Evidence map›Paper›PMID 26563260›Full record

ArticleBMC medical informatics and decision making2015

Fine-grained information extraction from German transthoracic echocardiography reports.

Martin Toepfer, Hamo Corovic, Georg Fette, Peter Klügl, Stefan Störk, Frank Puppe

Erratum issuedOpen access · goldAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.8field-weighted citation impact, top 15% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 31 citations in OpenAlex.

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  9. Ad Hoc Information Extraction for Clinical Data Warehouses.Methods of information in medicine · 2018
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Martin ToepferChair of Computer Science VI, University of Würzburg, Am Hubland, Würzburg, D-97074, Germany. martin.toepfer@uni-wuerzburg.de.
Hamo CorovicComprehensive Heart Failure Center, University of Würzburg, Straubmühlweg 2a, Würzburg, D-97078, Germany.
Georg FetteChair of Computer Science VI, University of Würzburg, Am Hubland, Würzburg, D-97074, Germany.
Peter KlüglChair of Computer Science VI, University of Würzburg, Am Hubland, Würzburg, D-97074, Germany.
Stefan StörkComprehensive Heart Failure Center, University of Würzburg, Straubmühlweg 2a, Würzburg, D-97078, Germany.
Frank PuppeChair of Computer Science VI, University of Würzburg, Am Hubland, Würzburg, D-97074, Germany.
University of Würzburg · DEAverbis (Germany) · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInformation extraction techniques that get structured representations out of unstructured data make a large amount of clinically relevant information about patients accessible for semantic applications. These methods typically rely on standardized terminologies that guide this process. Many languages and clinical domains, however, lack appropriate resources and tools, as well as evaluations of their applications, especially if detailed conceptualizations of the domain are required. For instance, German transthoracic echocardiography reports have not been targeted sufficiently before, despite of their importance for clinical trials. This work therefore aimed at development and evaluation of an information extraction component with a fine-grained terminology that enables to recognize almost all relevant information stated in German transthoracic echocardiography reports at the University Hospital of Würzburg.

methodsA domain expert validated and iteratively refined an automatically inferred base terminology. The terminology was used by an ontology-driven information extraction system that outputs attribute value pairs. The final component has been mapped to the central elements of a standardized terminology, and it has been evaluated according to documents with different layouts.

resultsThe final system achieved state-of-the-art precision (micro average.996) and recall (micro average.961) on 100 test documents that represent more than 90 % of all reports. In particular, principal aspects as defined in a standardized external terminology were recognized with f 1=.989 (micro average) and f 1=.963 (macro average). As a result of keyword matching and restraint concept extraction, the system obtained high precision also on unstructured or exceptionally short documents, and documents with uncommon layout.

conclusionsThe developed terminology and the proposed information extraction system allow to extract fine-grained information from German semi-structured transthoracic echocardiography reports with very high precision and high recall on the majority of documents at the University Hospital of Würzburg. Extracted results populate a clinical data warehouse which supports clinical research.

Indexed as

EchocardiographyGermanyHumansInformation Storage and RetrievalInformation SystemsThorax

Identifiers

PMID26563260
PMCPMC4643516
OpenAlexW2197629079

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.