Ozlem Uzuner

Summary

Affiliation: University at Albany
Country: USA

Publications

  1. pmc Evaluating the state-of-the-art in automatic de-identification
    Ozlem Uzuner
    University at Albany, SUNY, Draper 114A, 135 Western Ave, Albany, NY 12222, USA
    J Am Med Inform Assoc 14:550-63. 2007
  2. pmc Evaluating the state of the art in coreference resolution for electronic medical records
    Ozlem Uzuner
    Department of Information Studies, University at Albany, SUNY, Albany, New York 12222, USA
    J Am Med Inform Assoc 19:786-91. 2012
  3. pmc 2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text
    Ozlem Uzuner
    Department of Information Studies, University at Albany, State University of New York, Albany, New York 12222, USA
    J Am Med Inform Assoc 18:552-6. 2011
  4. pmc Community annotation experiment for ground truth generation for the i2b2 medication challenge
    Ozlem Uzuner
    Department of Information Studies, University at Albany, State University of New York, Albany, NY, USA
    J Am Med Inform Assoc 17:519-23. 2010
  5. pmc Extracting medication information from clinical text
    Ozlem Uzuner
    Department of Information Studies, University at Albany, State University of New York, Albany, NY, USA
    J Am Med Inform Assoc 17:514-8. 2010
  6. pmc Semantic relations for problem-oriented medical records
    Ozlem Uzuner
    University at Albany, State University of New York, 135 Western Ave, Draper 114A, Albany, NY 12222, USA
    Artif Intell Med 50:63-73. 2010
  7. pmc Recognizing obesity and comorbidities in sparse data
    Ozlem Uzuner
    University at Albany, SUNY, Albany, NY, USA
    J Am Med Inform Assoc 16:561-70. 2009
  8. pmc Machine learning and rule-based approaches to assertion classification
    Ozlem Uzuner
    Information Studies, State Unviersity of New York, Albany, NY, USA
    J Am Med Inform Assoc 16:109-15. 2009
  9. pmc A de-identifier for medical discharge summaries
    Ozlem Uzuner
    University at Albany, State University of New York, Draper 114, Albany, NY 12222, USA
    Artif Intell Med 42:13-35. 2008
  10. pmc Identifying patient smoking status from medical discharge records
    Ozlem Uzuner
    University at Albany, SUNY, Draper 114A, 135 Western Avenue, Albany, NY 12222, USA
    J Am Med Inform Assoc 15:14-24. 2008

Detail Information

Publications11

  1. pmc Evaluating the state-of-the-art in automatic de-identification
    Ozlem Uzuner
    University at Albany, SUNY, Draper 114A, 135 Western Ave, Albany, NY 12222, USA
    J Am Med Inform Assoc 14:550-63. 2007
    ..However, identifying ambiguous PHI proved challenging. The performance of systems on the test data set is encouraging. Future evaluations of these systems will involve larger data sets from more heterogeneous sources...
  2. pmc Evaluating the state of the art in coreference resolution for electronic medical records
    Ozlem Uzuner
    Department of Information Studies, University at Albany, SUNY, Albany, New York 12222, USA
    J Am Med Inform Assoc 19:786-91. 2012
    ..These corpora contained various record types (ie, discharge summaries, pathology reports) from multiple institutions...
  3. pmc 2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text
    Ozlem Uzuner
    Department of Information Studies, University at Albany, State University of New York, Albany, New York 12222, USA
    J Am Med Inform Assoc 18:552-6. 2011
    ..Ensembles of classifiers, information from unlabeled data, and external knowledge sources can help when the training data are inadequate...
  4. pmc Community annotation experiment for ground truth generation for the i2b2 medication challenge
    Ozlem Uzuner
    Department of Information Studies, University at Albany, State University of New York, Albany, NY, USA
    J Am Med Inform Assoc 17:519-23. 2010
    ....
  5. pmc Extracting medication information from clinical text
    Ozlem Uzuner
    Department of Information Studies, University at Albany, State University of New York, Albany, NY, USA
    J Am Med Inform Assoc 17:514-8. 2010
    ..However, they are limited in recognizing duration and reason fields and would benefit from future research...
  6. pmc Semantic relations for problem-oriented medical records
    Ozlem Uzuner
    University at Albany, State University of New York, 135 Western Ave, Draper 114A, Albany, NY 12222, USA
    Artif Intell Med 50:63-73. 2010
    ..We describe semantic relation (SR) classification on medical discharge summaries. We focus on relations targeted to the creation of problem-oriented records. Thus, we define relations that involve the medical problems of patients...
  7. pmc Recognizing obesity and comorbidities in sparse data
    Ozlem Uzuner
    University at Albany, SUNY, Albany, NY, USA
    J Am Med Inform Assoc 16:561-70. 2009
    ..Information on disease-related concepts, such as symptoms and medications, and general medical knowledge help systems infer intuitive judgments on the diseases...
  8. pmc Machine learning and rule-based approaches to assertion classification
    Ozlem Uzuner
    Information Studies, State Unviersity of New York, Albany, NY, USA
    J Am Med Inform Assoc 16:109-15. 2009
    ....
  9. pmc A de-identifier for medical discharge summaries
    Ozlem Uzuner
    University at Albany, State University of New York, Draper 114, Albany, NY 12222, USA
    Artif Intell Med 42:13-35. 2008
    ..For example, medical discharge summaries, which are studied in this paper, are characterized by fragmented, incomplete utterances and domain-specific language; they cannot be fully processed by tools designed for lay language...
  10. pmc Identifying patient smoking status from medical discharge records
    Ozlem Uzuner
    University at Albany, SUNY, Draper 114A, 135 Western Avenue, Albany, NY 12222, USA
    J Am Med Inform Assoc 15:14-24. 2008
    ..g., "smok", "tobac", "cigar", Social History, etc.). Many of the effective smoking status identifiers benefit from these features...
  11. pmc Specializing for predicting obesity and its co-morbidities
    Ira Goldstein
    College of Computing and Information, State University of New York, University at Albany, Draper 114B, 1400 Washington Avenue, Albany, NY 12222, USA
    J Biomed Inform 42:873-86. 2009
    ..We evaluate specializing on each of the 16 diseases and show that it improves significantly over voting and stacking when used for multi-class classification on our data...