Learning to rate clinical concepts using simulated clinician feedback

Conference Paper
Carterette, Mohammad Alsulmi and Ben . 2017
Conference Name: 
ACM International Conference on Intelligent User Interfaces
Conference Date: 
Tuesday, March 7, 2017
Sponsoring Organization: 
Publication Abstract: 

We present a user-based model for rating concepts (i.e., words and phrases) in clinical queries based on their relevance to clinical decision making. Our approach can be adopted by information retrieval systems (e.g., search engines) to identify the most important concepts in user queries in order to better understand user intent and to improve search results. In our experiments, we examine several learning algorithms and show that by using simulated user feedback, our approach can predict the ratings of the clinical concepts in newly unseen queries with high prediction accuracy.