Literature DB >> 11928488

Creating knowledge repositories from biomedical reports: the MEDSYNDIKATE text mining system.

Udo Hahn1, Martin Romacker, Stefan Schulz.   

Abstract

MEDSYNDIKATE is a natural language processor for automatically acquiring knowledge from medical finding reports. The content of these documents is transferred to formal representation structures which constitute a corresponding text knowledge base. The system architecture integrates requirements from the analysis of single sentences, as well as those of referentially linked sentences forming cohesive texts. The strong demands MEDSYNDIKATE poses to the availability of expressive knowledge sources are accounted for by two alternative approaches to (semi)automatic ontology engineering. We also present data for the knowledge extraction performance of MEDSYNDIKATE for three major syntactic patterns in medical documents.

Mesh:

Year:  2002        PMID: 11928488

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  10 in total

1.  Discovering protein similarity using natural language processing.

Authors:  Indra N Sarkar; Thomas C Rindflesch
Journal:  Proc AMIA Symp       Date:  2002

2.  NLP-based information extraction for managing the molecular biology literature.

Authors:  Bisharah Libbus; Thomas C Rindflesch
Journal:  Proc AMIA Symp       Date:  2002

Review 3.  Natural Language Processing methods and systems for biomedical ontology learning.

Authors:  Kaihong Liu; William R Hogan; Rebecca S Crowley
Journal:  J Biomed Inform       Date:  2010-07-18       Impact factor: 6.317

4.  Automated knowledge acquisition from clinical narrative reports.

Authors:  Xiaoyan Wang; Amy Chused; Noémie Elhadad; Carol Friedman; Marianthi Markatou
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

5.  A flexible framework for deriving assertions from electronic medical records.

Authors:  Kirk Roberts; Sanda M Harabagiu
Journal:  J Am Med Inform Assoc       Date:  2011-07-01       Impact factor: 4.497

6.  Selecting information in electronic health records for knowledge acquisition.

Authors:  Xiaoyan Wang; Herbert Chase; Marianthi Markatou; George Hripcsak; Carol Friedman
Journal:  J Biomed Inform       Date:  2010-03-31       Impact factor: 6.317

Review 7.  Overview of the First Natural Language Processing Challenge for Extracting Medication, Indication, and Adverse Drug Events from Electronic Health Record Notes (MADE 1.0).

Authors:  Abhyuday Jagannatha; Feifan Liu; Weisong Liu; Hong Yu
Journal:  Drug Saf       Date:  2019-01       Impact factor: 5.606

8.  Automated acquisition of disease drug knowledge from biomedical and clinical documents: an initial study.

Authors:  Elizabeth S Chen; George Hripcsak; Hua Xu; Marianthi Markatou; Carol Friedman
Journal:  J Am Med Inform Assoc       Date:  2007-10-18       Impact factor: 4.497

9.  Ranking the whole MEDLINE database according to a large training set using text indexing.

Authors:  Brian P Suomela; Miguel A Andrade
Journal:  BMC Bioinformatics       Date:  2005-03-24       Impact factor: 3.169

10.  A web service for biomedical term look-up.

Authors:  Henk Harkema; Ian Roberts; Rob Gaizauskas; Mark Hepple
Journal:  Comp Funct Genomics       Date:  2005
  10 in total

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