Literature DB >> 32570340

An Evolutionary Approach to the Annotation of Discharge Summaries.

Christina Lohr1,2, Luise Modersohn1,2, Johannes Hellrich1,2, Tobias Kolditz1,2, Udo Hahn1,2.   

Abstract

We here describe the evolution of annotation guidelines for major clinical named entities, namely Diagnosis, Findings and Symptoms, on a corpus of approximately 1,000 German discharge letters. Due to their intrinsic opaqueness and complexity, clinical annotation tasks require continuous guideline tuning, beginning from the initial definition of crucial entities and the subsequent iterative evolution of guidelines based on empirical evidence. We describe rationales for adaptation, with focus on several metrical criteria and task-centered clinical constraints.

Keywords:  Annotation guideline; Clinical text corpus; German discharge summaries

Year:  2020        PMID: 32570340     DOI: 10.3233/SHTI200116

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  2 in total

1.  Annotation and initial evaluation of a large annotated German oncological corpus.

Authors:  Madeleine Kittner; Mario Lamping; Damian T Rieke; Julian Götze; Bariya Bajwa; Ivan Jelas; Gina Rüter; Hanjo Hautow; Mario Sänger; Maryam Habibi; Marit Zettwitz; Till de Bortoli; Leonie Ostermann; Jurica Ševa; Johannes Starlinger; Oliver Kohlbacher; Nisar P Malek; Ulrich Keilholz; Ulf Leser
Journal:  JAMIA Open       Date:  2021-04-19

2.  Automatic extraction of 12 cardiovascular concepts from German discharge letters using pre-trained language models.

Authors:  Phillip Richter-Pechanski; Nicolas A Geis; Christina Kiriakou; Dominic M Schwab; Christoph Dieterich
Journal:  Digit Health       Date:  2021-11-26
  2 in total

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