Meliha Yetisgen-Yildiz

Summary

Publications

  1. doi request reprint A text processing pipeline to extract recommendations from radiology reports
    Meliha Yetisgen-Yildiz
    Biomedical and Health Informatics, School of Medicine, University of Washington, Seattle, WA, United States
    J Biomed Inform 46:354-62. 2013
  2. pmc Automatic identification of critical follow-up recommendation sentences in radiology reports
    Meliha Yetisgen-Yildiz
    Biomedical and Health Informatics, School of Medicine, University of Washington, Seattle, WA, USA
    AMIA Annu Symp Proc 2011:1593-602. 2011
  3. doi request reprint Assertion modeling and its role in clinical phenotype identification
    Cosmin Adrian Bejan
    Biomedical and Health Informatics, University of Washington, Seattle, WA 98195 7240, United States
    J Biomed Inform 46:68-74. 2013
  4. pmc Assessing pneumonia identification from time-ordered narrative reports
    Cosmin A Bejan
    Biomedical and Health Informatics, School of Medicine, University of Washington, Seattle, WA, USA
    AMIA Annu Symp Proc 2012:1119-28. 2012
  5. pmc Pneumonia identification using statistical feature selection
    Cosmin Adrian Bejan
    Department of Biomedical and Health Informatics, School of Medicine, University of Washington, Seattle, Washington 98195 7240, USA
    J Am Med Inform Assoc 19:817-23. 2012
  6. ncbi request reprint Using statistical and knowledge-based approaches for literature-based discovery
    Meliha Yetisgen-Yildiz
    Information School, University of Washington, Seattle, WA, USA
    J Biomed Inform 39:600-11. 2006

Detail Information

Publications6

  1. doi request reprint A text processing pipeline to extract recommendations from radiology reports
    Meliha Yetisgen-Yildiz
    Biomedical and Health Informatics, School of Medicine, University of Washington, Seattle, WA, United States
    J Biomed Inform 46:354-62. 2013
    ..Our fully statistical approach achieved the best f-score 0.758 in identifying the critical recommendation sentences in radiology reports...
  2. pmc Automatic identification of critical follow-up recommendation sentences in radiology reports
    Meliha Yetisgen-Yildiz
    Biomedical and Health Informatics, School of Medicine, University of Washington, Seattle, WA, USA
    AMIA Annu Symp Proc 2011:1593-602. 2011
    ..We applied 5-fold cross validation and our best performing classifier achieved 95.60% precision, 79.82% recall, 87.0% F-score, and 99.59% classification accuracy in identifying the critical recommendation sentences in radiology reports...
  3. doi request reprint Assertion modeling and its role in clinical phenotype identification
    Cosmin Adrian Bejan
    Biomedical and Health Informatics, University of Washington, Seattle, WA 98195 7240, United States
    J Biomed Inform 46:68-74. 2013
    ..Furthermore, we confirm the intuition that assertion classification contributes in significantly improving the results of phenotype identification from free-text clinical records...
  4. pmc Assessing pneumonia identification from time-ordered narrative reports
    Cosmin A Bejan
    Biomedical and Health Informatics, School of Medicine, University of Washington, Seattle, WA, USA
    AMIA Annu Symp Proc 2012:1119-28. 2012
    ..Our system achieves significantly better results when compared with a baseline previously proposed for pneumonia identification...
  5. pmc Pneumonia identification using statistical feature selection
    Cosmin Adrian Bejan
    Department of Biomedical and Health Informatics, School of Medicine, University of Washington, Seattle, Washington 98195 7240, USA
    J Am Med Inform Assoc 19:817-23. 2012
    ..Based on the information extracted from the narrative reports associated with a patient, the task is to identify whether or not the patient is positive for pneumonia...
  6. ncbi request reprint Using statistical and knowledge-based approaches for literature-based discovery
    Meliha Yetisgen-Yildiz
    Information School, University of Washington, Seattle, WA, USA
    J Biomed Inform 39:600-11. 2006
    ..We also evaluate LitLinker's performance by using the information retrieval metrics of precision and recall...