Zebra: searching for rare diseases: a case of task-based search in the medical domain

TY - GEN

T1 - Zebra: searching for rare diseases

T2 - Task Based and Aggregated Search Workshop

AU - Dragusin, Radu

AU - Petcu, Paula

AU - Lioma, Christina

AU - Winther, Ole

PY - 2012

Y1 - 2012

N2 - Task-based search addresses situations where standard off-the-shelf Information Retrieval (IR) technology may not suffice to satisfy users in their tasks. In these situations, IR systems should be tailored to the user’s task-specific needs and requirements. One such task is searching for rare disease diagnostic hypotheses in the domain of medical IR. In this work, we build upon an existing vertical medical search engine, Zebra, that is focused on rare disease diagnosis. In previous work, Zebra has been evaluated using real-life medical cases of rare and difficult diseases, and has been found to be a useful and competitive tool for clinicians. In this work, we extend Zebra’s functionalities to optimise the task of medical diagnosis through search as follows: we add the option of grouping retrieved documents into clusters based on disease name occurrence, and we offer a ‘disease-ranking’ option, in addition to the standard ‘document-ranking’ option. This paper presents and discusses these functionalities.

AB - Task-based search addresses situations where standard off-the-shelf Information Retrieval (IR) technology may not suffice to satisfy users in their tasks. In these situations, IR systems should be tailored to the user’s task-specific needs and requirements. One such task is searching for rare disease diagnostic hypotheses in the domain of medical IR. In this work, we build upon an existing vertical medical search engine, Zebra, that is focused on rare disease diagnosis. In previous work, Zebra has been evaluated using real-life medical cases of rare and difficult diseases, and has been found to be a useful and competitive tool for clinicians. In this work, we extend Zebra’s functionalities to optimise the task of medical diagnosis through search as follows: we add the option of grouping retrieved documents into clusters based on disease name occurrence, and we offer a ‘disease-ranking’ option, in addition to the standard ‘document-ranking’ option. This paper presents and discusses these functionalities.

M3 - Article in proceedings

SP - 36

EP - 39

BT - Proceedings of the ECIR 2012 Workshop on Task-Based and Aggregated Search (TBAS2012)

A2 - Larsen, Birger

A2 - Lioma, Christina

A2 - de Vries, Arjen

Y2 - 1 April 2012

ER -