Confident interpretation of Bayesian decision tree ensembles for clinical applications
Schetinin, Vitaly; Fieldsend, Jonathan E.; Partridge, Derek; et al.Coats, Timothy J.; Krzanowski, Wojtek J.; Everson, Richard M.; Bailey, Trevor C.; Hernandez, Adolfo
IEEE Transactions on Information Technology in Biomedicine
Institute of Electrical and Electronics Engineers (IEEE)
Bayesian averaging (BA) over ensembles of decision models allows evaluation of the uncertainty of decisions that is of crucial importance for safety-critical applications such as medical diagnostics. The interpretability of the ensemble can also give useful information for experts responsible for making reliable decisions. For this ...
Bayesian averaging (BA) over ensembles of decision models allows evaluation of the uncertainty of decisions that is of crucial importance for safety-critical applications such as medical diagnostics. The interpretability of the ensemble can also give useful information for experts responsible for making reliable decisions. For this reason, decision trees (DTs) are attractive decision models for experts. However, BA over such models makes an ensemble of DTs uninterpretable. In this paper, we present a new approach to probabilistic interpretation of Bayesian DT ensembles. This approach is based on the quantitative evaluation of uncertainty of the DTs, and allows experts to find a DT that provides a high predictive accuracy and confident outcomes. To make the BA over DTs feasible in our experiments, we use a Markov Chain Monte Carlo technique with a reversible jump extension. The results obtained from clinical data show that in terms of predictive accuracy, the proposed method outperforms the maximum a posteriori (MAP) method that has been suggested for interpretation of DT ensembles.
College of Engineering, Mathematics and Physical Sciences
Item views 0
Full item downloads 0
Showing items related by title, author, creator and subject.
Rose, DC; Sutherland, WJ; Parker, C; et al. (Elsevier Masson, 29 September 2016)Decision support tools, usually considered to be software-based, may be an important part of the quest for evidence-based decision-making in agriculture to improve productivity and environmental outputs. These tools can ...
Decision making and referral from primary care for possible lung and colorectal cancer: a qualitative study of patients' experiences Banks, J; Walter, FM; Hall, N; et al. (Royal College of General Practitioners, 1 December 2014)BACKGROUND: The challenge for GPs when assessing whether to refer a patient for cancer investigation is that many cancer symptoms are also caused by benign self-limiting illness. UK National Institute for Health and Care ...
Exploring GPs' experiences of using diagnostic tools for cancer: a qualitative study in primary care Green, T; Martins, T; Hamilton, W; et al. (Oxford University Press (OUP), 1 February 2015)BACKGROUND: The UK has an estimated 5-10000 extra cancer deaths each year when compared to other European countries and diagnostic delays are thought to make a significant contribution to this. One of the initiatives in ...