Use cases
In AVATAR Transfer, the project consortium is working on five key use cases to transfer the developments and technologies researched in the predecessor project AVATAR into the field of application. Partners from academic research and industry are working together on strategies and solutions for the various use cases. This ensures that both scientific background knowledge and the user's perspective are incorporated into the implementation.
The application case will demonstrate how anonymised secondary data can be used for patient-specific evaluation of treatment options in hearing health.
To this end, care pathways and data flows from the project partners involved are analysed and then used to train a prediction model. This model should ultimately make it possible to predict the course of therapies in hearing health to a certain extent.
In this application, methods for using clinical and non-clinical data for rehabilitation in ophthalmology are being developed and tested.
The focus is on an anonymisation service which, with the consent of patients, collates and standardises data from both inside and outside clinical care and makes it available as anonymous data sets. To this end, methods for generating artificial data sets are being further developed in such a way that temporal relationships are preserved while the risk of re-identification is kept as low as possible.
In this application, the use of secondary health data for the development, approval and post-market surveillance (PMS) of medical devices and diagnostics is being investigated. The aim is to research a technical and legal infrastructure that enables the secure and data protection-compliant use of existing healthcare data.
The use case focuses on the secure use of biosignals, e.g. recording brain waves (EEG), through the development, validation and integration of novel anonymisation methods. The aim is to research anonymisation techniques that combine the protection of personal data with the preservation of its medical significance.
To this end, a software toolbox is being developed that anonymises clinical data while ensuring that medical findings remain possible and that the data can be used with AI-supported evaluations.
The focus of the use case is the development and validation of a process for removing human DNA sequences from microbiology sequencing data sets. The aim is to develop a workflow that removes patient references from the sequencing data set while retaining the remaining information content for pathogen diagnostics. To this end, software is being developed that uses Oxford Nanopore Technologies' Read Until API to detect human sequences in real time and remove them from the data set during sequencing.
Vier Anwendungsbeispiele wurden in AVATAR zur Erforschung von verschiedenen Anonymisierungsmethoden und der Entwicklung von Technologien zur Datenabfrage genutzt. Dabei brachten sowohl Partner aus der akademischen Forschung als auch der Industrie ihre eigenen Anwendungsbeispiele ein.
- Hörgesundheitsdaten: Entwicklung von Technologien zur Abfrage verschiedener Datenräume und damit gemeinsamer Datennutzung am Beispiel der Hörgerätetherapie
- Bilddaten: Erforschung von Anonymisierungsmethoden für Bilddaten und tabellarische Daten aus der Optometrie, Nutzung der Daten für MDR/IVDR-konformes Post-Market-Surveillance von Medizinprodukten sowie zu Demonstrations- und Schulungszwecken
- Elektroenzephalographie-Daten: Erforschung von Anonymisierungmethoden für EEG-Daten
- DNA-Sequenzdaten: Erforschung von Anonymisierungmethoden (adaptive Sequenzierung) für die Erregerbestimmung in der Infektionsdiagnostik