3 research outputs found
Ensemble Learning of Colorectal Cancer Survival Rates
In this paper, we describe a dataset relating to cellular and physical
conditions of patients who are operated upon to remove colorectal tumours. This
data provides a unique insight into immunological status at the point of tumour
removal, tumour classification and post-operative survival. We build on
existing research on clustering and machine learning facets of this data to
demonstrate a role for an ensemble approach to highlighting patients with
clearer prognosis parameters. Results for survival prediction using 3 different
approaches are shown for a subset of the data which is most difficult to model.
The performance of each model individually is compared with subsets of the data
where some agreement is reached for multiple models. Significant improvements
in model accuracy on an unseen test set can be achieved for patients where
agreement between models is achieved.Comment: IEEE International Conference on Computational Intelligence and
Virtual Environments for Measurement Systems and Applications (CIVEMSA) 2013,
pp. 82 - 86, 201
Ensemble learning of colorectal cancer survival rates
In this paper, we describe a dataset relating to cellular and physical conditions of patients who are operated upon to remove colorectal tumours. This data provides a unique insight into immunological status at the point of tumour removal, tumour classification and post-operative survival. We build on existing research on clustering and machine learning facets of this data to demonstrate a role for an ensemble approach to highlighting patients with clearer prognosis parameters. Results for survival prediction using 3 different approaches are shown for a subset of the data which is most difficult to model. The performance of each model individually is compared with subsets of the data where some agreement is reached for multiple models. Significant improvements in model accuracy on an unseen test set can be achieved for patients where agreement between models is achieved