Missing data imputation in longitudinal cohort studies - Application of PLANN-ARD in breast cancer survival

Ana S. Fernandes; Ian H. Jarman; Terence A. Etchells; José M. Fonseca; Elia Biganzoli; Chris Bajdik; Paulo J G Lisboa

doi:10.1109/ICMLA.2008.106

Missing data imputation in longitudinal cohort studies - Application of PLANN-ARD in breast cancer survival

Ana S. Fernandes, Ian H. Jarman, Terence A. Etchells, José M. Fonseca, Elia Biganzoli, Chris Bajdik, Paulo J G Lisboa

Fondazione IRCCS Istituto Nazionale dei Tumori

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

Abstract

Missing values are common in medical datasets and may be amenable to data imputation when modelling a given data set or validating on an external cohort. This paper discusses model averaging over samples of the imputed distribution and extends this approach to generic non-linear modelling with the Partial Logistic Artificial Neural Network (PLANN) regularised within the evidence-based framework with Automatic Relevance Determination (ARD), The study then applies the imputation to external validation over new patient cohorts, considering also the case of predictions made for individual patients. A prognostic index is defined for the non-linear model and validation results show that 4 statistically significant risk groups identified at the 95% level of confidence from the modelling data, from Christie Hospital (n=931), retain good separation during external validation with data from the British Columbia Cancer Agency (n=4, 083).

Original language	English
Title of host publication	Proceedings - 7th International Conference on Machine Learning and Applications, ICMLA 2008
Pages	644-649
Number of pages	6
DOIs	https://doi.org/10.1109/ICMLA.2008.106
Publication status	Published - 2008
Event	7th International Conference on Machine Learning and Applications, ICMLA 2008 - San Diego, CA, United States Duration: Dec 11 2008 → Dec 13 2008

Other

Other	7th International Conference on Machine Learning and Applications, ICMLA 2008
Country/Territory	United States
City	San Diego, CA
Period	12/11/08 → 12/13/08

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Software

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10.1109/ICMLA.2008.106

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Fernandes, A. S., Jarman, I. H., Etchells, T. A., Fonseca, J. M., Biganzoli, E., Bajdik, C., & Lisboa, P. J. G. (2008). Missing data imputation in longitudinal cohort studies - Application of PLANN-ARD in breast cancer survival. In Proceedings - 7th International Conference on Machine Learning and Applications, ICMLA 2008 (pp. 644-649). [4725043] https://doi.org/10.1109/ICMLA.2008.106

Missing data imputation in longitudinal cohort studies - Application of PLANN-ARD in breast cancer survival. / Fernandes, Ana S.; Jarman, Ian H.; Etchells, Terence A.; Fonseca, José M.; Biganzoli, Elia; Bajdik, Chris; Lisboa, Paulo J G.

Proceedings - 7th International Conference on Machine Learning and Applications, ICMLA 2008. 2008. p. 644-649 4725043.

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

Fernandes, AS, Jarman, IH, Etchells, TA, Fonseca, JM, Biganzoli, E, Bajdik, C & Lisboa, PJG 2008, Missing data imputation in longitudinal cohort studies - Application of PLANN-ARD in breast cancer survival. in Proceedings - 7th International Conference on Machine Learning and Applications, ICMLA 2008., 4725043, pp. 644-649, 7th International Conference on Machine Learning and Applications, ICMLA 2008, San Diego, CA, United States, 12/11/08. https://doi.org/10.1109/ICMLA.2008.106

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Missing data imputation in longitudinal cohort studies - Application of PLANN-ARD in breast cancer survival

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