Projects
The QUEST Center conducts projects in various areas.
The unique feature of our projects is their practical and translational focus: we seek to test new approaches in design, analysis and reporting in biomedical research, both preclinical and clinical, to improve translation of research results into clinical care.
The projects are, among others, identified and evaluated by so-called "meta-research", i.e. research on research. The focus of our projects lies on Open Science, Stakeholder Engagement, Incentives & Indicators as well as Quality Assurance (see filter below).
Search results
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Open Science Ongoing ANONY-MED
ANONY-MED creates an ethically aligned, trustworthy AI toolbox for privacy-preserving data synthesis using generative AI methods like GANs and homomorphic encryption in healthcare. This advances AI models in radiology, cardiology, and stroke therapy, while ensuring transparency and robustness.
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Quality Assurance Open Science Closed BUA Open Science Dashboards
The project aims to include FAIR criteria in the Charité Metrics Dashboard and co-develop prototype open science dashboards for other research fields.
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Quality Assurance Open Science Ongoing CARDS
The CARDS project aims to develop and expand tools, services, and training offered to researchers of the Berlin University Alliance (BUA) on the topic of research data management (RDM).
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Quality Assurance Open Science Closed Needs Assessment on Research Data Management at Charité 2021/22
In winter 2021/22, the current status of research data management (RDM) was surveyed throughout the Berlin University Alliance (BUA), i.e. at the Charité and the three large Berlin universities.
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Open Science Ongoing PRO-MaP
This project will develop recommendations for actions that researchers, research institutions, funders publishers can use to promote the sharing of detailed methods and reusable step-by-step protocols in the life sciences.
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Open Science Ongoing Responsible Translation
The project aims to optimize trustworthiness, robustness, usefulness, and transparency of data and algorithm-driven biomedical research. Through conceptual development, meta-research, and stakeholder engagement, we aim to generate evidence-based best practices for high research standards.