Document Type
Conference Paper
Rights
This item is available under a Creative Commons License for non-commercial use only
Disciplines
1.2 COMPUTER AND INFORMATION SCIENCE
Abstract
In machine learning based clinical decision support (CDS) systems the features used to train prediction models are of paramount importance. Strong features will lead to accurate models, whereas as weak features will have the opposite effect. Feature sets can either be designed by domain experts, or automatically extracted for unstructured data that happens to be available from some process other than a CDS system. This paper compares the usefulness of structured expert-designed features to features extracted from unstructured data sources in an oncological survival prediction application scenario.
Recommended Citation
Strunkin, D., Mac Namee, B., Kelleher, J.D.:Feeling the Ambiance: Uusing Smart Ambiance to Increase Contextual Awareness in Game Agents. Proceedings of the International Conference on Information Technology: New Generations, 2012
Publication Details
Proceedings of the International Conference on Information Technology: New Generations.