Skip to main content

User account menu

  • Log in
DBS-Logo

Database Group Leipzig

within the department of computer science

ScaDS-Logo Logo of the University of Leipzig

Main navigation

  • Home
  • Study
    • Exams
      • Hinweise zu Klausuren
    • Courses
      • Current
    • Modules
    • LOTS-Training
    • Abschlussarbeiten
    • Masterstudiengang Data Science
    • Oberseminare
    • Problemseminare
    • Top-Studierende
  • Research
    • Projects
      • Benchmark datasets for entity resolution
      • FAMER
      • HyGraph
      • Privacy-Preserving Record Linkage
      • GRADOOP
    • Publications
    • Prototypes
    • Annual reports
    • Cooperations
    • Graduations
    • Colloquia
    • Conferences
  • Team
    • Erhard Rahm
    • Member
    • Former employees
    • Associated members
    • Gallery

Annotating Medical Forms using UMLS

Breadcrumb

  • Home
  • Research
  • Publications
  • Annotating Medical Forms using UMLS

Christen, V. ; Groß, A. ; Varghese, J. ; Dugas, M. ; Rahm, E.

Annotating Medical Forms using UMLS

Proc. 11th Intl. Conference on Data Integration in the Life Sciences (DILS), Los Angeles, July 2015

2015 / 07

Paper

Futher information: http://link.springer.com/chapter/10.1007/978-3-319-21843-4_5

Abstract

Medical forms are frequently used to document patient data or to collect relevant data for clinical trials. It is crucial to harmonize medical forms in order to improve interoperability and data integration between medical applications. Here we propose a (semi-) automatic annotation of medical forms with concepts of the Unified Medical Language System (UMLS). Our annotation workflow encompasses a novel semantic blocking, sophisticated match techniques and post-processing steps to select reasonable annotations. We evaluate our methods based on reference mappings between medical forms and UMLS, and further manually validate the recommended annotations.

<h2 id="bibtex_heading">BibTex</h2>
<pre id="bibtex_listing">
@inproceedings{christen2015annotating,
title={{Annotating Medical Forms Using UMLS}},
author={Christen, Victor and Gro{\\ss}, Anika and Varghese, Julian and Dugas, Martin and Rahm, Erhard},
booktitle={Data Integration in the Life Sciences},
pages={55--69},
year={2015},
organization={Springer}
}

</pre>

Recent publications

  • 2025 / 9: Generating Semantically Enriched Mobility Data from Travel Diaries
  • 2025 / 8: Slice it up: Unmasking User Identities in Smartwatch Health Data
  • 2025 / 7: MPGT: Multimodal Physics-Constrained Graph Transformer Learning for Hybrid Digital Twins
  • 2025 / 6: Leveraging foundation models and goal-dependent annotations for automated cell confluence assessment
  • 2025 / 6: SecUREmatch: Integrating Clerical Review in Privacy-Preserving Record Linkage

Footer menu

  • Directions
  • Contact
  • Impressum