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Computer Science

D-Index
50
Citations
10909
World Ranking
5586
National Ranking
2550

Overview

Lynette Hirschman is affiliated with Mitre in the United States. Their research portfolio spans several intersecting areas within computer science and biochemistry, genetics, and molecular biology. They have contributed extensively to fields such as molecular biology, toxicology, artificial intelligence, computational theory and mathematics, and safety research.

The scientist's work is prominently focused on biomedical text mining and ontologies, pharmacovigilance and adverse drug reactions, computational drug discovery methods, academic integrity and plagiarism detection, AI in service interactions, genetics, bioinformatics, and biomedical research, as well as pharmaceutical economics and policy.

Frequent coauthors who have collaborated with Lynette Hirschman include John Aberdeen, Tonia Korves, Cheryl Clark, Robyn Kozierok, and Christopher Garay. Collaboration volumes indicate multiple joint publications, reflecting established research partnerships.

Lynette Hirschman has published in a range of academic venues. The most frequent publication platforms include arXiv (Cornell University), Database, Drug Safety, the Journal of the American Medical Informatics Association, and Frontiers in Artificial Intelligence.

Significant recent papers authored or co-authored by Lynette Hirschman include:

  • Challenges and opportunities for mining adverse drug reactions: perspectives from pharma, regulatory agencies, healthcare providers and consumers, 2022, Database
  • ADE Eval: An Evaluation of Text Processing Systems for Adverse Event Extraction from Drug Labels for Pharmacovigilance, 2020, Drug Safety
  • Resilience of clinical text de-identified with "hiding in plain sight" to hostile reidentification attacks by human readers, 2020, Journal of the American Medical Informatics Association
  • Assessing Open-Ended Human-Computer Collaboration Systems: Applying a Hallmarks Approach, 2021, Frontiers in Artificial Intelligence
  • Overview of the COVID-19 text mining tool interactive demonstration track in BioCreative VII, 2022, Database

Best Publications

  • A model-theoretic coreference scoring scheme

    Marc Vilain;John Burger;John Aberdeen;Dennis Connolly

  • Overview of BioCreAtIvE: critical assessment of information extraction for biology

    Lynette Hirschman;Alexander S. Yeh;Christian Blaschke;Alfonso Valencia

  • Accomplishments and challenges in literature data mining for biology

    Lynette Hirschman;Jong C. Park;Junichi Tsujii;Limsoon Wong

  • Overview of BioCreative II gene normalization.

    Alexander A. Morgan;Zhiyong Lu;Xinglong Wang;Aaron M. Cohen

  • 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

  • Natural language question answering: the view from here

    L. Hirschman;R. Gaizauskas

  • Deep Read: A Reading Comprehension System

    Lynette Hirschman;Marc Light;Eric Breck;John D. Burger

  • The TIPSTER SUMMAC Text Summarization Evaluation

    Inderjeet Mani;David House;Gary Klein;Lynette Hirschman

  • Linking genes to literature: text mining, information extraction, and retrieval applications for biology

    Martin Krallinger;Alfonso Valencia;Lynette Hirschman

  • The challenge of spoken language systems: Research directions for the nineties

    R. Cole;L. Hirschman;L. Atlas;M. Beckman

  • Evaluation of text-mining systems for biology: overview of the Second BioCreative community challenge

    Martin Krallinger;Alexander Morgan;Larry Smith;Florian Leitner

  • BioCreAtIvE Task 1A: gene mention finding evaluation

    Unknown

  • MITRE: description of the Alembic system used for MUC-6

    John Aberdeen;John Burger;David Day;Lynette Hirschman

  • The Genomic Standards Consortium

    Dawn Field;Linda A Amaral-Zettler;Guy Cochrane;James R. Cole

  • Evaluation of text data mining for database curation: lessons learned from the KDD Challenge Cup

    Unknown

  • Text mining for the biocuration workflow

    Lynette Hirschman;Gully A. P. C. Burns;Martin Krallinger;Cecilia Arighi

  • Multi-site data collection and evaluation in spoken language understanding

    L. Hirschman;M. Bates;D. Dahl;W. Fisher

  • SUMMAC: a text summarization evaluation

    Inderjeet Mani;Gary Klein;David House;Lynette Hirschman

  • Overview of BioCreAtIvE task 1B: normalized gene lists

    Unknown

  • The MITRE Identification Scrubber Toolkit: Design, training, and assessment

    John S. Aberdeen;Samuel Bayer;Reyyan Yeniterzi;Benjamin Wellner

  • Mixed-Initiative Development of Language Processing Systems

    David Day;John Aberdeen;Lynette Hirschman;Robyn Kozierok

  • Information extraction in molecular biology

    Christian Blaschke;Lynette Hirschman;Alfonso Valencia

  • Text mining and manual curation of chemical-gene-disease networks for the comparative toxicogenomics database (CTD).

    Thomas C Wiegers;Allan Peter Davis;K Bretonnel Cohen;K Bretonnel Cohen;Lynette Hirschman

  • An Overview of BioCreative II.5

    Florian Leitner;Scott A. Mardis;Martin Krallinger;Gianni Cesareni

Frequent Co-Authors

Dawn Field
Dawn Field University of Oxford
Nikos C. Kyrpides
Nikos C. Kyrpides Joint Genome Institute
George M. Garrity
George M. Garrity Michigan State University
Cathy H. Wu
Cathy H. Wu University of Delaware
Frank Oliver Glöckner
Frank Oliver Glöckner Jacobs University
Jack A. Gilbert
Jack A. Gilbert University of California, San Diego
Folker Meyer
Folker Meyer Argonne National Laboratory
Martin Krallinger
Martin Krallinger Barcelona Supercomputing Center
Guy Cochrane
Guy Cochrane European Bioinformatics Institute
Susanna-Assunta Sansone
Susanna-Assunta Sansone University of Oxford

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