Overview of the CHIP2021 Shared Task 1: Classifying Positive and Negative Clinical Findings in Medical Dialog

DOI: 10.12201/bmr.202207.00010

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  Abstract: As a result of the COVID-19 outbreak, Internet-based online consultations have slowly become popular among the general public. In the doctor-patient dialogue, there is key information known as clinical findings such as abdominal pain and fever. The effective identification of the polarity (negative or positive) of these clinical findings is very important for application systems such as automatic diagnosis systems. Therefore, the 7th China Health Information Processing Conference (CHIP2021) organizes Evaluation Task 1, a medical conversation-based clinical finding negative and positive discrimination task, which provides a series of clinical findings men-tioned in doctor-patient conversations, and participants are asked to judge the mentions of these clinical findings into one of the four categories of negative, positive, other, no label. The evaluation corpus is the real data set of Springer, which has more noise. There are two lists for system evaluation, A and B. Eighty-one teams submitted results for list A, with the highest Macro-F1 value of 78.03, and 15 teams submitted results for list B, with the highest Macro-F1 value of 78.05.

  Key words: China Health Information Processing Conference; Online Consultation; Clinical finding classification

  Submit time: 4 July 2022

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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