World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
48
Citations
9785
World Ranking
6160
National Ranking
2765

Overview

Özlem Uzuner is affiliated with George Mason University in the United States. Their research is primarily focused on the field of Computer Science, with significant contributions in Artificial Intelligence, Molecular Biology, General Health Professions, Sociology and Political Science, and Information Systems.

Their work encompasses a range of topics, with notable emphasis on:

  • Topic Modeling
  • Biomedical Text Mining and Ontologies
  • Machine Learning in Healthcare
  • Natural Language Processing Techniques
  • Hate Speech and Cyberbullying Detection
  • Misinformation and Its Impacts
  • Food Security and Health in Diverse Populations

They have published extensively in prominent venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • Journal of the American Medical Informatics Association
  • Journal of Biomedical Informatics
  • ACM Transactions on Asian and Low-Resource Language Information Processing
  • JMIR Medical Informatics

Their recent papers show a diversity of collaborative and topical focus. Some selected recent publications are:

  • An Empirical Study of Machine learning Algorithms for Social Media Bot Detection (2021), 2021 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)
  • A Survey of Offensive Language Detection for the Arabic Language (2021), ACM Transactions on Asian and Low-Resource Language Information Processing
  • The 2019 n2c2/OHNLP Track on Clinical Semantic Textual Similarity: Overview (2020), JMIR Medical Informatics
  • The 2019 n2c2/UMass Lowell shared task on clinical concept normalization (2020), Journal of the American Medical Informatics Association
  • Large language models for biomedicine: foundations, opportunities, challenges, and best practices (2024), Journal of the American Medical Informatics Association

Özlem Uzuner collaborates regularly with several co-authors, including:

  • Meliha Yetişgen
  • Kevin Lybarger
  • Nicholas J Dobbins
  • Giridhar Kaushik Ramachandran
  • Fatemah Husain

Best Publications

  • 2010 i2b2/VA challenge on concepts, assertions, and relations in clinical text.

    Özlem Uzuner;Brett R South;Shuying Shen;Scott L DuVall

  • Evaluating the State-of-the-Art in Automatic De-identification

    Özlem Uzuner;Yuan Luo;Peter Szolovits

  • Extracting medication information from clinical text

    Özlem Uzuner;Imre Solti;Eithon Cadag

  • Evaluating temporal relations in clinical text: 2012 i2b2 Challenge.

    Weiyi Sun;Anna Rumshisky;Ozlem Uzuner

  • Identifying Patient Smoking Status from Medical Discharge Records

    Özlem Uzuner;Özlem Uzuner;Ira Goldstein;Yuan Luo;Isaac S. Kohane

  • De-identification of patient notes with recurrent neural networks.

    Franck Dernoncourt;Ji Young Lee;Ozlem Uzuner;Peter Szolovits

  • Overcoming barriers to NLP for clinical text: the role of shared tasks and the need for additional creative solutions

    Wendy Webber Chapman;Prakash M. Nadkarni;Lynette Hirschman;Leonard W. D'Avolio;Leonard W. D'Avolio

  • Automated systems for the de-identification of longitudinal clinical narratives

    Amber Stubbs;Christopher Kotfila;Özlem Uzuner

  • 2018 n2c2 shared task on adverse drug events and medication extraction in electronic health records.

    Sam Henry;Kevin Buchan;Michele Filannino;Michele Filannino;Amber Stubbs

  • Viewpoint Paper: Recognizing Obesity and Comorbidities in Sparse Data

    Unknown

  • Annotating longitudinal clinical narratives for de-identification

    Amber Stubbs;Özlem Uzuner

  • Sentiment Analysis of Suicide Notes: A Shared Task.

    John P. Pestian;Pawel Matykiewicz;Michelle Linn-Gust;Brett R South

  • Evaluating the state of the art in coreference resolution for electronic medical records.

    Ozlem Uzuner;Andreea Bodnari;Shuying Shen;Tyler Forbush

  • Identifying risk factors for heart disease over time

    Amber Stubbs;Christopher Kotfila;Hua Xu;Özlem Uzuner

  • CLPsych 2019 Shared Task: Predicting the Degree of Suicide Risk in Reddit Posts

    Ayah Zirikly;Philip Resnik;Özlem Uzuner;Kristy Hollingshead

  • Community annotation experiment for ground truth generation for the i2b2 medication challenge.

    Özlem Uzuner;Imre Solti;Fei Xia;Eithon Cadag

  • Can Linguistic Predictors Detect Fraudulent Financial Filings

    Sunita Goel;Jagdish Gangolly;Sue R. Faerman;Ozlem Uzuner

  • A de-identifier for medical discharge summaries

    Özlem Uzuner;Tawanda C. Sibanda;Yuan Luo;Peter Szolovits

  • De-identification of psychiatric intake records: Overview of 2016 CEGS N-GRID shared tasks Track 1.

    Amber Stubbs;Michele Filannino;Özlem Uzuner

  • Machine Learning and Rule-based Approaches to Assertion Classification

    Özlem Uzuner;Özlem Uzuner;Özlem Uzuner;Xiaoran Zhang;Tawanda C. Sibanda

  • Methodological Review: Annotating temporal information in clinical narratives

    Weiyi Sun;Anna Rumshisky;Ozlem Uzuner

Frequent Co-Authors

Hua Xu
Hua Xu Yale University
Jimmy Lin
Jimmy Lin University of Waterloo
Sushil Jajodia
Sushil Jajodia George Mason University
Mari Ostendorf
Mari Ostendorf University of Washington
Guergana Savova
Guergana Savova Harvard University
Pierre Zweigenbaum
Pierre Zweigenbaum University of Paris-Saclay
Isaac S. Kohane
Isaac S. Kohane Harvard University

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