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A shared task involving multi-label classification of clinical free text

Published:29 June 2007Publication History

ABSTRACT

This paper reports on a shared task involving the assignment of ICD-9-CM codes to radiology reports. Two features distinguished this task from previous shared tasks in the biomedical domain. One is that it resulted in the first freely distributable corpus of fully anonymized clinical text. This resource is permanently available and will (we hope) facilitate future research. The other key feature of the task is that it required categorization with respect to a large and commercially significant set of labels. The number of participants was larger than in any previous biomedical challenge task. We describe the data production process and the evaluation measures, and give a preliminary analysis of the results. Many systems performed at levels approaching the inter-coder agreement, suggesting that human-like performance on this task is within the reach of currently available technologies.

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  1. A shared task involving multi-label classification of clinical free text

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        • Published in

          cover image DL Hosted proceedings
          BioNLP '07: Proceedings of the Workshop on BioNLP 2007: Biological, Translational, and Clinical Language Processing
          June 2007
          241 pages

          Publisher

          Association for Computational Linguistics

          United States

          Publication History

          • Published: 29 June 2007

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          • research-article

          Acceptance Rates

          Overall Acceptance Rate33of92submissions,36%

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