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Journal of biomedical informatics v.75 suppl., 2017년, pp.S62 - S70   SCI SCIE
본 등재정보는 저널의 등재정보를 참고하여 보여주는 베타서비스로 정확한 논문의 등재여부는 등재기관에 확인하시기 바랍니다.

Symptom severity prediction from neuropsychiatric clinical records: Overview of 2016 CEGS N-GRID shared tasks Track 2

Filannino, Michele (University at Albany, State University of New York, Albany, NY, USA ) ; Stubbs, Amber (Simmons College, Boston, MA, USA ) ; Uzuner, Özlem (University at Albany, State University of New York, Albany, NY, USA ) ;
  • 초록  

    Abstract The second track of the CEGS N-GRID 2016 natural language processing shared tasks focused on predicting symptom severity from neuropsychiatric clinical records. For the first time, initial psychiatric evaluation records have been collected, de-identified, annotated and shared with the scientific community. One-hundred-ten researchers organized in twenty-four teams participated in this track and submitted sixty-five system runs for evaluation. The top ten teams each achieved an inverse normalized macro-averaged mean absolute error score over 0.80. The top performing system employed an ensemble of six different machine learning-based classifiers to achieve a score 0.86. The task resulted to be generally easy with the exception of two specific classes of records: records with very few but crucial positive valence signals, and records describing patients predominantly affected by negative rather than positive valence. Those cases proved to be very challenging for most of the systems. Further research is required to consider the task solved. Overall, the results of this track demonstrate the effectiveness of data-driven approaches to the task of symptom severity classification. Highlights Results from 110 researchers in 24 teams and 65 submissions. The best system performs comparably to the least experienced annotator. Positive domain symptom severity classification can be tackled automatically. Systems fail when patients show both signs of negative and positive valence. Graphical abstract [DISPLAY OMISSION]


  • 주제어

    Shared tasks .   CEGS N-GRID .   Neuropsychiatric records .   Symptom severity classification .   Clinical NLP.  

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