Evidence map›Paper›PMID 38740374›Full record

ArticleMethods of information in medicine2024

Europe's Largest Research Infrastructure for Curated Medical Data Models with Semantic Annotations.

Sarah Riepenhausen, Max Blumenstock, Christian Niklas, Stefan Hegselmann, Philipp Neuhaus, Alexandra Meidt, Cornelia Püttmann, Michael Storck, Matthias Ganzinger, Julian Varghese and 1 more

Abstract read
In one paragraph

Article in Methods of information in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Multi-modal dataset creation for federated learning with DICOM-structured reports.International journal of computer assisted radiology and surgery · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Sarah RiepenhausenInstitute of Medical Informatics, University of Münster, Münster, Nordrhein-Westfalen, Germany.
Max BlumenstockInstitute of Medical Informatics, Heidelberg University Hospital, Heidelberg, Germany.
Christian NiklasInstitute of Medical Informatics, Heidelberg University Hospital, Heidelberg, Germany.
Stefan HegselmannInstitute of Medical Informatics, University of Münster, Münster, Nordrhein-Westfalen, Germany.
Philipp NeuhausInstitute of Medical Informatics, University of Münster, Münster, Nordrhein-Westfalen, Germany.
Alexandra MeidtInstitute of Medical Informatics, University of Münster, Münster, Nordrhein-Westfalen, Germany.
Cornelia PüttmannInstitute of Medical Informatics, University of Münster, Münster, Nordrhein-Westfalen, Germany.
Michael StorckInstitute of Medical Informatics, University of Münster, Münster, Nordrhein-Westfalen, Germany.
Matthias GanzingerInstitute of Medical Informatics, Heidelberg University Hospital, Heidelberg, Germany.
Julian VargheseInstitute of Medical Informatics, University of Münster, Münster, Nordrhein-Westfalen, Germany.
Martin DugasInstitute of Medical Informatics, Heidelberg University Hospital, Heidelberg, Germany.

Funding

German Research Foundation (Deutsche Forschungsgemeinschaft, DFG grants) DU 352/11-1German Research Foundation (Deutsche Forschungsgemeinschaft, DFG grants) DU 352/11-2German Research Foundation (Deutsche Forschungsgemeinschaft, DFG grants) DU 352/14-4
6 · The paper itself

Abstract

backgroundStructural metadata from the majority of clinical studies and routine health care systems is currently not yet available to the scientific community.

objectiveTo provide an overview of available contents in the Portal of Medical Data Models (MDM Portal).

methodsThe MDM Portal is a registered European information infrastructure for research and health care, and its contents are curated and semantically annotated by medical experts. It enables users to search, view, discuss, and download existing medical data models.

resultsThe most frequent keyword is "clinical trial" (

conclusionTo our knowledge, the MDM Portal constitutes Europe's largest collection of medical data models with semantically annotated elements. As such, it can be used to increase compatibility of medical datasets and can be utilized as a large expert-annotated medical text corpus for natural language processing.

Indexed as

Data CurationHealth Information SystemsMetadataPublic Health InfrastructureSemanticsHumansNatural Language ProcessingSemantic WebUnified Medical Language System

Identifiers

PMID38740374
PMCPMC11495939

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.