ReviewBundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz2024
[Data processing in secure data processing environments using the example of MRI brain scans-a simultaneous plea for a legal provision for data processing for scientific research purposes].
Review in Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- [Anonymization of general practitioners' electronic medical records in two research datasets].Gesundheitswesen (Bundesverband der Arzte des Offentlichen Gesundheitsdienstes (Germany)) · 2025Article
- Artificial intelligence in neuro-oncology: Current advances and legal considerations in the European Union.Neuro-oncology advancesReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of data for medical scientific research offers great potential for society as a whole, as the evaluation of large volumes of data with machine learning methods can result in new research approaches as well as new methods of diagnostics or treatment. However, the use of such data often fails due to high prerequisites or unclear requirements of data protection law.Processing of radiology data, such as MRI brain scans, is tied to specific risks for data subjects. This complicates the processing of such data for research purposes. Data trustees can help to reduce these risks through offering independent anonymization and pseudonymization services as well as secure processing environments in which health data is stored only for the time required for processing and analysis and is subsequently deleted.Thus, the use of data trustees can help to comply with data protection law, with risk-reduction being considered in favor of processing in decisions weighing the interests for and against data processing as necessary to comply with Art. 9 Para. 2 lit. j, Art. 89 Para 1 of the General Data Protection Regulation (GPDR) in conjunction with national law, or when assessing the compatibility of the secondary purpose of the processing with the purpose of collection. In this respect, the use of data trust models can contribute to the reduction of hurdles for the data processing of health data for scientific research purposes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.