Medical Systems, CBMS 2016: Proceedings. Institute of Electrical and Electronics Engineers Inc. 2016. p. 271-272. (IEEE 29th International Symposium on Computer-Based Medical Systems (CBMS)). doi: 10.1109/CBMS.2016.69

Modelling the Time Taken to Experience a Type 2 Diabetes Related Complication Using a Survival Tree in Order to Advise General Practitioners

Abstract

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UN SDGs

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