Evidence map›Paper›PMID 38789442›Full record

ArticleScientific reports2024

Research collaboration data platform ensuring general data protection.

Monica Toma, Caroline Bönisch, Benjamin Löhnhardt, Michael Kelm, Hanibal Bohnenberger, Sven Winkelmann, Philipp Ströbel, Tibor Kesztyüs

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Monica Toma *Siemens Healthineers AG, Erlangen, Germany. monica.toma@siemens-healthineers.com.
Caroline Bönisch *Medical Data Integration Center, Department of Medical Informatics, University Medical Center Göttingen, Göttingen, Germany. caroline.boenisch@hochschule-stralsund.de.
Benjamin LöhnhardtDepartment of Medical Informatics, University Medical Center Göttingen, Göttingen, Germany.
Michael KelmSiemens Healthineers AG, Erlangen, Germany.
Hanibal BohnenbergerInstitute of Pathology, University Medical Center Göttingen, Göttingen, Germany.
Sven WinkelmannSiemens Healthineers AG, Erlangen, Germany.
Philipp StröbelInstitute of Pathology, University Medical Center Göttingen, Göttingen, Germany.
Tibor KesztyüsMedical Data Integration Center, Department of Medical Informatics, University Medical Center Göttingen, Göttingen, Germany.

Funding

German Federal Ministry of Education and Research 3GW0451
6 · The paper itself

Abstract

Translational data is of paramount importance for medical research and clinical innovation. It has the potential to benefit individuals and organizations, however, the protection of personal data must be guaranteed. Collecting diverse omics data and electronic health records (EHR), re-using the minimized data, as well as providing a reliable data transfer between different institutions are mandatory steps for the development of the promising field of big data and artificial intelligence in medical research. This is made possible within the proposed data platform in this research project. The established data platform enables the collaboration between public and commercial organizations by data transfer from various clinical systems into a cloud for supporting multi-site research while ensuring compliant data governance.

Indexed as

Computer SecurityElectronic Health RecordsBig DataBiomedical ResearchCooperative BehaviorHumans

Identifiers

PMID38789442
PMCPMC11126409

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.